100 resultados para Composite Dynamic Object


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Tämän diplomityön tavoitteena oli selvittää puupohjaisten kuitukomposiittimateriaalien soveltuvuutta veneteollisuuden valmistusmateriaaliksi. Huviveneiden rakennusta säätelee huvivenedirektiivi ja lukuisat standardit. Standardien mukaan uusien materiaalien käyttö veneenrakennuksessa on mahdollista, mikäli materiaalin ominaisuudet todetaan muun muassa laboratoriotesteissä soveltuviksi kyseiseen käyttötarkoitukseen. Tutkimusta varten valmistettiin kuusi erilaista kuitukomposiittimateriaalia. Tutkimuksessa käytettiin myös neljän kaupallisen puumuovikomposiittivalmistajan materiaalia. Vertailumateriaaleiksi valittiin puuraaka-aineista mänty, saarni ja mahonki sekä muoviraakaaineista ABS – muovi. Tarkisteltaville materiaaleille määriteltiin standardien mukaisin testein taivutuslujuus, vetolujuus, Charpy – iskulujuus, Brinell – kovuus, veden absorptio sekä paksuusturpoama. Saatuja arvoja vertailtiin vertailumateriaalien kirjallisuudessa mainittuihin arvoihin. Puupohjaisten kuitukomposiittien ominaisuudet jäivät vertailumateriaalien vastaavista lukuun ottamatta Brinell – kovuutta. Taivutus- ja vetolujuuden osalta eräiden kaupallisten puumuovikomposiittivalmistajien ilmoittamat lujuusarvot olivat lähellä veneenrakennuksessa käytettyjen materiaalien vastaavia. Suurimpana yksittäisenä haasteena puukuitupohjaisilla kuitukomposiiteilla havaittiin Charpy – iskulujuus. Myös veden absorption saattaminen alhaiseksi havaittiin tärkeäksi veneilysovelluksissa. Ominaisuuksien kehittäminen on kuitenkin käytettävissä olevan tutkimustiedon perusteella mahdollista. Diplomityössä saatujen tulosten perusteella on puupohjaisilla kuitukomposiiteilla potentiaalia veneteollisuudessa. Jatkotutkimusta tulisikin kohdistaa materiaalin ominaisuuksien kehittämiseen.

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This study presents the information required to describe the machine and device resources in the turret punch press environment which are needed for the development of the analysing method for automated production. The description of product and device resources and their interconnectedness is the starting point for method comparison the development of expenses, production planning and the performance of optimisation. The manufacturing method cannot be optimized unless the variables and their interdependence are known. Sheet metal parts in particular may then become remarkably complex, and their automatic manufacture may be difficult or, with some automatic equipment, even impossible if not know manufacturing properties. This thesis consists of three main elements, which constitute the triangulation. In the first phase of triangulation, the manufacture occuring on a turret punch press is examined in order to find the factors that affect the efficiency of production. In the second phase of triangulation, the manufacturability of products on turret punch presses is examined through a set of laboratory tests. The third phase oftriangulation involves an examination of five industry parts. The main key findings of this study are: all possible efficiency in high automation level machining cannot be achieved unless the raw materials used in production and the dependencies of the machine and tools are well known. Machine-specific manufacturability factors for turret punch presses were not taken into account in the industrial case samples. On the grounds of the performed tests and industrial case samples, the designer of a sheet metal product can directly influence the machining time, material loss, energy consumption and the number of tools required on a turret punch press by making decisions in the way presented in the hypothesis of thisstudy. The sheet metal parts to be produced can be optimised to bemanufactured on a turret punch press when the material to be used and the kinds of machine and tool options available are known. This provides in-depth knowledge of the machine and tool properties machine and tool-specifically. None of the optimisation starting points described here is a separate entity; instead, they are all connected to each other.

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Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

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The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

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Dental oxide ceramics have been inspired by their biocompability and mechanical properties which have made durable all-ceramic structures possible. Clinical longevity of the prosthetic structures is dependent on effective bonding with luting cements. As the initial shear bond strength values can be comparable with several materials and procedures, long-term durability is affected by ageing. Aims of the current study were: to measure the shear bond strength of resin composite-to-ceramics and to evaluate the longevity of the bond; to analyze factors affecting the bond, with special emphasis on: the form of silicatization of the ceramic surface; form of silanization; type of resin primer and the effect of the type of the resin composite luting cement; the effect of ageing in water was studied regarding its effect to the endurance of the bond. Ceramic substrates were alumina and yttrium stabilized zirconia. Ceramic conditioning methods included tribochemical silicatization and use of two silane couplings agents. A commercial silane primer was used as a control silane. Various combinations of conditioning methods, primers and resin cements were tested. Bond strengths were measured by shear bond strength method. The longevity of the bond was generally studied by thermocycling the materials in water. Additionally, in one of the studies thermal cycling was compared with long-term water storaging. Results were analysed statistically with ANOVA and Weibull analysis. Tribochemical treatment utilizing air pressure of 150 kPa resulted shear bond strengths of 11.2 MPa to 18.4 MPa and air pressure of 450 kPa 18.2 MPa to 30.5 MPa, respectively. Thermocycling of 8000 cycles or four years water storaging both decreased shear bond strength values to a range of 3.8 MPa to 7.2 MPa whereas initial situation varied from 16.8. Mpa to 23.0 MPa. The silane used in studies had no statistical significance. The use of primers without 10-MDP resulted spontaneous debonding during thermocycling or shear bond strengths below 5 MPa. As conclusion, the results showed superior long-term bonding with primers containing 10-MDP. Silicatization with silanizing showed improved initial shear bond strength values which considerably decreased with ageing in water. Thermal cycling and water storing for up to four years played the major role in reduction of bond strength, which could be due to thermal fatigue of the bonding interface and hydrolytic degradation of the silane coupled interface.

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The objective of this dissertation is to improve the dynamic simulation of fluid power circuits. A fluid power circuit is a typical way to implement power transmission in mobile working machines, e.g. cranes, excavators etc. Dynamic simulation is an essential tool in developing controllability and energy-efficient solutions for mobile machines. Efficient dynamic simulation is the basic requirement for the real-time simulation. In the real-time simulation of fluid power circuits there exist numerical problems due to the software and methods used for modelling and integration. A simulation model of a fluid power circuit is typically created using differential and algebraic equations. Efficient numerical methods are required since differential equations must be solved in real time. Unfortunately, simulation software packages offer only a limited selection of numerical solvers. Numerical problems cause noise to the results, which in many cases leads the simulation run to fail. Mathematically the fluid power circuit models are stiff systems of ordinary differential equations. Numerical solution of the stiff systems can be improved by two alternative approaches. The first is to develop numerical solvers suitable for solving stiff systems. The second is to decrease the model stiffness itself by introducing models and algorithms that either decrease the highest eigenvalues or neglect them by introducing steady-state solutions of the stiff parts of the models. The thesis proposes novel methods using the latter approach. The study aims to develop practical methods usable in dynamic simulation of fluid power circuits using explicit fixed-step integration algorithms. In this thesis, twomechanisms whichmake the systemstiff are studied. These are the pressure drop approaching zero in the turbulent orifice model and the volume approaching zero in the equation of pressure build-up. These are the critical areas to which alternative methods for modelling and numerical simulation are proposed. Generally, in hydraulic power transmission systems the orifice flow is clearly in the turbulent area. The flow becomes laminar as the pressure drop over the orifice approaches zero only in rare situations. These are e.g. when a valve is closed, or an actuator is driven against an end stopper, or external force makes actuator to switch its direction during operation. This means that in terms of accuracy, the description of laminar flow is not necessary. But, unfortunately, when a purely turbulent description of the orifice is used, numerical problems occur when the pressure drop comes close to zero since the first derivative of flow with respect to the pressure drop approaches infinity when the pressure drop approaches zero. Furthermore, the second derivative becomes discontinuous, which causes numerical noise and an infinitely small integration step when a variable step integrator is used. A numerically efficient model for the orifice flow is proposed using a cubic spline function to describe the flow in the laminar and transition areas. Parameters for the cubic spline function are selected such that its first derivative is equal to the first derivative of the pure turbulent orifice flow model in the boundary condition. In the dynamic simulation of fluid power circuits, a tradeoff exists between accuracy and calculation speed. This investigation is made for the two-regime flow orifice model. Especially inside of many types of valves, as well as between them, there exist very small volumes. The integration of pressures in small fluid volumes causes numerical problems in fluid power circuit simulation. Particularly in realtime simulation, these numerical problems are a great weakness. The system stiffness approaches infinity as the fluid volume approaches zero. If fixed step explicit algorithms for solving ordinary differential equations (ODE) are used, the system stability would easily be lost when integrating pressures in small volumes. To solve the problem caused by small fluid volumes, a pseudo-dynamic solver is proposed. Instead of integration of the pressure in a small volume, the pressure is solved as a steady-state pressure created in a separate cascade loop by numerical integration. The hydraulic capacitance V/Be of the parts of the circuit whose pressures are solved by the pseudo-dynamic method should be orders of magnitude smaller than that of those partswhose pressures are integrated. The key advantage of this novel method is that the numerical problems caused by the small volumes are completely avoided. Also, the method is freely applicable regardless of the integration routine applied. The superiority of both above-mentioned methods is that they are suited for use together with the semi-empirical modelling method which necessarily does not require any geometrical data of the valves and actuators to be modelled. In this modelling method, most of the needed component information can be taken from the manufacturer’s nominal graphs. This thesis introduces the methods and shows several numerical examples to demonstrate how the proposed methods improve the dynamic simulation of various hydraulic circuits.

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The aim of the study was to create and evaluate an intervention programme for Tanzanian children from a low-income area who are at risk of reading and writing difficulties. The learning difficulties, including reading and writing difficulties, are likely to be behind many of the common school problems in Tanzania, but they are not well understood, and research is needed. The design of the study included an identification and intervention phase with follow-up. A group based dynamic assessment approach was used in identifying children at risk of difficulties in reading and writing. The same approach was used in the intervention. The study was a randomized experiment with one experimental and two control groups. For the experimental and the control groups, a total of 96 (46 girls and 50 boys) children from grade one were screened out of 301 children from two schools in a low income urban area of Dar-es-Salaam. One third of the children, the experimental group, participated in an intensive training programme in literacy skills for five weeks, six hours per week, aimed at promoting reading and writing ability, while the children in the control groups had a mathematics and art programme. Follow-up was performed five months after the intervention. The intervention programme and the tests were based on the Zambian BASAT (Basic Skill Assessment Tool, Ketonen & Mulenga, 2003), but the content was drawn from the Kiswahili school curriculum in Tanzania. The main components of the training and testing programme were the same, only differing in content. The training process was different from traditional training in Tanzanian schools in that principles of teaching and training in dynamic assessment were followed. Feedback was the cornerstone of the training and the focus was on supporting the children in exploring knowledge and strategies in performing the tasks. The experimental group improved significantly more (p = .000) than the control groups during the intervention from pre-test to follow-up (repeated measures ANOVA). No differences between the control groups were noticed. The effect was significant on all the measures: phonological awareness, reading skills, writing skills and overall literacy skills. A transfer effect on school marks in Kiswahili and English was found. Following a discussion of the results, suggestions for further research and adaptation of the programme are presented.

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The consumption of manganese is increasing, but huge amounts of manganese still end up in waste in hydrometallurgical processes. The recovery of manganese from multi-metal solutions at low concentrations may not be economical. In addition, poor iron control typically prevents the production of high purity manganese. Separation of iron from manganese can be done with chemical precipitation or solvent extraction methods. Combined carbonate precipitation with air oxidation is a feasible method to separate iron and manganese due to the fast kinetics, good controllability and economical reagents. In addition the leaching of manganese carbonate is easier and less acid consuming than that of hydroxide or sulfide precipitates. Selective iron removal with great efficiency from MnSO4 solution is achieved by combined oxygen or air oxidation and CaCO3 precipitation at pH > 5.8 and at a redox potential of > 200 mV. In order to avoid gypsum formation, soda ash should be used instead of limestone. In such case, however, extra attention needs to be paid on the reagents mole ratios in order to avoid manganese coprecipitation. After iron removal, pure MnSO4 solution was obtained by solvent extraction using organophosphorus reagents, di-(2-ethylhexyl)phosphoric acid (D2EHPA) and bis(2,4,4- trimethylpentyl)phosphinic acid (CYANEX 272). The Mn/Ca and Mn/Mg selectivities can be increased by decreasing the temperature from the commonly used temperatures (40 –60oC) to 5oC. The extraction order of D2EHPA (Ca before Mn) at low temperature remains unchanged but the lowering of temperature causes an increase in viscosity and slower phase separation. Of these regents, CYANEX 272 is selective for Mn over Ca and, therefore, it would be the better choice if there is Ca present in solution. A three-stage Mn extraction followed by a two-stage scrubbing and two-stage sulfuric acid stripping is an effective method of producing a very pure MnSO4 intermediate solution for further processing. From the intermediate MnSO4 some special Mn- products for ion exchange applications were synthesized and studied. Three types of octahedrally coordinated manganese oxide materials as an alternative final product for manganese were chosen for synthesis: layer structured Nabirnessite, tunnel structured Mg-todorokite and K-kryptomelane. As an alternative source of pure MnSO4 intermediate, kryptomelane was synthesized by using a synthetic hydrometallurgical tailings. The results show that the studied OMS materials adsorb selectively Cu, Ni, Cd and K in the presence of Ca and Mg. It was also found that the exchange rates were reasonably high due to the small particle dimensions. Materials are stable in the studied conditions and their maximum Cu uptake capacity was 1.3 mmol/g. Competitive uptake of metals and acid was studied using equilibrium, batch kinetic and fixed-bed measurements. The experimental data was correlated with a dynamic model, which also accounts for the dissolution of the framework manganese. Manganese oxide micro-crystals were also bound onto silica to prepare a composite material having a particle size large enough to be used in column separation experiments. The MnOx/SiO2 ratio was found to affect significantly the properties of the composite. The higher the ratio, the lower is the specific surface area, the pore volume and the pore size. On the other hand, higher amount of silica binder gives composites better mechanical properties. Birnesite and todorokite can be aggregated successfully with colloidal silica at pH 4 and with MnO2/SiO2 weight ratio of 0.7. The best gelation and drying temperature was 110oC and sufficiently strong composites were obtained by additional heat-treatment at 250oC for 2 h. The results show that silica–supported MnO2 materials can be utilized to separate copper from nickel and cadmium. The behavior of the composites can be explained reasonably well with the presented model and the parameters estimated from the data of the unsupported oxides. The metal uptake capacities of the prepared materials were quite small. For example, the final copper loading was 0.14 mmol/gMnO2. According to the results the special MnO2 materials are potential for a specific environmental application to uptake harmful metal ions.

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In this thesis, general approach is devised to model electrolyte sorption from aqueous solutions on solid materials. Electrolyte sorption is often considered as unwanted phenomenon in ion exchange and its potential as an independent separation method has not been fully explored. The solid sorbents studied here are porous and non-porous organic or inorganic materials with or without specific functional groups attached on the solid matrix. Accordingly, the sorption mechanisms include physical adsorption, chemisorption on the functional groups and partition restricted by electrostatic or steric factors. The model is tested in four Cases Studies dealing with chelating adsorption of transition metal mixtures, physical adsorption of metal and metalloid complexes from chloride solutions, size exclusion of electrolytes in nano-porous materials and electrolyte exclusion of electrolyte/non-electrolyte mixtures. The model parameters are estimated using experimental data from equilibrium and batch kinetic measurements, and they are used to simulate actual single-column fixed-bed separations. Phase equilibrium between the solution and solid phases is described using thermodynamic Gibbs-Donnan model and various adsorption models depending on the properties of the sorbent. The 3-dimensional thermodynamic approach is used for volume sorption in gel-type ion exchangers and in nano-porous adsorbents, and satisfactory correlation is obtained provided that both mixing and exclusion effects are adequately taken into account. 2-Dimensional surface adsorption models are successfully applied to physical adsorption of complex species and to chelating adsorption of transition metal salts. In the latter case, comparison is also made with complex formation models. Results of the mass transport studies show that uptake rates even in a competitive high-affinity system can be described by constant diffusion coefficients, when the adsorbent structure and the phase equilibrium conditions are adequately included in the model. Furthermore, a simplified solution based on the linear driving force approximation and the shrinking-core model is developed for very non-linear adsorption systems. In each Case Study, the actual separation is carried out batch-wise in fixed-beds and the experimental data are simulated/correlated using the parameters derived from equilibrium and kinetic data. Good agreement between the calculated and experimental break-through curves is usually obtained indicating that the proposed approach is useful in systems, which at first sight are very different. For example, the important improvement in copper separation from concentrated zinc sulfate solution at elevated temperatures can be correctly predicted by the model. In some cases, however, re-adjustment of model parameters is needed due to e.g. high solution viscosity.

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The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

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This thesis investigates the effectiveness of time-varying hedging during the financial crisis of 2007 and the European Debt Crisis of 2010. In addition, the seven test economies are part of the European Monetary Union and these countries are in different economical states. Time-varying hedge ratio was constructed using conditional variances and correlations, which were created by using multivariate GARCH models. Here we have used three different underlying portfolios: national equity markets, government bond markets and the combination of these two. These underlying portfolios were hedged by using credit default swaps. Empirical part includes the in-sample and out-of-sample analysis, which are constructed by using constant and dynamic models. Moreover, almost in every case dynamic models outperform the constant ones in the determination of the hedge ratio. We could not find any statistically significant evidence to support the use of asymmetric dynamic conditional correlation model. In addition, our findings are in line with prior literature and support the use of time-varying hedge ratio. Finally, we found that in some cases credit default swaps are not suitable instruments for hedging and they act more as a speculative instrument.

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This master’s thesis aims to examine the relationship between dynamic capabilities and operational-level innovations. In addition, measures for the concept of dynamic capabilities are developed. The study was executed in the magazine publishing industry which is considered favourable for examining dynamic capabilities, since the sector is characterized by rapid change. As a basis for the study and the measure development, a literary review was conducted. Data for the empirical section was gathered by a survey targeted to chief-editors of Finnish consumer magazines. The relationship between dynamic capabilities and innovation was examined by multiple linear regression. The results indicate that dynamic capabilities have effect on the emergence of radical innovations. Environmental dynamism’s effect on radical innovations was not detected. Also, dynamic capabilities’ effect on innovation was not greater in turbulent operating environment.

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Object-oriented programming is a widely adopted paradigm for desktop software development. This paradigm partitions software into separate entities, objects, which consist of data and related procedures used to modify and inspect it. The paradigm has evolved during the last few decades to emphasize decoupling between object implementations, via means such as explicit interface inheritance and event-based implicit invocation. Inter-process communication (IPC) technologies allow applications to interact with each other. This enables making software distributed across multiple processes, resulting in a modular architecture with benefits in resource sharing, robustness, code reuse and security. The support for object-oriented programming concepts varies between IPC systems. This thesis is focused on the D-Bus system, which has recently gained a lot of users, but is still scantily researched. D-Bus has support for asynchronous remote procedure calls with return values and a content-based publish/subscribe event delivery mechanism. In this thesis, several patterns for method invocation in D-Bus and similar systems are compared. The patterns that simulate synchronous local calls are shown to be dangerous. Later, we present a state-caching proxy construct, which avoids the complexity of properly asynchronous calls for object inspection. The proxy and certain supplementary constructs are presented conceptually as generic object-oriented design patterns. The e ect of these patterns on non-functional qualities of software, such as complexity, performance and power consumption, is reasoned about based on the properties of the D-Bus system. The use of the patterns reduces complexity, but maintains the other qualities at a good level. Finally, we present currently existing means of specifying D-Bus object interfaces for the purposes of code and documentation generation. The interface description language used by the Telepathy modular IM/VoIP framework is found to be an useful extension of the basic D-Bus introspection format.