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A prime motivation for using XML to directly represent pieces of information is the ability of supporting ad-hoc or 'schema-later' settings. In such scenarios, modeling data under loose data constraints is essential. Of course, the flexibility of XML comes at a price: the absence of a rigid, regular, and homogeneous structure makes many aspects of data management more challenging. Such malleable data formats can also lead to severe information quality problems, because the risk of storing inconsistent and incorrect data is greatly increased. A prominent example of such problems is the appearance of the so-called fuzzy duplicates, i.e., multiple and non-identical representations of a real-world entity. Similarity joins correlating XML document fragments that are similar can be used as core operators to support the identification of fuzzy duplicates. However, similarity assessment is especially difficult on XML datasets because structure, besides textual information, may exhibit variations in document fragments representing the same real-world entity. Moreover, similarity computation is substantially more expensive for tree-structured objects and, thus, is a serious performance concern. This thesis describes the design and implementation of an effective, flexible, and high-performance XML-based similarity join framework. As main contributions, we present novel structure-conscious similarity functions for XML trees - either considering XML structure in isolation or combined with textual information -, mechanisms to support the selection of relevant information from XML trees and organization of this information into a suitable format for similarity calculation, and efficient algorithms for large-scale identification of similar, set-represented objects. Finally, we validate the applicability of our techniques by integrating our framework into a native XML database management system; in this context we address several issues around the integration of similarity operations into traditional database architectures.
Wireless Sensor Networks (WSN) are dynamically-arranged networks typically composed of a large number of arbitrarily-distributed sensor nodes with computing capabilities contributing to –at least– one common application. The main characteristic of these networks is that of being functionally constrained due to a scarce availability of resources and strong dependence on uncontrollable environmental factors. These conditions introduce severe restrictions on the applicability of classic real-time methods aiming at guaranteeing time-bounded communications. Existing real-time solutions tend to apply concepts that were originally not conceived for sensor networks, idealizing realistic application scenarios and overlooking at important design limitations. This results in a number of misleading practices contributing to approaches of restricted validity in real-world scenarios. Amending the confrontation between WSNs and real-time objectives starts with a review of the basic fundamentals of existing approaches. In doing so, this thesis presents an alternative approach based on a generalized timeliness notion suitable to the particularities of WSNs. The new conceptual notion allows the definition of feasible real-time objectives opening a new scope of possibilities not constrained to idealized systems. The core of this thesis is based on the definition and application of Quality of Service (QoS) trade-offs between timeliness and other significant QoS metrics. The analysis of local and global trade-offs provides a step-by-step methodology identifying the correlations between these quality metrics. This association enables the definition of alternative trade-off configurations (set points) influencing the quality performance of the network at selected instants of time. With the basic grounds established, the above concepts are embedded in a simple routing protocol constituting a proof of concept for the validity of the presented analysis. Extensive evaluations under realistic scenarios are driven on simulation environments as well as real testbeds, validating the consistency of this approach.
Wetlands are special areas that they offer habitat for terrestrial and water life. Wetlands are nest sides also for amphibian, for this reason wetlands offer wide range diversity for species. Wetlands are also reproduction regions for birds. Wetlands have special importance for ecosystem because they obstruct erosion. Wetlands absorb contaminants from water therefore wetlands contribute to clean water and they offer more potable water. Wetlands obstruct waterflood. In that case wetlands must be maintained and conserved. Wetlands must be conserved because wetlands vanish very rapidly because of contamination, excessively agriculture, urban sprawl, dams…etc. this PhD thesis contributes to solve problems of wetlands that they are affected from urbanization especially metropolitan areas. Growth of cities requires more land for settlements; the more settlements bring about the more urban sprawl. The more urban sprawl deteriorates more natural regions. In this cycle wetlands are also affected from urbanization effects. In this sense some precautions should be developed in order to protect wetlands from urbanization effect. These precautions should include anticipation about effects of urbanization. An important tool for conserving wetlands and protecting these regions from cities is land uses and land use planning in city and regional planning. First step of land use planning is determination of settlement appropriateness. Settlement appropriateness contributes to choose correct locations for settlement in this respect wetlands can be affected in minimum level from urban sprawl. This PhD thesis inquires a method about buffer zones around wetlands and Thresholds in basin of wetlands; and this method is examined in two case study areas Mogan and Büyükçekmece Lake. According to results of Mogan and Büyükçekmece Lake the PhD method will be generalized to other quasi wetlands that they exist near cities and are affected from urban sprawl.
In robotics, information is often regarded as a means to an end. The question of how to structure information and how to bridge the semantic gap between different levels of abstraction in a uniform way is still widely regarded as a technical issue. Ignoring these challenges appears to lead robotics into a similar stasis as experienced in the software industry of the late 1960s. From the beginning of the software crisis until today, numerous methods, techniques, and tools for managing the increasing complexity of software systems have evolved. The attempt to transfer several of these ideas towards applications in robotics yielded various control architectures, frameworks, and process models. These attempts mainly provide modularisation schemata which suggest how to decompose a complex system into less complex subsystems. The schematisation of representation and information flow however is mostly ignored. In this work, a set of design schemata is proposed which is embedded into an action/perception-oriented design methodology to promote thorough abstractions between distinct levels of control. Action-oriented design decomposes control systems top-down and sensor data is extracted from the environment as required. This comes with the problem that information is often condensed in a premature fashion. That way, sensor processing is dependent on the control system design resulting in a monolithical system structure with limited options for reusability. In contrast, perception-oriented design constructs control systems bottom-up starting with the extraction of environment information from sensor data. The extracted entities are placed into structures which evolve with the development of the sensor processing algorithms. In consequence, the control system is strictly dependent on the sensor processing algorithms which again results in a monolithic system. In their particular domain, both design approaches have great advantages but fail to create inherently modular systems. The design approach proposed in this work combines the strengths of action orientation and perception orientation into one coherent methodology without inheriting their weaknesses. More precisely, design schemata for representation, translation, and fusion of environmental information are developed which establish thorough abstraction mechanisms between components. The explicit introduction of abstractions particularly supports extensibility and scalability of robot control systems by design.
The aim of this thesis was to link Computational Fluid Dynamics (CFD) and Population Balance Modelling (PBM) to gain a combined model for the prediction of counter-current liquid-liquid extraction columns. Parts of the doctoral thesis project were done in close cooperation with the Fraunhofer ITWM. Their in-house CFD code Finite Pointset Method (FPM) was further developed for two-phase simulations and used for the CFD-PBM coupling. The coupling and all simulations were also carried out in the commercial CFD code Fluent in parallel. For the solution methods of the PBM there was a close cooperation with Prof. Attarakih from the Al-Balqa Applied University in Amman, Jordan, who developed a new adaptive method, the Sectional Quadrature Method of Moments (SQMOM). At the beginning of the project, there was a lack of two-phase liquid-liquid CFD simulations and their experimental validation in literature. Therefore, stand-alone CFD simulations without PBM were carried out both in FPM and Fluent to test the predictivity of CFD for stirred liquid-liquid extraction columns. The simulations were validated by Particle Image Velocimetry (PIV) measurements. The two-phase PIV measurements were possible when using an iso-optical system, where the refractive indices of both liquid phases are identical. These investigations were done in segments of two Rotating Disc Contactors with 150mm and 450mm diameter to validate CFD at lab and at industrial scale. CFD results of the aqueous phase velocities, hold-up, droplet raising velocities and turbulent energy dissipation were compared to experimental data. The results show that CFD can predict most phenomena and there was an overall good agreement. In the next steps, different solution methods for the PBM, e.g. the SQMOM and the Quadrature Method of Moments (QMOM) were implemented, varied and tested in Fluent and FPM in a two-fluid model. In addition, different closures for coalescence and breakage were implemented to predict drop size distributions and Sauter mean diameters in the RDC DN150 column. These results show that a prediction of the droplet size distribution is possible, even when no adjustable parameters are used. A combined multi-fluid CFD-PBM model was developed by means of the SQMOM to overcome drawbacks of the two-fluid approach. Benefits of the multi-fluid approach could be shown, but the high computational load was also visible. Therefore, finally, the One Primary One Secondary Particle Method (OPOSPM), which is a very easy and efficient special case of the SQMOM, was introduced in CFD to simulate a full pilot plant column of the RDC DN150. The OPOSPM offers the possibility of a one equation model for the solution of the PBM in CFD. The predicted results for the mean droplet diameter and the dispersed phase hold up agree well with literature data. The results also show that the new CFD-PBM model is very efficient from computational point of view (two times less than the QMOM and five times less than the method of classes). The overall results give rise to the expectation that the coupled CFD-PBM model will lead to a better, faster and more cost-efficient layout of counter-current extraction columns in future.
Prostate cancer preferentially metastasizes to the skeleton and abundant evidence exists that osteoblasts specifically support the metastatic process, including cancer stem cell niche formation. At early stages of bone metastasis, crosstalk of prostate cancer cells and osteoblasts through soluble molecules results in a decrease of cancer cell proliferation, accompanied by altered adhesive properties and increased expression of bone-specific genes, or osteomimicry. Osteoblasts synthesize a plethora of biologically active factors, which comprise the unique bone microenvironment. By means of quantitative real-time RT-PCR it was determined that exposure to the osteoblast secretome induced gene expression changes in prostate cancer cells, including the upregulation of osteomimetic genes such as BMP2, AP, COL1A1, OPG and RANKL. IL6 and TGFbeta1 signaling pathway components also became upregulated at early time points. Moreover, osteoblast-released IL6 and TGFbeta1 contributed to the upregulation of OPG mRNA in LNCaP. Thus, the earliest response of prostate cancer cells to osteoblast-released factors, which ultimately cause metastatic cells to assume an osteomimetic phenotype, involved activation of paracrine and autocrine IL6 and TGFbeta signaling. On the other hand, a microarray analysis showed that osteoblasts exposed to the secretome of prostate cancer cells exhibited gene expression alterations suggestive of repressed proliferation, decreased matrix synthesis and inhibited immune response, which together indicate enhanced preosteocytic differentiation. TGFbeta signaling, known to inhibit osteoblast maturation, was strongly suppressed, as shown by elevated expression of negative regulators, downregulation of pathway components and of numerous target genes. Transcriptional downregulation of osteoblast inhibitory molecules such as DKK1 and FST also occurred, with concomitant upregulation of the osteoinductive molecules ADM, STC1 and BMP2, and of the transcription factors CBFA1 and HES1, which promote osteoblast differentiation. Finally, the mRNA encoding NPPB, the precursor of a molecule implicated in the inhibition of TGFbetaeffects, in bone formation and in stem cell maintenance, became upregulated after coculture both in osteoblasts and in prostate cancer cells. These results provide an insight into potential mechanisms of dysregulated bone formation in metastatic prostate cancer, as well as mechanisms by which osteoblasts might enhance the invasive, osteomimetic and stem cell-like properties of the tumor cells. In particular, the differential modulation of TGFbetasignaling in prostate cancer cells and osteoblasts appears to merit further research.
A number of natural products are known that contain an enamide as a key structural feature. This functionality is a very important subunit in various biologically active products and pharmaceutical drug lead compounds. In addition, enamides serve as highly versatile synthetic intermediates, particularly in the pericyclic reaction, formation of heterocycles, cross-coupling and in asymmetric synthesis. As a result, several protocols have been devised for the preparation of enamides. Traditional syntheses include condensation of aldehydes and ketones with amides or from hydroxylamines and acetic anhydride, require harsh conditions and yield mixtures of E/Z products. Several metal catalyzed approaches have been also investigated, such as isomerization of N-allylamides and catalytic cross-coupling of amides with vinyl halides or pseudohalides. These protocols proceed under milder conditions but suffer from the limited availability of these starting materials. The research described in this dissertation focuses on efficient and atom-economic preparation of enamides and thioenamides, using readily available starting materials. We developed catalyst systems generated in situ from bis(2-methallyl)-cycloocta-1,5-diene-ruthenium(II), phosphines and Lewis acid or base, efficiently catalyze the addition of primary amides and thioamides to terminal alkynes with exclusive formation of the anti-Markovnikov products in high yield and stereoselectivity under mild reaction conditions. The generality of the newly developed methodologies is demonstrated by common functional group tolerance. Furthermore, Markovnikov products were formed via phosphine-catalyzed addition of cyclic amides to phenylacetylene derivatives. The hydroamidation protocol of primary amides was successfully used in the synthesis of naturally occurring compounds, such as alatamide, lansiumamide A, botryllamides C and E, and the key intermediate in the synthesis of aristolactam. In order to investigate the reaction mechanism, the addition of various amides and carboxylic acids to terminal alkynes was performed using deuterium labeled starting materials and followed by in situ NMR and GC-MS studies.
A classical conjecture in the representation theory of finite groups, the McKay conjecture, states that for any finite group and prime number p the number of complex irreducible characters of degree prime to p is equal to the number of complex irreducible characters of degree prime to p of the normalizer of a p-Sylow subgroup. Recently a reduction theorem was proved by Isaacs, Malle and Navarro: If all simple groups are “good”, then the McKay conjecture holds. In this work we are concerned with the problem of goodness for finite groups of Lie type in their defining characteristic. A simple group is called “good” if certain equivariant bijections between the involved character sets exist. We present a structural approach to the construction of such a bijection by utilizing the so-called “Steinberg-Map”. This yields very natural bijections and we prove most of the desired properties.
The aim of this study is to describe the consolidation in thermoplastic tape placement
process to obtain high quality structure, making the process viable for automotive
and aerospace industrial applications. The major barrier in this technique is very
short residence time of material under the consolidation roller to accomplished complete
polymer diffusion in the bonded region. Hence investigation is performed to find
out the optimize manufacturing parameters by extensive material, process, product
testing and through process simulation.
Temperature distribution and convective heat transfer under the hot gas torch is experimentally
mapped out. Bonding process inside the laminate is the combine effect
of layers (tapes) intimate contact Dic development and resulting polymer diffusion Dh
at these contacted sections. Three energy levels are identified based on the process
velocity and hot gas flow combinations. For the low energy parameter combinations,
the energy input to the incoming tape and substrate material is limited and result in
incomplete intimate contact which restricts the bonding process. On other hand high
energy input although could increase the bonding degree Db even up to the 97%, but
also activate the thermal degradation phenomena. It is found out that the rate of polymer
healing (diffusion) and polymer crosslinking follows the Arrhenius laws with the
activation energies of 43 KJ/mol and 276 KJ/mol. The polymer crosslinking at high
temperature exposure hinder the polymer diffusion process and reduces the strength
development. So the parameters combination at intermediate energy level provides
the opportunity of continuous interlaminar strength improvement through out the layup
process.
Deformation of tape edges is identified as the dictating factor for the laminate’s transverse
strength. Tape placement with slight overlap reinforced the transverse joint by
more 10 % as compared to pure matrix joint. Finally the simulation tool developed in
this research work is used for identifying the existing limitation to achieve full consolidation.
A parameter study shows that extended consolidation either by mean of additional
pass or by increasing consolidation length widens the high strength (over 90%)
bonding degree Db contour. Thus high lay-up velocity (up to 7 m/min) is viable for industrial
production rate.
Mrázek et al. [25] proposed a unified approach to curve estimation which combines localization and regularization. Franke et al. [10] used that approach to discuss the case of the regularized local least-squares (RLLS) estimate. In this thesis we will use the unified approach of Mrázek et al. to study some asymptotic properties of local smoothers with regularization. In particular, we shall discuss the Huber M-estimate and its limiting cases towards the L2 and the L1 cases. For the regularization part, we will use quadratic regularization. Then, we will define a more general class of regularization functions. Finally, we will do a Monte Carlo simulation study to compare different types of estimates.