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Synapses are the fundamental structures that regulate the functionality of the neural circuit. The ability of the synapse to modulate its structure and function at a fast rate due to various sensory inputs provides the strength to the nervous system to incorporate new adaptations and behaviors in the animal. The synapses are very dynamic throughout the life of the animal starting from early development. Continuous events of formation and elimination of synapse, activation and inhibition of synaptic function are observed in almost all synapses. These processes occur at a high speed and require controlled cellular mechanisms. Imbalance in these processes results in defective nervous system and has been reported in many neurological disorders. Thus, it is important to understand the mechanisms that regulate process of synapse development maintenance and function.
Kinases and phosphatases are the key regulators of cellular mechanisms. Understanding the function of these molecules in the neuron will shed light on the molecular mechanisms of synaptic plasticity. Using Drosophila melanogaster larval neuromuscular junction as a model, Bulat et al. (2014) performed a large RNAi based screen targeting kinome and phosphatome of Drosophila to identify the essential kinases and phosphatases and found Myeloid leukemia factor-1 adaptor molecule (Madm) and Protein phosphatase 4 (PP4) as novel regulators of synapse development and maintenance. The function of these molecules in the nervous system has not been reported and hence I investigated on the role of Madm and PP4 in the regulation of synapse development, maintenance and function.
Myeloid leukemia factor-1 adaptor molecule (Madm), a ubiquitously expressing psuedokinase essentially functions to regulate synaptic growth, stability and function. Using a combination of genetic and high throughput imaging, I could demonstrate that Madm functions to regulate the synaptic growth and stability from the presynapse and synaptic organization form the postsynapse. Also, I could demonstrate that Madm functions in association with mTOR pathway to regulate synapse growth acting downstream of 4E-BP. In addition, using electrophysiology, we could demonstrate that Madm is essential for the basic synaptic transmission with an additive function of retrograde synaptic potentiation. In summary, I could demonstrate that Madm is a novel regulator of synaptic development, maintenance and function.
Protein phosphatase 4 (PP4), a ubiquitously expressing protein phosphatase is involved in the regulation of multiple aspects of the nervous system. I could demonstrate that PP4 is essential for the development of nervous system and the metamorphosis. Using genetics and imaging analysis, I could demonstrate that loss of PP4 results in the abnormal morphology of cell organelles. In addition, I could show that loss of PP4 results in defective brain development with poorly developed structures.
Altogether, in this study, I could demonstrate the importance of novel molecules, a pesudokinase Madm and protein phosphatases PP4 in the nervous system to regulate distinct aspects of the neuron.
With the burgeoning computing power available, multiscale modelling and simulation has these days become increasingly capable of capturing the details of physical processes on different scales. The mechanical behavior of solids is oftentimes the result of interaction between multiple spatial and temporal scales at different levels and hence it is a typical phenomena of interest exhibiting multiscale characteristic. At the most basic level, properties of solids can be attributed to atomic interactions and crystal structure that can be described on nano scale. Mechanical properties at the macro scale are modeled using continuum mechanics for which we mention stresses and strains. Continuum models, however they offer an efficient way of studying material properties they are not accurate enough and lack microstructural information behind the microscopic mechanics that cause the material to behave in a way it does. Atomistic models are concerned with phenomenon at the level of lattice thereby allowing investigation of detailed crystalline and defect structures, and yet the length scales of interest are inevitably far beyond the reach of full atomistic computation and is rohibitively expensive. This makes it necessary the need for multiscale models. The bottom line and a possible avenue to this end is, coupling different length scales, the continuum and the atomistics in accordance with standard procedures. This is done by recourse to the Cauchy-Born rule and in so doing, we aim at a model that is efficient and reasonably accurate in mimicking physical behaviors observed in nature or laboratory. In this work, we focus on concurrent coupling based on energetic formulations that links the continuum to atomistics. At the atomic scale, we describe deformation of the solid by the displaced positions of atoms that make up the solid and at the continuum level deformation of the solid is described by the displacement field that minimize the total energy. In the coupled model, continuum-atomistic, a continuum formulation is retained as the overall framework of the problem and the atomistic feature is introduced by way of constitutive description, with the Cauchy-Born rule establishing the point of contact. The entire formulation is made in the framework of nonlinear elasticity and all the simulations are carried out within the confines of quasistatic settings. The model gives direct account to measurable features of microstructures developed by crystals through sequential lamination.
Understanding human crowd behaviour has been an intriguing topic of interdisciplinary research in recent decades. Modelling of crowd dynamics using differential equations is an indispensable approach to unraveling the various complex dynamics involved in such interacting particle systems. Numerical simulation of pedestrian crowd via these mathematical models allows us to study different realistic scenarios beyond the limitations of studies via controlled experiments.
In this thesis, the main objective is to understand and analyse the dynamics in a domain shared by both pedestrians and moving obstacles. We model pedestrian motion by combining the social force concept with the idea of optimal path computation. This leads to a system of ordinary differential equations governing the dynamics of individual pedestrians via the interaction forces (social forces) between them. Additionally, a non-local force term involving the optimal path and desired velocity governs the pedestrian trajectory. The optimal path computation involves solving a time-independent Eikonal equation, which is coupled to the system of ODEs. A hydrodynamic model is developed from this microscopic model via the mean-field limit.
To consider the interaction with moving obstacles in the domain, we model a set of kinematic equations for the obstacle motion. Two kinds of obstacles are considered - "passive", which move in their predefined trajectories and have only a one-way interaction with pedestrians, and "dynamic", which have a feedback interaction with pedestrians and have their trajectories changing dynamically. The coupled model of pedestrians and obstacles is used to discern pedestrian collision avoidance behaviour in different computational scenarios in a long rectangular domain. We observe that pedestrians avoid collisions through route choice strategies that involve changes in speed and path. We extend this model to consider the interaction between pedestrians and vehicular traffic. We appropriately model the interactions of vehicles, following lane traffic, based on the car-following approach. We observe how the deceleration and braking mechanism of vehicles is executed at pedestrian crossings depending on the right of way on the roads.
As a second objective, we study the disease contagion in moving crowds. We consider the influence of the crowd motion in a complex dynamical environment on the course of infection of pedestrians. A hydrodynamic model for multi-group pedestrian flow is derived from the kinetic equations based on a social force model. It is coupled along with an Eikonal equation to a non-local SEIS contagion model for disease spread. Here, apart from the description of local contacts, the influence of contact times has also been modelled. We observe that the nature of the flow and the geometry of the domain lead to changes in density which affect the contact time and, consequently, the rate of spread of infection.
Finally, the social force model is compared to a variable speed based rational behaviour pedestrian model. We derive a hierarchy of the heuristics-based model from microscopic to macroscopic scales and numerically investigate these models in different density scenarios. Various numerical test cases are considered, including uni- and bi-directional flows and scenarios with and without obstacles. We observe that in low-density scenarios, collision avoidance forces arising from the behavioural heuristics give valid results. Whereas in high-density scenarios, repulsive force terms are essential.
The numerical simulations of all the models are carried out using a mesh-free particle method based on least square approximations. The meshfree numerical framework provides an efficient and elegant way to handle complex geometric situations involving boundaries and stationary or moving obstacles.
This Dissertation tried to provide insights into the influences of individual and contextual factors on Technical and Vocational Education and Training (TVET) teachers’ learning and professional development in Ethiopia. Specifically, this research focused on identifying and determining the influences of teachers’ self perception as learners and professionals, and investigates the impact of the context, process and content of their learning and experiences on their professional development. The knowledge of these factors and their impacts help in improving the learning and professional development of the TVET teachers and their professionalization. This research tried to provide answers for the following five research questions. (1) How do TVET teachers perceive themselves as active learners and as professionals? And what are the implications of their perceptions on their learning and development? (2) How do TVET teachers engage themselves in learning and professional development activities? (3) What contextual factors facilitated or hindered the TVET Teachers’ learning and professional development? (4) Which competencies are found critical for the TVET teachers’ learning and professional development? (5) What actions need to be considered to enhance and sustain TVET teachers learning and professional development in their context? It is believed that the research results are significant not only to the TVET teachers, but also to schools leaders, TVET Teacher Training Institutions, education experts and policy makers, researchers and others stakeholders in the TVET sector. The theoretical perspectives adopted in this research are based on the systemic constructivist approach to professional development. An integrated approach to professional development requires that the teachers’ learning and development activities to be taken as an adult education based on the principles of constructivism. Professional development is considered as context - specific and long-term process in which teachers are trusted, respected and empowered as professionals. Teachers’ development activities are sought as more of collaborative activities portraying the social nature of learning. Schools that facilitate the learning and development of teachers exhibit characteristics of a learning organisation culture where, professional collaboration, collegiality and shared leadership are practiced. This research has drawn also relevant point of views from studies and reports on vocational education and TVET teacher education programs and practices at international, continental and national levels. The research objectives and the types of research questions in this study implied the use of a qualitative inductive research approach as a research strategy. Primary data were collected from TVET teachers in four schools using a one-on-one qualitative in-depth interview method. These data were analyzed using a Qualitative Content Analysis method based on the inductive category development procedure. ATLAS.ti software was used for supporting the coding and categorization process. The research findings showed that most of the TVET teachers neither perceive themselves as professionals nor as active learners. These perceptions are found to be one of the major barriers to their learning and development. Professional collaborations in the schools are minimal and teaching is sought as an isolated individual activity; a secluded task for the teacher. Self-directed learning initiatives and individual learning projects are not strongly evident. The predominantly teacher-centered approach used in TVET teacher education and professional development programs put emphasis mainly to the development of technical competences and has limited the development of a range of competences essential to teachers’ professional development. Moreover, factors such as the TVET school culture, the society’s perception of the teaching profession, economic conditions, and weak links with industries and business sectors are among the major contextual factors that hindered the TVET teachers’ learning and professional development. A number of recommendations are forwarded to improve the professional development of the TVET teachers. These include change in the TVET schools culture, a paradigm shift in TVET teacher education approach and practice, and development of educational policies that support the professionalization of TVET teachers. Areas for further theoretical research and empirical enquiry are also suggested to support the learning and professional development of the TVET teachers in Ethiopia.
The focus of this work has been to develop two families of wavelet solvers for the inner displacement boundary-value problem of elastostatics. Our methods are particularly suitable for the deformation analysis corresponding to geoscientifically relevant (regular) boundaries like sphere, ellipsoid or the actual Earth's surface. The first method, a spatial approach to wavelets on a regular (boundary) surface, is established for the classical (inner) displacement problem. Starting from the limit and jump relations of elastostatics we formulate scaling functions and wavelets within the framework of the Cauchy-Navier equation. Based on numerical integration rules a tree algorithm is constructed for fast wavelet computation. This method can be viewed as a first attempt to "short-wavelength modelling", i.e. high resolution of the fine structure of displacement fields. The second technique aims at a suitable wavelet approximation associated to Green's integral representation for the displacement boundary-value problem of elastostatics. The starting points are tensor product kernels defined on Cauchy-Navier vector fields. We come to scaling functions and a spectral approach to wavelets for the boundary-value problems of elastostatics associated to spherical boundaries. Again a tree algorithm which uses a numerical integration rule on bandlimited functions is established to reduce the computational effort. For numerical realization for both methods, multiscale deformation analysis is investigated for the geoscientifically relevant case of a spherical boundary using test examples. Finally, the applicability of our wavelet concepts is shown by considering the deformation analysis of a particular region of the Earth, viz. Nevada, using surface displacements provided by satellite observations. This represents the first step towards practical applications.
In this work the investigation of a (Ti, Al, Si) N system was done. The main point of investigation was to study the possibility of getting the nanocomposite coatings structures by deposition of multilayer films from TiN, AlSiN, . This tries to understand the relation between the mechanical properties (hardness, Young s modulus), and the microstructure (nanocrystalline with individual phases). Particularly special attention was given to the temperature effects on microstructural changes in annealing at 600 °C for the coatings. The surface hardness, elastic modulus, and the multilayers diffusion and compositions were the test tools for the comparison between the different coated samples with and without annealing at 600 °C. To achieve this object a rectangular aluminum vacuum chamber with three unbalanced sputtering magnetrons for the deposition of thin film coatings from different materials was constructed The chamber consists mainly of two chambers, the pre-vacuum chamber to load the workpiece, and the main vacuum chamber where the sputtering deposition of the thin film coatings take place. The workpiece is moving on a car travel on a railway between the two chambers to the position of the magnetrons by step motors. The chambers are divided by a self constructed rectangular gate controlled manually from outside the chamber. The chamber was sealed for vacuum use using glue and screws. Therefore, different types of glue were tested not only for its ability to develop an uniform thin layer in the gap between the aluminum plates to seal the chamber for vacuum use, but also low outgassing rates which made it suitable for vacuum use. A epoxy was able to fulfill this tasks. The evacuation characteristics of the constructed chamber was improved by minimizing the inner surface outgassing rate. Therefore, the throughput outgassing rate test method was used in the comparisons between the selected two aluminum materials (A2017 and A5353) samples short time period (one hour) outgassing rates. Different machining methods and treatments for the inner surface of the vacuum chamber were tested. The machining of the surface of material A (A2017) with ethanol as coolant fluid was able to reduce its outgassing rate a factor of 6 compared with a non-machined sample surface of the same material. The reduction of the surface porous oxide layer on the top of the aluminum surface by the pickling process with HNO3 acid, and the protection of it by producing another passive non-porous oxides layer using anodizing process will protect the surface for longer time and will minimize the outgassing rates even under humid atmosphere The residual gas analyzer (RGA) 6. Summary test shows that more than 85% of the gases inside the test chamber were water vapour (H2O) and the rests are (N2, H2, CO), so liquid nitrogen water vapor trap can enhance the chamber pumping down process. As a result it was possible to construct a chamber that can be pumped down using a turbo molecular pump (450 L/s) to the range of 1x10-6 mbar within one hour of evacuations where the chamber volume is 160 Litters and the inner surface area is 1.6 m2. This is a good base pressure for the process of sputtering deposition of hard thin film coatings. Multilayer thin film coating was deposited to demonstrate that nanostructured thin film within the (Ti, Al, Si) N system could be prepared by reactive magnetron sputtering of multi thin film layers of TiN, AlSiN. The (SNMS) spectrometry of the test samples show that a complete diffusion between the different deposited thin film coating layers in each sample takes place, even at low substrate deposition temperature. The high magnetic flux of the unbalanced magnetrons and the high sputtering power were able to produce a high ion-toatom flux, which give high mobility to the coated atoms. The interactions between the high mobility of the coated atoms and the ion-to-atom flux were sufficient to enhance the diffusion between the different deposited thin layers. It was shown from the XRD patterns for this system that the structure of the formed mixture consists of two phases. One phase is noted as TiN bulk and another detected unknown amorphous phase, which can be SiNx or AlN or a combination of Ti-Al-Si-N. As a result we where able to deposit a nanocomposite coatings by the deposition of multilayers from TiN, AlSiN thin film coatings using the constructed vacuum chamber
Learning From Networked-data: Methods and Models for Understanding Online Social Networks Dynamics
(2020)
Abstract
Nowadays, people and systems created by people are generating an unprecedented amount of
data. This data has brought us data-driven services with a variety of applications that affect
people’s behavior. One of these applications is the emergent online social networks as a method
for communicating with each other, getting and sharing information, looking for jobs, and many
other things. However, the tremendous growth of these online social networks has also led to many
new challenges that need to be addressed. In this context, the goal of this thesis is to better understand
the dynamics between the members of online social networks from two perspectives. The
first perspective is to better understand the process and the motives underlying link formation in
online social networks. We utilize external information to predict whether two members of an online
social network are friends or not. Also, we contribute a framework for assessing the strength of
friendship ties. The second perspective is to better understand the decay dynamics of online social
networks resulting from the inactivity of their members. Hence, we contribute a model, methods,
and frameworks for understanding the decay mechanics among the members, for predicting members’
inactivity, and for understanding and analyzing inactivity cascades occurring during the decay.
The results of this thesis are: (1) The link formation process is at least partly driven by interactions
among members that take place outside the social network itself; (2) external interactions might
help reduce the noise in social networks and for ranking the strength of the ties in these networks;
(3) inactivity dynamics can be modeled, predicted, and controlled using the models contributed in
this thesis, which are based on network measures. The contributions and the results of this thesis
can be beneficial in many respects. For example, improving the quality of a social network by introducing
new meaningful links and removing noisy ones help to improve the quality of the services
provided by the social network, which, e.g., enables better friend recommendations and helps to
eliminate fake accounts. Moreover, understanding the decay processes involved in the interaction
among the members of a social network can help to prolong the engagement of these members. This
is useful in designing more resilient social networks and can assist in finding influential members
whose inactivity may trigger an inactivity cascade resulting in a potential decay of a network.
Typically software engineers implement their software according to the design of the software
structure. Relations between classes and interfaces such as method-call relations and inheritance
relations are essential parts of a software structure. Accordingly, analyzing several types of
relations will benefit the static analysis process of the software structure. The tasks of this
analysis include but not limited to: understanding of (legacy) software, checking guidelines,
improving product lines, finding structure, or re-engineering of existing software. Graphs with
multi-type edges are possible representation for these relations considering them as edges, while
nodes represent classes and interfaces of software. Then, this multiple type edges graph can
be mapped to visualizations. However, the visualizations should deal with the multiplicity of
relations types and scalability, and they should enable the software engineers to recognize visual
patterns at the same time.
To advance the usage of visualizations for analyzing the static structure of software systems,
I tracked difierent development phases of the interactive multi-matrix visualization (IMMV)
showing an extended user study at the end. Visual structures were determined and classified
systematically using IMMV compared to PNLV in the extended user study as four categories:
High degree, Within-package edges, Cross-package edges, No edges. In addition to these structures
that were found in these handy tools, other structures that look interesting for software
engineers such as cycles and hierarchical structures need additional visualizations to display
them and to investigate them. Therefore, an extended approach for graph layout was presented
that improves the quality of the decomposition and the drawing of directed graphs
according to their topology based on rigorous definitions. The extension involves describing
and analyzing the algorithms for decomposition and drawing in detail giving polynomial time
complexity and space complexity. Finally, I handled visualizing graphs with multi-type edges
using small-multiples, where each tile is dedicated to one edge-type utilizing the topological
graph layout to highlight non-trivial cycles, trees, and DAGs for showing and analyzing the
static structure of software. Finally, I applied this approach to four software systems to show
its usefulness.
In this thesis, we have dealt with two modeling approaches of the credit risk, namely the structural (firm value) and the reduced form. In the former one, the firm value is modeled by a stochastic process and the first hitting time of this stochastic process to a given boundary defines the default time of the firm. In the existing literature, the stochastic process, triggering the firm value, has been generally chosen as a diffusion process. Therefore, on one hand it is possible to obtain closed form solutions for the pricing problems of credit derivatives and on the other hand the optimal capital structure of a firm can be analysed by obtaining closed form solutions of firm's corporate securities such as; equity value, debt value and total firm value, see Leland(1994). We have extended this approach by modeling the firm value as a jump-diffusion process. The choice of the jump-diffusion process was a crucial step to obtain closed form solutions for corporate securities. As a result, we have chosen a jump-diffusion process with double exponentially distributed jump heights, which enabled us to analyse the effects of jump on the optimal capital structure of a firm. In the second part of the thesis, by following the reduced form models, we have assumed that the default is triggered by the first jump of a Cox process. Further, by following Schönbucher(2005), we have modeled the forward default intensity of a firm as a geometric Brownian motion and derived pricing formulas for credit default swap options in a more general setup than the ones in Schönbucher(2005).
In der vorliegenden Arbeit wird das Tragverhalten von durchlaufenden stahlfaserbewehrten Stahlverbunddecken analysiert. Auf der Basis von experimentellen und rechnerischen Untersuchungen werden zwei Bemessungsmodelle entwickelt. Anhand der experimentellen Untersuchungen an einfeldrigen und durchlaufenden stahlfaserbewehrten Verbunddecken werden Aufschlüsse über das Trag- und Verformungsverhalten der Decken gewonnen. Dabei werden sowohl offene trapezförmige als auch hinterschnittene Profilbleche verwendet. Auf eine konventionelle Betonstahlbewehrung wird gänzlich verzichtet. Das Stützmoment wird vom Stahlfaserbeton alleine aufgenommen. In vier Versuchsserien mit insgesamt 18 Versuchen werden einzelne Parameter wie z. B. unterschiedliche Deckenstärken, unterschiedliche Profilblechgeometrien sowie unterschiedliche Stahlfaserbetonmischungen untersucht. Für die Berechnung und Bemessung werden die im Verbundbau üblichen Nachweisverfahren aufgegriffen und modifiziert. Die Traganteile des Stahlfaserbetons werden über den Ansatz von Spannungsblöcken implementiert. Bei der Nachrechnung der einzelnen Versuche zeigt sich die Eignung der Verfahren. Für die einzelnen Nachweise werden in Parameterstudien Bemessungsdiagramme und –tabellen erstellt, die dem anwendenden Ingenieur ein einfaches und sicheres Bemessen ermöglichen. Anhand der experimentellen Ergebnisse und der rechnerischen Untersuchungen werden zwei mögliche Bemessungsmodelle entwickelt, mit denen die Tragfähigkeit von stahlfaserbewehrten durchlaufenden Verbunddecken nachgewiesen werden kann. Dabei kann der Nachweis entweder nach den Verfahren Elastisch-Plastisch oder Plastisch-Plastisch erfolgen.
In 2006 Jeffrey Achter proved that the distribution of divisor class groups of degree 0 of function fields with a fixed genus and the distribution of eigenspaces in symplectic similitude groups are closely related to each other. Gunter Malle proposed that there should be a similar correspondence between the distribution of class groups of number fields and the distribution of eigenspaces in ceratin matrix groups. Motivated by these results and suggestions we study the distribution of eigenspaces corresponding to the eigenvalue one in some special subgroups of the general linear group over factor rings of rings of integers of number fields and derive some conjectural statements about the distribution of \(p\)-parts of class groups of number fields over a base field \(K_{0}\). Where our main interest lies in the case that \(K_{0}\) contains the \(p\)th roots of unity, because in this situation the \(p\)-parts of class groups seem to behave in an other way like predicted by the popular conjectures of Henri Cohen and Jacques Martinet. In 2010 based on computational data Malle has succeeded in formulating a conjecture in the spirit of Cohen and Martinet for this case. Here using our investigations about the distribution in matrixgroups we generalize the conjecture of Malle to a more abstract level and establish a theoretical backup for these statements.
Acidic zeolites like H-Y, H-ZSM-5, H-MCM-22 and H-MOR zeolites were found to be the selective adsorbents for the removal of thiophene from toluene or n-heptane as solvent. The competitive adsorption of toluene is found to influence the adsorption capacity for thiophene and is more predominant when high-alumina zeolites are used as adsorbents. This behaviour is also reflected by the results of the adsorption of thiophene on H-ZSM-5 zeolites with varied nSi/nAl ratios (viz. 13, 19 and 36) from toluene and n-heptane as solvents, respectively. UV-Vis spectroscopic results show that the oligomerization of thiophene leads to the formation of dimers and trimers on these zeolites. The oligomerization in acid zeolites is regarded to be dependent on the geometry of the pore system of the zeolites. The sulphur-containing compounds with more than one ring viz. benzothiophene, which are also present in substantial amounts in certain hydrocarbon fractions, are not adsorbed on H-ZSM-5 zeolites. This is obvious, as the diameter of the pore aperture of zeolite H-ZSM-5 is smaller than the molecular size of benzothiophene. Metal ion-exchanged FAU-type zeolites are found to be promising adsorbents for the removal of sulphur-containing compounds from model solutions. The introduction of Cu+-, Ni2+-, Ce3+-, La3+- and Y3+- ions into zeolite Na+-Y by aqueous ion-exchange substantially improves the adsorption capacity for thiophene from toluene or n-heptane as solvent. More than the absolute content of Cu+-ions, the presence of Cu+-ions at the sites exposed to supercages is believed to influence the adsorption of thiophene on Cu+-Y zeolite. It was shown experimentally for the case of Cu+-Y and Ce3+-Y that the supercages present in the FAU zeolite allow for an access of bulkier sulphur-containing compounds (viz. benzothiophene, dibenzothiophene and dimethyl dibenzothiophene). The presence of these bulkier compounds compete with thiophene and are preferentially adsorbed on Cu+-Y zeolite. IR spectroscopic results revealed that the adsorption of thiophene on Na+-Y, Cu+-Y and Ni2+-Y is primarily a result of the interaction of thiophene via pi-complexation between C=C double bond (of thiophene) and metal ions (in the zeolite framework). A different mode of interaction of thiophene with Ce3+-, La3+- and Y3+-metal ions was observed in the IR spectra of thiophene adsorbed on Ce3+-Y, La3+-Y and Y3+-Y zeolites, respectively. On these adsorbents, thiophene is believed to interact via a lone electron pair of the sulphur atom with metal ions present in the adsorbent (M-S interaction). The experimental results show that there is a large difference in the thiophene adsorption capacities of pi-complexation adsorbents (like Cu+-Y, Ni2+-Y) between the model solution with toluene as solvent and the model solution with n-heptane as solvent. The lower capacity of these zeolites for the adsorption of thiophene from toluene than from n-heptane as solvent is the clear indication of competition of toluene in interating with adsorbent in a way similar to thiophene. The difference in thiophene adsorption capacities is very low in the case of adsorbents Ce3+-Y, La3+-Y and Y3+-Y, which are believed to interact with thiophene predominantly by direct M3+-S bond (thiophene interacting with metal ion via a lone pair of electrons). TG-DTA analysis was used to study the regeneration behaviour of the adsorbents. Acid zeolites can be regenerated by simply heating at 400 °C in a flow of nitrogen whereas thiophene is chemically adsorbed on the metal ion. By contrast, it is not possible to regenerate by heating under idle inert gas flow. The only way to regenerate these adsorbents is to burn off the adsorbate, which eventually brings about an undesired emission of SOx. The exothermic peaks appeared at different temperatures in the heat flow profiles of Cu+-Y, Ce3+-Y, La3+-Y and Y3+-Y are also indicating that two different types of interaction are present as revealed by IR spectroscopy, too. One major difficulty in reducing the sulphur content in fuels to value below 10 ppm is the inability in removing alkyl dibenzothiophenes, viz. 4,6 dimethyl dibenzothiophene, by the existing catalytic hydrodesulphurization technique. Cu+-Y and Ce3+-Y were found in the present study to adsorb this compound from toluene to a certain extent. To meet the stringent regulations on sulphur content, selective adsorption by zeolites could be a valuable post-purification method after the catalytic hydrodesulphurization unit.
Highly Automated Driving (HAD) vehicles represent complex and safety critical systems. They are deployed in an open context i.e., an intricate environment which undergoes continual changes. The complexity of these systems and insufficiencies in sensing and understanding the open context may result in unsafe and uncertain behaviour. The safety critical nature of the HAD vehicles requires modelling of root causes for unsafe behaviour and their mitigation to argue sufficient reduction of residual risk.
Standardization activities such as ISO 21448 provide guidelines on the Safety Of The Intended Functionality (SOTIF) and focus on the analysis of performance limitations under the influence of triggering conditions that can lead to hazardous behaviour. SOTIF references traditional safety analyses methods e.g., Failure Mode and Effect Analysis (FMEA) and Fault Tree Analysis (FTA) to perform safety analysis. These analyses methods are based on certain assumptions e.g., single point failure in FMEA and independence of basic events in FTA. Moreover, these analyses are generally based on expert knowledge i.e., data-based models or hybrid approaches (expert and data) are seldom practised. The resulting safety model is fixed i.e., it is generally seen as a one-time artefact. Open context environment may contain triggering conditions which may not be evident to the expert. Open context also evolves over time and new phenomena may emerge.
This thesis explores the applicability of the traditional safety analyses techniques to provide safety models for HAD vehicles operating in the open context, under the light of modelling assumptions taken by traditional safety analyses techniques. Moreover, incorporating uncertainties into safety analyses models is also explored. An explicit distinction between the inherent uncertainty of a probabilistic event (aleatory) and uncertainty due to lack of knowledge (epistemic) is made to formalize models to perform SOTIF analysis. A further distinction is made for conditions of complete ignorance and termed as ontological uncertainty. The distinction is important as for HAD vehicles operating in open context the ontological uncertainty can never be completely disregarded.
This thesis proposes a novel framework of SOTIF to model, estimate and dis cover triggering conditions relevant to performance limitations. The framework provides the ability to model uncertainties while also providing a hybrid approach i.e., supporting inclusion of expert knowledge as well as data driven engineering processes. Two representative algorithms are provided to support the framework. Bayesian Network (BN) and p-value hypothesis testing are utilised in this regard. The framework is implemented on a real-world case study in which LIDARs based perception systems are used as vehicle detection system.
Dealing with information in modern times involves users to cope with hundreds of thousands of documents, such as articles, emails, Web pages, or News feeds.
Above all information sources, the World Wide Web presents information seekers with great challenges.
It offers more text in natural language than one is capable to read.
The key idea for this research intends to provide users with adaptable filtering techniques, supporting them in filtering out the specific information items they need.
Its realization focuses on developing an Information Extraction system,
which adapts to a domain of concern, by interpreting the contained formalized knowledge.
Utilizing the Resource Description Framework (RDF), which is the Semantic Web's formal language for exchanging information,
allows extending information extractors to incorporate the given domain knowledge.
Because of this, formal information items from the RDF source can be recognized in the text.
The application of RDF allows a further investigation of operations on recognized information items, such as disambiguating and rating the relevance of these.
Switching between different RDF sources allows changing the application scope of the Information Extraction system from one domain of concern to another.
An RDF-based Information Extraction system can be triggered to extract specific kinds of information entities by providing it with formal RDF queries in terms of the SPARQL query language.
Representing extracted information in RDF extends the coverage of the Semantic Web's information degree and provides a formal view on a text from the perspective of the RDF source.
In detail, this work presents the extension of existing Information Extraction approaches by incorporating the graph-based nature of RDF.
Hereby, the pre-processing of RDF sources allows extracting statistical information models dedicated to support specific information extractors.
These information extractors refine standard extraction tasks, such as the Named Entity Recognition, by using the information provided by the pre-processed models.
The post-processing of extracted information items enables representing these results in RDF format or lists, which can now be ranked or filtered by relevance.
Post-processing also comprises the enrichment of originating natural language text sources with extracted information items by using annotations in RDFa format.
The results of this research extend the state-of-the-art of the Semantic Web.
This work contributes approaches for computing customizable and adaptable RDF views on the natural language content of Web pages.
Finally, due to the formal nature of RDF, machines can interpret these views allowing developers to process the contained information in a variety of applications.
Hardware Contention-Aware Real-Time Scheduling on Multi-Core Platforms in Safety-Critical Systems
(2019)
While the computing industry has shifted from single-core to multi-core processors for performance gain, safety-critical systems (SCSs) still require solutions that enable their transition while guaranteeing safety, requiring no source-code modifications and substantially reducing re-development and re-certification costs, especially for legacy applications that are typically substantial. This dissertation considers the problem of worst-case execution time (WCET) analysis under contentions when deadline-constrained tasks in independent partitioned task set execute on a homogeneous multi-core processor with dynamic time-triggered shared memory bandwidth partitioning in SCSs.
Memory bandwidth in multi-core processors is shared across cores and is a significant cause of performance bottleneck and temporal variability of multiple-orders in task’s execution times due to contentions in memory sub-system. Further, the circular dependency is not only between WCET and CPU scheduling of others cores, but also between WCET and memory bandwidth assignments over time to cores. Thus, there is need of solutions that allow tailoring memory bandwidth assignments to workloads over time and computing safe WCET. It is pragmatically infeasible to obtain WCET estimates from static WCET analysis tools for multi-core processors due to the sheer computational complexity involved.
We use synchronized periodic memory servers on all cores that regulate each core’s maximum memory bandwidth based on allocated bandwidth over time. First, we present a workload schedulability test for known even-memory-bandwidth-assignment-to-active-cores over time, where the number of active cores represents the cores with non-zero memory bandwidth assignment. Its computational complexity is similar to merge-sort. Second, we demonstrate using a real avionics certified safety-critical application how our method’s use can preserve an existing application’s single-core CPU schedule under contentions on a multi-core processor. It enables incremental certification using composability and requires no-source code modification.
Next, we provide a general framework to perform WCET analysis under dynamic memory bandwidth partitioning when changes in memory bandwidth to cores assignment are time-triggered and known. It provides a stall maximization algorithm that has a complexity similar to a concave optimization problem and efficiently implements the WCET analysis. Last, we demonstrate dynamic memory assignments and WCET analysis using our method significantly improves schedulability compared to the stateof-the-art using an Integrated Modular Avionics scenario.
Abstract
The main theme of this thesis is about Graph Coloring Applications and Defining Sets in Graph Theory.
As in the case of block designs, finding defining sets seems to be difficult problem, and there is not a general conclusion. Hence we confine us here to some special types of graphs like bipartite graphs, complete graphs, etc.
In this work, four new concepts of defining sets are introduced:
• Defining sets for perfect (maximum) matchings
• Defining sets for independent sets
• Defining sets for edge colorings
• Defining set for maximal (maximum) clique
Furthermore, some algorithms to find and construct the defining sets are introduced. A review on some known kinds of defining sets in graph theory is also incorporated, in chapter 2 the basic definitions and some relevant notations used in this work are introduced.
chapter 3 discusses the maximum and perfect matchings and a new concept for a defining set for perfect matching.
Different kinds of graph colorings and their applications are the subject of chapter 4.
Chapter 5 deals with defining sets in graph coloring. New results are discussed along with already existing research results, an algorithm is introduced, which enables to determine a defining set of a graph coloring.
In chapter 6, cliques are discussed. An algorithm for the determination of cliques using their defining sets. Several examples are included.
Hydrogels are known to be covalently or ionic cross-linked, hydrophilic three-dimensional
polymer networks, which exist in our bodies in a biological gel form such as the vitreous
humour that fills the interior of the eyes. Poly(N-isopropylacrylamide) (poly(NIPAAm))
hydrogels are attracting more interest in biomedical applications because, besides others, they
exhibit a well-defined lower critical solution temperature (LCST) in water, around 31–34°C,
which is close to the body temperature. This is considered to be of great interest in drug
delivery, cell encapsulation, and tissue engineering applications. In this work, the
poly(NIPAAm) hydrogel is synthesized by free radical polymerization. Hydrogel properties
and the dimensional changes accompanied with the volume phase transition of the
thermosensitive poly(NIPAAm) hydrogel were investigated in terms of Raman spectra,
swelling ratio, and hydration. The thermal swelling/deswelling changes that occur at different
equilibrium temperatures and different solutions (phenol, ethanol, propanol, and sodium
chloride) based on Raman spectrum were investigated. In addition, Raman spectroscopy has
been employed to evaluate the diffusion aspects of bovine serum albumin (BSA) and phenol
through the poly(NIPAAm) network. The determination of the mutual diffusion coefficient,
\(D_{mut}\) for hydrogels/solvent system was achieved successfully using Raman spectroscopy at
different solute concentrations. Moreover, the mechanical properties of the hydrogel, which
were investigated by uniaxial compression tests, were used to characterize the hydrogel and to
determine the collective diffusion coefficient through the hydrogel. The solute release coupled
with shrinking of the hydrogel particles was modelled with a bi-dimensional diffusion model
with moving boundary conditions. The influence of the variable diffusion coefficient is
observed and leads to a better description of the kinetic curve in the case of important
deformation around the LCST. A good accordance between experimental and calculated data
was obtained.
Optical Character Recognition (OCR) system plays an important role in digitization of data acquired as images from a variety of sources. Although the area is very well explored for Latin languages, some of the languages based on Arabic cursive script are not yet explored. It is due to many factors: Most importantly are the unavailability of proper data sets and complexities posed by cursive scripts. The Pashto language is one of such languages which needs considerable exploration towards OCR. In order to develop such an OCR system, this thesis provides a pioneering study that explores deep learning for the Pashto language in the field of OCR.
The Pashto language is spoken by more than $50$ million people across the world, and it is an active medium both for oral as well as written communication. It is associated with rich literary heritage and contains huge written collection. These written materials present contents of simple to complex nature, and layouts from hand-scribed to printed text. The Pashto language presents mainly two types of complexities (i) generic w.r.t. cursive script, (ii) specific w.r.t. Pashto language. Generic complexities are cursiveness, context dependency, and breaker character anomalies, as well as space anomalies. Pashto specific complexities are variations in shape for a single character and shape similarity for some of the additional Pashto characters. Existing research in the area of Arabic OCR did not lead to an end-to-end solution for the mentioned complexities and therefore could not be generalized to build a sophisticated OCR system for Pashto.
The contribution of this thesis spans in three levels, conceptual level, data level, and practical level. In the conceptual level, we have deeply explored the Pashto language and identified those characters, which are responsible for the challenges mentioned above. In the data level, a comprehensive dataset is introduced containing real images of hand-scribed contents. The dataset is manually transcribed and has the most frequent layout patterns associated with the Pashto language. The practical level contribution provides a bridge, in the form of a complete Pashto OCR system, and connects the outcomes of the conceptual and data levels contributions. The practical contribution comprises of skew detection, text-line segmentation, feature extraction, classification, and post-processing. The OCR module is more strengthened by using deep learning paradigm to recognize Pashto cursive script by the framework of Recursive Neural Networks (RNN). Proposed Pashto text recognition is based on Long Short-Term Memory Network (LSTM) and realizes a character recognition rate of $90.78\%$ on Pashto real hand-scribed images. All these contributions are integrated into an application to provide a flexible and generic End-to-End Pashto OCR system.
The impact of this thesis is not only specific to the Pashto language, but it is also beneficial to other cursive languages like Arabic, Urdu, and Persian e.t.c. The main reason is the Pashto character set, which is a superset of Arabic, Persian, and Urdu languages. Therefore, the conceptual contribution of this thesis provides insight and proposes solutions to almost all generic complexities associated with Arabic, Persian, and Urdu languages. For example, an anomaly caused by breaker characters is deeply analyzed, which is shared among 70 languages, mainly use Arabic script. This thesis presents a solution to this issue and is equally beneficial to almost all Arabic like languages.
The scope of this thesis has two important aspects. First, a social impact, i.e., how a society may benefit from it. The main advantages are to bring the historical and almost vanished document to life and to ensure the opportunities to explore, analyze, translate, share, and understand the contents of Pashto language globally. Second, the advancement and exploration of the technical aspects. Because, this thesis empirically explores the recognition and challenges which are solely related to the Pashto language, both regarding character-set and the materials which present such complexities. Furthermore, the conceptual and practical background of this thesis regarding complexities of Pashto language is very beneficial regarding OCR for other cursive languages.
This thesis presents a novel, generic framework for information segmentation in document images.
A document image contains different types of information, for instance, text (machine printed/handwritten), graphics, signatures, and stamps.
It is necessary to segment information in documents so that to process such segmented information only when required in automatic document processing workflows.
The main contribution of this thesis is the conceptualization and implementation of an information segmentation framework that is based on part-based features.
The generic nature of the presented framework makes it applicable to a variety of documents (technical drawings, magazines, administrative, scientific, and academic documents) digitized using different methods (scanners, RGB cameras, and hyper-spectral imaging (HSI) devices).
A highlight of the presented framework is that it does not require large training sets, rather a few training samples (for instance, four pages) lead to high performance, i.e., better than previously existing methods.
In addition, the presented framework is simple and can be adapted quickly to new problem domains.
This thesis is divided into three major parts on the basis of document digitization method (scanned, hyper-spectral imaging, and camera captured) used.
In the area of scanned document images, three specific contributions have been realized.
The first of them is in the domain of signature segmentation in administrative documents.
In some workflows, it is very important to check the document authenticity before processing the actual content.
This can be done based on the available seal of authenticity, e.g., signatures.
However, signature verification systems expect pre-segmented signature image, while signatures are usually a part of document.
To use signature verification systems on document images, it is necessary to first segment signatures in documents.
This thesis shows that the presented framework can be used to segment signatures in administrative documents.
The system based on the presented framework is tested on a publicly available dataset where it outperforms the state-of-the-art methods and successfully segmented all signatures, while less than half of the found signatures are false positives.
This shows that it can be applied for practical use.
The second contribution in the area of scanned document images is segmentation of stamps in administrative documents.
A stamp also serves as a seal for documents authenticity.
However, the location of stamp on the document can be more arbitrary than a signature depending on the person sealing the document.
This thesis shows that a system based on our generic framework is able to extract stamps of any arbitrary shape and color.
The evaluation of the presented system on a publicly available dataset shows that it is also able to segment black stamps (that were not addressed in the past) with a recall and precision of 83% and 73%, respectively.
%Furthermore, to segment colored stamps, this thesis presents a novel feature set which is based on intensity gradient, is able to extract unseen, colored, arbitrary shaped, textual as well as graphical stamps, and outperforms the state-of-the-art methods.
The third contribution in the scanned document images is in the domain of information segmentation in technical drawings (architectural floorplans, maps, circuit diagrams, etc.) containing usually a large amount of graphics and comparatively less textual components. Further, as in technical drawings, text is overlapping with graphics.
Thus, automatic analysis of technical drawings uses text/graphics segmentation as a pre-processing step.
This thesis presents a method based on our generic information segmentation framework that is able to detect the text, which is touching graphical components in architectural floorplans and maps.
Evaluation of the method on a publicly available dataset of architectural floorplans shows that it is able to extract almost all touching text components with precision and recall of 71% and 95%, respectively.
This means that almost all of the touching text components are successfully extracted.
In the area of hyper-spectral document images, two contributions have been realized.
Unlike normal three channels RGB images, hyper-spectral images usually have multiple channels that range from ultraviolet to infrared regions including the visible region.
First, this thesis presents a novel automatic method for signature segmentation from hyper-spectral document images (240 spectral bands between 400 - 900 nm).
The presented method is based on a part-based key point detection technique, which does not use any structural information, but relies only on the spectral response of the document regardless of ink color and intensity.
The presented method is capable of segmenting (overlapping and non-overlapping) signatures from varying backgrounds like, printed text, tables, stamps, logos, etc.
Importantly, the presented method can extract signature pixels and not just the bounding boxes.
This is substantial when signatures are overlapping with text and/or other objects in image. Second, this thesis presents a new dataset comprising of 300 documents scanned using a high-resolution hyper-spectral scanner. Evaluation of the presented signature segmentation method on this hyper-spectral dataset shows that it is able to extract signature pixels with the precision and recall of 100% and 79%, respectively.
Further contributions have been made in the area of camera captured document images. A major problem in the development of Optical Character Recognition (OCR) systems for camera captured document images is the lack of labeled camera captured document images datasets. In the first place, this thesis presents a novel, generic, method for automatic ground truth generation/labeling of document images. The presented method builds large-scale (i.e., millions of images) datasets of labeled camera captured / scanned documents without any human intervention. The method is generic and can be used for automatic ground truth generation of (scanned and/or camera captured) documents in any language, e.g., English, Russian, Arabic, Urdu. The evaluation of the presented method, on two different datasets in English and Russian, shows that 99.98% of the images are correctly labeled in every case.
Another important contribution in the area of camera captured document images is the compilation of a large dataset comprising 1 million word images (10 million character images), captured in a real camera-based acquisition environment, along with the word and character level ground truth. The dataset can be used for training as well as testing of character recognition systems for camera-captured documents. Various benchmark tests are performed to analyze the behavior of different open source OCR systems on camera captured document images. Evaluation results show that the existing OCRs, which already get very high accuracies on scanned documents, fail on camera captured document images.
Using the presented camera-captured dataset, a novel character recognition system is developed which is based on a variant of recurrent neural networks, i.e., Long Short Term Memory (LSTM) that outperforms all of the existing OCR engines on camera captured document images with an accuracy of more than 95%.
Finally, this thesis provides details on various tasks that have been performed in the area closely related to information segmentation. This includes automatic analysis and sketch based retrieval of architectural floor plan images, a novel scheme for online signature verification, and a part-based approach for signature verification. With these contributions, it has been shown that part-based methods can be successfully applied to document image analysis.
Entwicklung von Fermentationsstrategien zur stofflichen Nutzung von nachwachsenden Rohstoffen
(2022)
Biertreber stellt einen wichtigen Vertreter eines nachwachsenden Rohstoffes dar, da es sich dabei um ein niedrigpreisiges Nebenprodukt des Brauprozesses handelt, welches jedes Jahr in großen Mengen anfällt. In der vorliegenden Arbeit wurde Biertreber aus sieben verschiedenen Braurezepten, sowohl aus eigener Herstellung als auch industriellen Ursprungs, analysiert und in Bezug auf die zugrundeliegenden Braugänge klassifiziert. Darüber hinaus wurde der Treber durch Pressen in zwei separate Stoffströme aufgeteilt: eine flüssige und eine feste Fraktion. Für beide Fraktionen wurden Bioprozesse etabliert, um einerseits das flüssige Substrat (Treberpresssaft) mit einem Milchsäurebakterium (Lactobacillus delbrueckii subsp. lactis) zu Milchsäure und andererseits das feste Substrat (Treberrückstand) mit einem lignocellulolytischen und gemischtsäuregärung-betreibenden Stamm (Cellulomonas uda) zu Ethanol und Essigsäure umzusetzen. Außerdem wurde ein kinetisches Modell aufgestellt, welches u.a. die Milchsäurebildung und das Zellwachstum von L. delbrueckii subsp. lactis für drei Treberpresssäfte unterschiedlicher Braurezepturen, d.h. mit unterschiedlicher Nährstoffausstattung, in einer simultanen Verzuckerung und Fermentation vorhersagen konnte. Des Weiteren konnten die entwickelten Fermentationsstrategien zur Verwertung des Treberpresssaftes und Treberrückstandes sowie die zugrundeliegenden Prozessüberwachungs- und Regelungsstrategien auf Fermentationen mit den gleichen Organismen aber dem Substrat Wiesenschnitt – also einen weiteren nachwachsenden Rohstoff – übertragen werden.