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In this thesis, we focus on the application of the Heath-Platen (HP) estimator in option
pricing. In particular, we extend the approach of the HP estimator for pricing path dependent
options under the Heston model. The theoretical background of the estimator
was first introduced by Heath and Platen [32]. The HP estimator was originally interpreted
as a control variate technique and an application for European vanilla options was
presented in [32]. For European vanilla options, the HP estimator provided a considerable
amount of variance reduction. Thus, applying the technique for path dependent options
under the Heston model is the main contribution of this thesis.
The first part of the thesis deals with the implementation of the HP estimator for pricing
one-sided knockout barrier options. The main difficulty for the implementation of the HP
estimator is located in the determination of the first hitting time of the barrier. To test the
efficiency of the HP estimator we conduct numerical tests with regard to various aspects.
We provide a comparison among the crude Monte Carlo estimation, the crude control
variate technique and the HP estimator for all types of barrier options. Furthermore, we
present the numerical results for at the money, in the money and out of the money barrier
options. As numerical results imply, the HP estimator performs superior among others
for pricing one-sided knockout barrier options under the Heston model.
Another contribution of this thesis is the application of the HP estimator in pricing bond
options under the Cox-Ingersoll-Ross (CIR) model and the Fong-Vasicek (FV) model. As
suggested in the original paper of Heath and Platen [32], the HP estimator has a wide
range of applicability for derivative pricing. Therefore, transferring the structure of the
HP estimator for pricing bond options is a promising contribution. As the approximating
Vasicek process does not seem to be as good as the deterministic volatility process in the
Heston setting, the performance of the HP estimator in the CIR model is only relatively
good. However, for the FV model the variance reduction provided by the HP estimator is
again considerable.
Finally, the numerical result concerning the weak convergence rate of the HP estimator
for pricing European vanilla options in the Heston model is presented. As supported by
numerical analysis, the HP estimator has weak convergence of order almost 1.
A popular model for the locations of fibres or grains in composite materials
is the inhomogeneous Poisson process in dimension 3. Its local intensity function
may be estimated non-parametrically by local smoothing, e.g. by kernel
estimates. They crucially depend on the choice of bandwidths as tuning parameters
controlling the smoothness of the resulting function estimate. In this
thesis, we propose a fast algorithm for learning suitable global and local bandwidths
from the data. It is well-known, that intensity estimation is closely
related to probability density estimation. As a by-product of our study, we
show that the difference is asymptotically negligible regarding the choice of
good bandwidths, and, hence, we focus on density estimation.
There are quite a number of data-driven bandwidth selection methods for
kernel density estimates. cross-validation is a popular one and frequently proposed
to estimate the optimal bandwidth. However, if the sample size is very
large, it becomes computational expensive. In material science, in particular,
it is very common to have several thousand up to several million points.
Another type of bandwidth selection is a solve-the-equation plug-in approach
which involves replacing the unknown quantities in the asymptotically optimal
bandwidth formula by their estimates.
In this thesis, we develop such an iterative fast plug-in algorithm for estimating
the optimal global and local bandwidth for density and intensity estimation with a focus on 2- and 3-dimensional data. It is based on a detailed
asymptotics of the estimators of the intensity function and of its second
derivatives and integrals of second derivatives which appear in the formulae
for asymptotically optimal bandwidths. These asymptotics are utilised to determine
the exact number of iteration steps and some tuning parameters. For
both global and local case, fewer than 10 iterations suffice. Simulation studies
show that the estimated intensity by local bandwidth can better indicate
the variation of local intensity than that by global bandwidth. Finally, the
algorithm is applied to two real data sets from test bodies of fibre-reinforced
high-performance concrete, clearly showing some inhomogeneity of the fibre
intensity.
The research problem is that the land-use (re-)planning process in the existing Egyptian cities
does not attain sustainability. This is because of the unfulfillment of essential principles within
their land-use structures, lack of harmony between the added and old parts in the cities, and
other reasons. This leads to the need for developing an assessment system, which is a
computational spatial planning support system-SPSS. This SPSS is used for identifying the
degree of sustainability attainment in land-uses plans, predicting probable problems, and
suggesting modifications in the evaluated plans.
The main goal is to design the SPSS for supporting sustainability in the Egyptian cities. The
secondary goals are: studying the Egyptian planning and administrative systems for designing
the technical and administrative frameworks for the SPSS, the development of an assessment
model from the SPSS for assessing sustainability in land-use structures of urban areas, as well
as the identification of the improvements required in the model and the recommendations for
developing the SPSS.
The theoretical part aims to design each of the administrative and technical frameworks of the
SPSS. This requires studying each of the main planning approaches, the sustainability in urban
land-use planning, and the significance of using efficient assessment tools for evaluating the
sustainability in this process. The added value of the planning support systems-PSSs for
planning and their role in supporting sustainability attainment in urban land-use planning are
discussed. Then, a group of previous examples in the sustainability assessment from various
countries (developed and developing countries) are selected, which have used various
assessment tools. This is to extract some learned lessons to be guides for the SPSS. And so,
the comprehensive technical framework for the SPSS is designed, which includes the suggested
methods and techniques that perform various stages of the assessment process.
The Egyptian context is studied regarding the planning and administration systems within the
Egyptian cities, as well as the spatial and administrative problems facing the sustainable
development. And so, the administrative framework for the SPSS is identified, which includes
the entities that should be involved in the assessment process.
The empirical part focuses on the design of a selected assessment model from the
comprehensive technical framework of the SPSS to be established as a minimized version from
it. This model is programmed in the form of a new toolbox within the ArcGIS™ software through
geoscripting using Python programming language to be applied for assessing the sustainability
attainment in the land-use structure of urban areas. The required assessing criteria for the model
specialized for the Egyptian and German cities are identified, for applying it on German and
Egyptian study areas.
The conclusions regarding each of PSSs, the Egyptian local administration and planning
systems, sustainability attainment in the land-use planning process in Egyptian Cities, as well as
the proposed SPSS and the developed toolbox are drawn. The recommendations are regarding
each of challenges facing the development and application of PSSs, the Egyptian local
administration and planning systems, the spatial problems in Egyptian cities, the establishment
of the SPSS, and the application of the toolbox. The future agenda is in the fields of sustainable urban land-use planning, planning support science, and the development process in the
Egyptian cities.
Due to the steadily growing flood of data, the appropriate use of visualizations for efficient data analysis is as important today as it has never been before. In many application domains, the data flood is based on processes that can be represented by node-link diagrams. Within such a diagram, nodes may represent intermediate results (or products), system states (or snapshots), milestones or real (and possibly georeferenced) objects, while links (edges) can embody transition conditions, transformation processes or real physical connections. Inspired by the engineering sciences application domain and the research project “SinOptiKom: Cross-sectoral optimization of transformation processes in municipal infrastructures in rural areas”, a platform for the analysis of transformation processes has been researched and developed based on a geographic information system (GIS). Caused by the increased amount of available and interesting data, a particular challenge is the simultaneous visualization of several visible attributes within one single diagram instead of using multiple ones. Therefore, two approaches have been developed, which utilize the available space between nodes in a diagram to display additional information.
Motivated by the necessity of appropriate result communication with various stakeholders, a concept for a universal, dashboard-based analysis platform has been developed. This web-based approach is conceptually capable of displaying data from various data sources and has been supplemented by collaboration possibilities such as sharing, annotating and presenting features.
In order to demonstrate the applicability and usability of newly developed applications, visualizations or user interfaces, extensive evaluations with human users are often inevitable. To reduce the complexity and the effort for conducting an evaluation, the browser-based evaluation framework (BREF) has been designed and implemented. Through its universal and flexible character, virtually any visualization or interaction running in the browser can be evaluated with BREF without any additional application (except for a modern web browser) on the target device. BREF has already proved itself in a wide range of application areas during the development and has since grown into a comprehensive evaluation tool.
Collaboration aims to increase the efficiency of problem solving and decision making by bringing diverse areas of expertise together, i.e., teams of experts from various disciplines, all necessary to come up with acceptable concepts. This dissertation is concerned with the design of highly efficient computer-supported collaborative work involving active participation of user groups with diverse expertise. Three main contributions can be highlighted: (1) the definition and design of a framework facilitating collaborative decision making; (2) the deployment and evaluation of more natural and intuitive interaction and visualization techniques in order to support multiple decision makers in virtual reality environments; and (3) the integration of novel techniques into a single proof-of-concept system.
Decision making processes are time-consuming, typically involving several iterations of different options before a generally acceptable solution is obtained. Although, collaboration is an often-applied method, the execution of collaborative sessions is often inefficient, does not involve all participants, and decisions are often finalized with- out the agreement of all participants. An increasing number of computer-supported cooperative work systems (CSCW) facilitate collaborative work by providing shared viewpoints and tools to solve joint tasks. However, most of these software systems are designed from a feature-oriented perspective, rather than a human-centered perspective and without the consideration of user groups with diverse experience and joint goals instead of joint tasks. The aim of this dissertation is to bring insights to the following research question: How can computer-supported cooperative work be designed to be more efficient? This question opens up more specific questions like: How can collaborative work be designed to be more efficient? How can all participants be involved in the collaboration process? And how can interaction interfaces that support collaborative work be designed to be more efficient? As such, this dissertation makes contributions in:
1. Definition and design of a framework facilitating decision making and collaborative work. Based on examinations of collaborative work and decision making processes requirements of a collaboration framework are assorted and formulated. Following, an approach to define and rate software/frameworks is introduced. This approach is used to translate the assorted requirements into a software’s architecture design. Next, an approach to evaluate alternatives based on Multi Criteria Decision Making (MCDM) and Multi Attribute Utility Theory (MAUT) is presented. Two case studies demonstrate the usability of this approach for (1) benchmarking between systems and evaluates the value of the desired collaboration framework, and (2) ranking a set of alternatives resulting from a decision-making process incorporating the points of view of multiple stake- holders.
2. Deployment and evaluation of natural and intuitive interaction and visualization techniques in order to support multiple diverse decision makers. A user taxonomy of industrial corporations serves to create a petri network of users in order to identify dependencies and information flows between each other. An explicit characterization and design of task models was developed to define interfaces and further components of the collaboration framework. In order to involve and support user groups with diverse experiences, smart de- vices and virtual reality are used within the presented collaboration framework. Natural and intuitive interaction techniques as well as advanced visualizations of user centered views of the collaboratively processed data are developed in order to support and increase the efficiency of decision making processes. The smartwatch as one of the latest technologies of smart devices, offers new possibilities of interaction techniques. A multi-modal interaction interface is provided, realized with smartwatch and smartphone in full immersive environments, including touch-input, in-air gestures, and speech.
3. Integration of novel techniques into a single proof-of-concept system. Finally, all findings and designed components are combined into the new collaboration framework called IN2CO, for distributed or co-located participants to efficiently collaborate using diverse mobile devices. In a prototypical implementation, all described components are integrated and evaluated. Examples where next-generation network-enabled collaborative environments, connected by visual and mobile interaction devices, can have significant impact are: design and simulation of automobiles and aircrafts; urban planning and simulation of urban infrastructure; or the design of complex and large buildings, including efficiency- and cost-optimized manufacturing buildings as task in factory planning. To demonstrate the functionality and usability of the framework, case studies referring to factory planning are demonstrated. Considering that factory planning is a process that involves the interaction of multiple aspects as well as the participation of experts from different domains (i.e., mechanical engineering, electrical engineering, computer engineering, ergonomics, material science, and even more), this application is suitable to demonstrate the utilization and usability of the collaboration framework. The various software modules and the integrated system resulting from the research will all be subjected to evaluations. Thus, collaborative decision making for co-located and distributed participants is enhanced by the use of natural and intuitive multi-modal interaction interfaces and techniques.
Benzene is a natural constituent of crude oil and a product of incomplete combustion of petrol
and has been classified as “carcinogenic to humans” by IARC in 1982 (IARC 1982). (E,E)-
Muconaldehyde has been postulated to be a microsomal metabolite of benzene in vitro
(Latriano et al. 1986). (E,E)-Muconaldehyde is hematotoxic in vivo and its role in the
hematotoxicity of benzene is unclear (Witz et al. 1985).
We intended to ascertain the presence of (E,E)-muconaldehyde in vivo by detection of a
protein conjugate deriving from (E,E)-muconaldehyde.
Therefore we improved the current synthetic access to (E,E)-muconaldehyde. (E,E)-
muconaldehyde was synthesized in three steps starting from with (E,E)-muconic acid in an
overall yield of 60 %.
Reaction of (E,E)-muconaldehyde with bovine serum albumin resulted in formation of a
conjugate which was converted upon addition of NaBH4 to a new species whose HPLC-
retention time, UV spectra, Q1 mass and MS2 spectra matched those of the crude reaction
product from one pot conversion of Ac-Lys-OMe with (E,E)-muconaldehyde in the presence
of NaBH4 and subsequent cleavage of protection groups.
Synthetic access to the presumed structure (S)-2-ammonio-6-(((E,E)-6-oxohexa-2,4-dien-1-
yl)amino)hexanoate (Lys(MUC-CHO)) was provided in eleven steps starting from (E,E)-
muconic acid and Lys(Z)-OtBu*HCl in 2 % overall yield. Additionally synthetic access to
(S)-2-ammonio-6-(((E,E)-6-hydroxyhexa-2,4-dien-1-yl)amino)hexanoate (Lys(MUC-OH))
and (S)-2-ammonio-6-((6-hydroxyhexyl)amino)hexanoate (IS) was provided.
With synthetic reference material at hand, the presumed structure Lys(MUC-OH) could be
identified from incubations of (E,E)-muconaldehyde with bovine serum albumin via HPLC-ESI+-
MS/MS.
Cytotoxicity analysis of (E,E)-muconaldehyde and Lys(MUC-CHO) in human promyelocytic
NB4 cells resulted in EC50 ≈ 1 μM for (E,E)-muconaldehyde. Lys(MUC-CHO) did not show
any additional cytotoxicity up to 10 μM.
B6C3F1 mice were exposed to 0, 400 and 800 mg/kg b.w. benzene to examine the formation
of Lys(MUC-OH) in vivo. After 24 h mice were sacrificed and serum albumin was isolated.
Analysis for Lys(MUC-OH) has not been performed in this work.
In this thesis, we deal with the finite group of Lie type \(F_4(2^n)\). The aim is to find information on the \(l\)-decomposition numbers of \(F_4(2^n)\) on unipotent blocks for \(l\neq2\) and \(n\in \mathbb{N}\) arbitrary and on the irreducible characters of the Sylow \(2\)-subgroup of \(F_4(2^n)\).
S. M. Goodwin, T. Le, K. Magaard and A. Paolini have found a parametrization of the irreducible characters of the unipotent subgroup \(U\) of \(F_4(q)\), a Sylow \(2\)-subgroup of \(F_4(q)\), of \(F_4(p^n)\), \(p\) a prime, for the case \(p\neq2\).
We managed to adapt their methods for the parametrization of the irreducible characters of the Sylow \(2\)-subgroup for the case \(p=2\) for the group \(F_4(q)\), \(q=p^n\). This gives a nearly complete parametrization of the irreducible characters of the unipotent subgroup \(U\) of \(F_4(q)\), namely of all irreducible characters of \(U\) arising from so-called abelian cores.
The general strategy we have applied to obtain information about the \(l\)-decomposition numbers on unipotent blocks is to induce characters of the unipotent subgroup \(U\) of \(F_4(q)\) and Harish-Chandra induce projective characters of proper Levi subgroups of \(F_4(q)\) to obtain projective characters of \(F_4(q)\). Via Brauer reciprocity, the multiplicities of the ordinary irreducible unipotent characters in these projective characters give us information on the \(l\)-decomposition numbers of the unipotent characters of \(F_4(q)\).
Sadly, the projective characters of \(F_4(q)\) we obtained were not sufficient to give the shape of the entire decomposition matrix.
Crowd condition monitoring concerns the crowd safety and concerns business performance metrics. The research problem to be solved is a crowd condition estimation approach to enable and support the supervision of mass events by first-responders and marketing experts, but is also targeted towards supporting social scientists, journalists, historians, public relations experts, community leaders, and political researchers. Real-time insights of the crowd condition is desired for quick reactions and historic crowd conditions measurements are desired for profound post-event crowd condition analysis.
This thesis aims to provide a systematic understanding of different approaches for crowd condition estimation by relying on 2.4 GHz signals and its variation in crowds of people, proposes and categorizes possible sensing approaches, applies supervised machine learning algorithms, and demonstrates experimental evaluation results. I categorize four sensing approaches. Firstly, stationary sensors which are sensing crowd centric signals sources. Secondly, stationary sensors which are sensing other stationary signals sources (either opportunistic or special purpose signal sources). Thirdly, a few volunteers within the crowd equipped with sensors which are sensing other surrounding crowd centric device signals (either individually, in a single group or collaboratively) within a small region. Fourthly, a small subset of participants within the crowd equipped with sensors and roaming throughout a whole city to sense wireless crowd centric signals.
I present and evaluate an approach with meshed stationary sensors which were sensing crowd centric devices. This was demonstrated and empirically evaluated within an industrial project during three of the world-wide largest automotive exhibitions. With over 30 meshed stationary sensors in an optimized setup across 6400m2 I achieved a mean absolute error of the crowd density of just 0.0115
people per square meter which equals to an average of below 6% mean relative error from the ground truth. I validate the contextual crowd condition anomaly detection method during the visit of chancellor Mrs. Merkel and during a large press conference during the exhibition. I present the approach of opportunistically sensing stationary based wireless signal variations and validate this during the Hannover CeBIT exhibition with 80 opportunistic sources with a crowd condition estimation relative error of below 12% relying only on surrounding signals in influenced by humans. Pursuing this approach I present an approach with dedicated signal sources and sensors to estimate the condition of shared office environments. I demonstrate methods being viable to even detect low density static crowds, such as people sitting at their desks, and evaluate this on an eight person office scenario. I present the approach of mobile crowd density estimation by a group of sensors detecting other crowd centric devices in the proximity with a classification accuracy of the crowd density of 66 % (improvement of over 22% over a individual sensor) during the crowded Oktoberfest event. I propose a collaborative mobile sensing approach which makes the system more robust against variations that may result from the background of the people rather than the crowd condition with differential features taking information about the link structure between actively scanning devices, the ratio between values observed by different devices, ratio of discovered crowd devices over time, team-wise diversity of discovered devices, number of semi- continuous device visibility periods, and device visibility durations into account. I validate the approach on multiple experiments including the Kaiserslautern European soccer championship public viewing event and evaluated the collaborative mobile sensing approach with a crowd condition estimation accuracy of 77 % while outperforming previous methods by 21%. I present the feasibility of deploying the wireless crowd condition sensing approach to a citywide scale during an event in Zurich with 971 actively sensing participants and outperformed the reference method by 24% in average.
1,3-Diynes are frequently found as an important structural motif in natural products, pharmaceuticals and bioactive compounds, electronic and optical materials and supramolecular molecules. Copper and palladium complexes are widely used to prepare 1,3-diynes by homocoupling of terminal alkynes; albeit the potential of nickel complexes towards the same is essentially unexplored. Although a detailed study on the reported nickel-acetylene chemistry has not been carried out, a generalized mechanism featuring a nickel(II)/nickel(0) catalytic cycle has been proposed. In the present work, a detailed mechanistic aspect of the nickel-mediated homocoupling reaction of terminal alkynes is investigated through the isolation and/or characterization of key intermediates from both the stoichiometric and the catalytic reactions. A nickel(II) complex [Ni(L-N4Me2)(MeCN)2](ClO4)2 (1) containing a tetradentate N,N′-dimethyl-2,11-diaza[3.3](2,6)pyridinophane (L-N4Me2) as ligand was used as catalyst for homocoupling of terminal alkynes by employing oxygen as oxidant at room temperature. A series of dinuclear nickel(I) complexes bridged by a 1,3-diyne ligand have been isolated from stoichiometric reaction between [Ni(L-N4Me2)(MeCN)2](ClO4)2 (1) and lithium acetylides. The dinuclear nickel(I)-diyne complexes [{Ni(L-N4Me2)}2(RC4R)](ClO4)2 (2) were well characterized by X-ray crystal structures, various spectroscopic methods, SQUID and DFT calculation. The complexes not only represent as a key intermediate in aforesaid catalytic reaction, but also describe the first structurally characterized dinuclear nickel(I)-diyne complexes. In addition, radical trapping and low temperature UV-Vis-NIR experiments in the formation of the dinuclear nickel(I)-diyne confirm that the reactions occurring during the reduction of nickel(II) to nickel(I) and C-C bond formation of 1,3-diyne follow non-radical concerted mechanism. Furthermore, spectroscopic investigation on the reactivity of the dinuclear nickel(I)-diyne complex towards molecular oxygen confirmed the formation of a mononuclear nickel(I)-diyne species [Ni(L-N4Me2)(RC4R)]+ (4) and a mononuclear nickel(III)-peroxo species [Ni(L-N4Me2)(O2)]+ (5) which were converted to free 1,3-diyne and an unstable dinuclear nickel(II) species [{Ni(L-N4Me2)}2(O2)]2+ (6). A mononuclear nickel(I)-alkyne complex [Ni(L-N4Me2)(PhC2Ph)](ClO4).MeOH (3) and the mononuclear nickel(III)-peroxo species [Ni(L-N4Me2)(O2)]+ (5) were isolated/generated and characterized to confirm the formulation of aforementioned mononuclear nickel(I)-diyne and mononuclear nickel(III)-peroxo species. Spectroscopic experiments on the catalytic reaction mixture also confirm the presence of aforesaid intermediates. Results of both stoichiometric and catalytic reactions suggested an intriguing mechanism involving nickel(II)/nickel(I)/nickel(III) oxidation states in contrast to the reported nickel(II)/nickel(0) catalytic cycle. These findings are expected to open a new paradigm towards nickel-catalyzed organic transformations.
The screening of metagenomic datasets led to the identification of new phage-derived members of the heme oxygenase and the ferredoxin-dependent bilin reductase enzyme families.
The novel bilin biosynthesis genes were shown to form mini-cassettes on metagenomic scaffolds and further form distinct clusters in phylogenetic analyses (Ledermann et al., 2016). In this project, it was demonstrated that the discovered sequences actually encode for active enzymes. The biochemical characterization of a member of the heme oxygenases (ΦHemO) revealed that it possesses a regiospecificity for the α-methine bridge in the cleavage of the heme macrocycle. The reaction product biliverdin IXα was shown to function as the substrate for the novel ferredoxin-dependent bilin reductases (PcyX reductases), which catalyze its reduction to PEB via the intermediate 15,16-DHBV. While it was demonstrated that ΦPcyX, a phage-derived member of the PcyX reductases, is an active enzyme, it also became clear that the rate of the reaction is highly dependent on the employed redox partner. It turned out that the ferredoxin from the cyanophage P-SSM2 is to date the most suitable redox partner for the reductases of the PcyX group. Furthermore, the solution of the ΦPcyX crystal structure revealed that it adopts an α/β/α-sandwich fold, typical for the FDBR-family. Activity assays and subsequent HPLC analyses with different variants of the ΦPcyX protein demonstrated that, despite their similarity, PcyX and PcyA reductases must act via different reaction mechanisms.
Another part of this project focused on the biochemical characterization of the FDBR KflaHY2 from the streptophyte alga Klebsormidium flaccidum. Experiments with recombinant KflaHY2 showed that it is an active FDBR which produces 3(Z)-PCB as the main reaction product, like it can be found in reductases of the PcyA group. Moreover, it was shown that under the employed assay conditions the reaction of BV to PCB proceeds in two different ways: Both 3(Z)-PΦB and 18¹,18²-DHBV occur as intermediates. Activity assays with the purified intermediates yielded PCB. Hence, both compounds are suitable substrates for KflaHY2.
The results of this work highlight the importance of the biochemical experiments, as catalytic activity cannot solely be predicted by sequence analysis.
The N-containing heterocycles have received strong attention from the organic synthesis field because of their importance for pharmaceutical and material sciences. Nitrogen element plays an important role between inorganic salts and biomolecules, to search convenient methods combine C-N bond together become a hot topic in recent decades.
Since the early beginning of 20th century, transition-metal-catalyzed coupling reactions had been well-known and world widely spread in organic researchs, achieved abundant significant progress. In the other side, the less toxic and more challenging transition metal free coupling method remained further potential value.
With the evolution of amination reactions and oxidants, more and more effective, simplified, and atom economic organic synthesis methods will come soon. And these stories also drove me to think about investigating the novel cross-dehydrogenative-coupling amination methods development as the topics of my PhD research.
Thus, we selected the phenothiazine derivatives as the N-nucleophile reagents and the phenols as the C-nucleophile reagents. To achieve the transition metal-free CDC aminations of phenols with phenothiazines, we scanned the chemical toolbox and tested a series of both common and uncommon oxidants.
Firstly, we start the condition in the presence of cumene and O2. The proposed mechanism initiated by a Hock process, which would form in situ peroxo-species as initiator of the reaction. And the initial infra-red analysis predicted there is a strong O-H..N interaction.
In the second method, a series of iodines with different valance have been tested to achieve the C-N bond formation of phenols with phenothiazines. This time, a simplified and more efficient method had been developed, which also provides a wider scope of phenols. Several controlling experiments had been conducted for the plausible pathway research. Large-scale synthesis of target molecular was also successfully performed.
And then, we focus the research on the cross-coupling reaction of pre-oxidized(iminated) phenothiazine with ubiquitous phenols and indoles. In this task, we first regio-selectively synthesized the novel iminated phenothiazine derivatives with the traditional biocide and mild disinfectant, Chloramine T. Then the phenothiazinimine performed an ultra-simple condensation technique with phenol or indole coupling partners in a simplified condition. Parallel reactions were also performed to investigate the plausible pathway.
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.
In this thesis we integrate discrete dividends into the stock model, estimate
future outstanding dividend payments and solve different portfolio optimization
problems. Therefore, we discuss three well-known stock models, including
discrete dividend payments and evolve a model, which also takes early
announcement into account.
In order to estimate the future outstanding dividend payments, we develop a
general estimation framework. First, we investigate a model-free, no-arbitrage
methodology, which is based on the put-call parity for European options. Our
approach integrates all available option market data and simultaneously calculates
the market-implied discount curve. We illustrate our method using stocks
of European blue-chip companies and show within a statistical assessment that
the estimate performs well in practice.
As American options are more common, we additionally develop a methodology,
which is based on market prices of American at-the-money options.
This method relies on a linear combination of no-arbitrage bounds of the dividends,
where the corresponding optimal weight is determined via a historical
least squares estimation using realized dividends. We demonstrate our method
using all Dow Jones Industrial Average constituents and provide a robustness
check with respect to the used discount factor. Furthermore, we backtest our
results against the method using European options and against a so called
simple estimate.
In the last part of the thesis we solve the terminal wealth portfolio optimization
problem for a dividend paying stock. In the case of the logarithmic utility
function, we show that the optimal strategy is not a constant anymore but
connected to the Merton strategy. Additionally, we solve a special optimal
consumption problem, where the investor is only allowed to consume dividends.
We show that this problem can be reduced to the before solved terminal wealth
problem.
A fast numerical method for an advanced electro-chemo-mechanical model is developed which is able to capture phase separation processes in porous materials. This method is applied to simulate lithium-ion battery cells, where the complex microstructure of the electrodes is fully resolved. The intercalation of ions into the popular cathode material LFP leads to a separation into lithium-rich and lithium-poor phases. The large concentration gradients result in high mechanical stresses. A phase-field method applying the Cahn-Hilliard equation is used to describe the diffusion. For the sake of simplicity, the linear elastic case is considered. Numerical tests for fully resolved three-dimensional granular microstructures are discussed in detail.
Asynchronous concurrency is a wide-spread way of writing programs that
deal with many short tasks. It is the programming model behind
event-driven concurrency, as exemplified by GUI applications, where the
tasks correspond to event handlers, web applications based around
JavaScript, the implementation of web browsers, but also of server-side
software or operating systems.
This model is widely used because it provides the performance benefits of
concurrency together with easier programming than multi-threading. While
there is ample work on how to implement asynchronous programs, and
significant work on testing and model checking, little research has been
done on handling asynchronous programs that involve heap manipulation, nor
on how to automatically optimize code for asynchronous concurrency.
This thesis addresses the question of how we can reason about asynchronous
programs while considering the heap, and how to use this this to optimize
programs. The work is organized along the main questions: (i) How can we
reason about asynchronous programs, without ignoring the heap? (ii) How
can we use such reasoning techniques to optimize programs involving
asynchronous behavior? (iii) How can we transfer these reasoning and
optimization techniques to other settings?
The unifying idea behind all the results in the thesis is the use of an
appropriate model encompassing global state and a promise-based model of
asynchronous concurrency. For the first question, We start from refinement
type systems for sequential programs and extend them to perform precise
resource-based reasoning in terms of heap contents, known outstanding
tasks and promises. This extended type system is known as Asynchronous
Liquid Separation Types, or ALST for short. We implement ALST in for OCaml
programs using the Lwt library.
For the second question, we consider a family of possible program
optimizations, described by a set of rewriting rules, the DWFM rules. The
rewriting rules are type-driven: We only guarantee soundness for programs
that are well-typed under ALST. We give a soundness proof based on a
semantic interpretation of ALST that allows us to show behavior inclusion
of pairs of programs.
For the third question, we address an optimization problem from industrial
practice: Normally, JavaScript files that are referenced in an HTML file
are be loaded synchronously, i.e., when a script tag is encountered, the
browser must suspend parsing, then load and execute the script, and only
after will it continue parsing HTML. But in practice, there are numerous
JavaScript files for which asynchronous loading would be perfectly sound.
First, we sketch a hypothetical optimization using the DWFM rules and a
static analysis.
To actually implement the analysis, we modify the approach to use a
dynamic analysis. This analysis, known as JSDefer, enables us to analyze
real-world web pages, and provide experimental evidence for the efficiency
of this transformation.
The complexity of modern real-time systems is increasing day by day. This inevitable rise in complexity predominantly stems from two contradicting requirements, i.e., ever increasing demand for functionality, and required low cost for the final product. The development of modern multi-processors and variety of network protocols and architectures have enabled such a leap in complexity and functionality possible. Albeit, efficient use of these multi-processors and network architectures is still a major problem. Moreover, the software design and its development process needs improvements in order to support rapid-prototyping for ever changing system designs. Therefore, in this dissertation, we provide solutions for different problems faced in the development and deployment process of real-time systems. The contributions presented in this thesis enable efficient utilization of system resources, rapid design & development and component modularity & portability.
In order to ease the certification process, time-triggered computation model is often used in distributed systems. However, time-triggered scheduling is NP-hard, due to which the process of schedule generation for complex large systems becomes convoluted. Large scheduler run-times and low scalability are two major problems with time-triggered scheduling. To solve these problems, we present a modular real-time scheduler based on a novel search-tree pruning technique, which consumes less time (compared to the state-of-the-art) in order to schedule tasks on large distributed time-triggered systems. In order to provide end-to-end guarantees, we also extend our modular scheduler to quickly generate schedules for time-triggered network traffic in large TTEthernet based networks. We evaluate our schedulers on synthetic but practical task-sets and demonstrate that our pruning technique efficiently reduces scheduler run-times and exhibits adequate scalability for future time-triggered distributed systems.
In safety critical systems, the certification process also requires strict isolation between independent components. This isolation is enforced by utilizing resource partitioning approach, where different criticality components execute in different partitions (each temporally and spatially isolated from each other). However, existing partitioning approaches use periodic servers or tasks to service aperiodic activities. This approach leads to utilization loss and potentially leads to large latencies. On the contrary to the periodic approaches, state-of-the-art aperiodic task admission algorithms do not suffer from problems like utilization loss. However, these approaches do not support partitioned scheduling or mixed-criticality execution environment. To solve this problem, we propose an algorithm for online admission of aperiodic tasks which provides job execution flexibility, jitter control and leads to lower latencies of aperiodic tasks.
For safety critical systems, fault-tolerance is one of the most important requirements. In time-triggered systems, modes are often used to ensure survivability against faults, i.e., when a fault is detected, current system configuration (or mode) is changed such that the overall system performance is either unaffected or degrades gracefully. In literature, it has been asserted that a task-set might be schedulable in individual modes but unschedulable during a mode-change. Moreover, conventional mode-change execution strategies might cause significant delays until the next mode is established. In order to address these issues, in this dissertation, we present an approach for schedulability analysis of mode-changes and propose mode-change delay reduction techniques in distributed system architecture defined by the DREAMS project. We evaluate our approach on an avionics use case and demonstrate that our approach can drastically reduce mode-change delays.
In order to manage increasing system complexity, real-time applications also require new design and development technologies. Other than fulfilling the technical requirements, the main features required from such technologies include modularity and re-usability. AUTOSAR is one of these technologies in automotive industry, which defines an open standard for software architecture of a real-time operating system. However, being an industrial standard, the available proprietary tools do not support model extensions and/or new developments by third-parties and, therefore, hinder the software evolution. To solve this problem, we developed an open-source AUTOSAR toolchain which supports application development and code generation for several modules. In order to exhibit the capabilities of our toolchain, we developed two case studies. These case studies demonstrate that our toolchain generates valid artifacts, avoids dirty workarounds and supports application development.
In order to cope with evolving system designs and hardware platforms, rapid-development of scheduling and analysis algorithms is required. In order to ease the process of algorithm development, a number of scheduling and analysis frameworks are proposed in literature. However, these frameworks focus on a specific class of applications and are limited in functionality. In this dissertation, we provide the skeleton of a scheduling and analysis framework for real-time systems. In order to support rapid-development, we also highlight different development components which promote code reuse and component modularity.
Composite materials are used in many modern tools and engineering applications and
consist of two or more materials that are intermixed. Features like inclusions in a matrix
material are often very small compared to the overall structure. Volume elements that
are characteristic for the microstructure can be simulated and their elastic properties are
then used as a homogeneous material on the macroscopic scale.
Moulinec and Suquet [2] solve the so-called Lippmann-Schwinger equation, a reformulation of the equations of elasticity in periodic homogenization, using truncated
trigonometric polynomials on a tensor product grid as ansatz functions.
In this thesis, we generalize their approach to anisotropic lattices and extend it to
anisotropic translation invariant spaces. We discretize the partial differential equation
on these spaces and prove the convergence rate. The speed of convergence depends on
the smoothness of the coefficients and the regularity of the ansatz space. The spaces of
translates unify the ansatz of Moulinec and Suquet with de la Vallée Poussin means and
periodic Box splines, including the constant finite element discretization of Brisard and
Dormieux [1].
For finely resolved images, sampling on a coarser lattice reduces the computational
effort. We introduce mixing rules as the means to transfer fine-grid information to the
smaller lattice.
Finally, we show the effect of the anisotropic pattern, the space of translates, and the
convergence of the method, and mixing rules on two- and three-dimensional examples.
References
[1] S. Brisard and L. Dormieux. “FFT-based methods for the mechanics of composites:
A general variational framework”. In: Computational Materials Science 49.3 (2010),
pp. 663–671. doi: 10.1016/j.commatsci.2010.06.009.
[2] H. Moulinec and P. Suquet. “A numerical method for computing the overall response
of nonlinear composites with complex microstructure”. In: Computer Methods in
Applied Mechanics and Engineering 157.1-2 (1998), pp. 69–94. doi: 10.1016/s00457825(97)00218-1.
The phase field approach is a powerful tool that can handle even complicated fracture phenomena within an apparently simple framework. Nonetheless, a profound understanding of the model is required in order to be able to interpret the obtained results correctly. Furthermore, in the dynamic case the phase field model needs to be verified in comparison to experimental data and analytical results in order to increase the trust in this new approach. In this thesis, a phase field model for dynamic brittle fracture is investigated with regard to these aspects by analytical and numerical methods
Using valuation theory we associate to a one-dimensional equidimensional semilocal Cohen-Macaulay ring \(R\) its semigroup of values, and to a fractional ideal of \(R\) we associate its value semigroup ideal. For a class of curve singularities (here called admissible rings) including algebroid curves the semigroups of values, respectively the value semigroup ideals, satisfy combinatorial properties defining good semigroups, respectively good semigroup ideals. Notably, the class of good semigroups strictly contains the class of value semigroups of admissible rings. On good semigroups we establish combinatorial versions of algebraic concepts on admissible rings which are compatible with their prototypes under taking values. Primarily we examine duality and quasihomogeneity.
We give a definition for canonical semigroup ideals of good semigroups which characterizes canonical fractional ideals of an admissible ring in terms of their value semigroup ideals. Moreover, a canonical semigroup ideal induces a duality on the set of good semigroup ideals of a good semigroup. This duality is compatible with the Cohen-Macaulay duality on fractional ideals under taking values.
The properties of the semigroup of values of a quasihomogeneous curve singularity lead to a notion of quasihomogeneity on good semigroups which is compatible with its algebraic prototype. We give a combinatorial criterion which allows to construct from a quasihomogeneous semigroup \(S\) a quasihomogeneous curve singularity having \(S\) as semigroup of values.
As an application we use the semigroup of values to compute endomorphism rings of maximal ideals of algebroid curves. This yields an explicit description of the intermediate rings in an algorithmic normalization of plane central arrangements of smooth curves based on a criterion by Grauert and Remmert. Applying this result to hyperplane arrangements we determine the number of steps needed to compute the normalization of a the arrangement in terms of its Möbius function.
Fucoidan is a class of biopolymers mainly found in brown seaweeds. Due to its diverse medical importance, homogenous supply as well as a GMP-compliant product is of a special interest. Therefore, in addition to optimization of its extraction and purification from classical resources, other techniques were tried (e.g., marine tissue culture and heterologous expression of enzymes involved in its biosynthesis). Results showed that 17.5% (w/w) crude fucoidan after pre-treatment and extraction was obtained from the brown macroalgae F. vesiculosus. Purification by affinity chromatography improved purity relative to the commercial purified product. Furthermore, biological investigations revealed improved anti-coagulant and anti-viral activities compared with crude fucoidan. Furthermore, callus-like and protoplast cultures as well as bioreactor cultivation were developed from F. vesiculosus representing a new horizon to produce fucoidan biotechnologically. Moreover, heterologous expression of several enzymes involved in its biosynthesis by E. coli (e.g., FucTs and STs) demonstrated the possibility to obtain active enzymes that could be utilized in enzymatic in vitro synthesis of fucoidan. All these competitive techniques could provide the global demands from fucoidan.
Multiphase materials combine properties of several materials, which makes them interesting for high-performing components. This thesis considers a certain set of multiphase materials, namely silicon-carbide (SiC) particle-reinforced aluminium (Al) metal matrix composites and their modelling based on stochastic geometry models.
Stochastic modelling can be used for the generation of virtual material samples: Once we have fitted a model to the material statistics, we can obtain independent three-dimensional “samples” of the material under investigation without the need of any actual imaging. Additionally, by changing the model parameters, we can easily simulate a new material composition.
The materials under investigation have a rather complicated microstructure, as the system of SiC particles has many degrees of freedom: Size, shape, orientation and spatial distribution. Based on FIB-SEM images, that yield three-dimensional image data, we extract the SiC particle structure using methods of image analysis. Then we model the SiC particles by anisotropically rescaled cells of a random Laguerre tessellation that was fitted to the shapes of isotropically rescaled particles. We fit a log-normal distribution for the volume distribution of the SiC particles. Additionally, we propose models for the Al grain structure and the Aluminium-Copper (\({Al}_2{Cu}\)) precipitations occurring on the grain boundaries and on SiC-Al phase boundaries.
Finally, we show how we can estimate the parameters of the volume-distribution based on two-dimensional SEM images. This estimation is applied to two samples with different mean SiC particle diameters and to a random section through the model. The stereological estimations are within acceptable agreement with the parameters estimated from three-dimensional image data
as well as with the parameters of the model.
Field-effect transistor (FET) sensors and in particular their nanoscale variant of silicon nanowire transistors are very promising technology platforms for label-free biosensor applications. These devices directly detect the intrinsic electrical charge of biomolecules at the sensor’s liquid-solid interface. The maturity of micro fabrication techniques enables very large FET sensor arrays for massive multiplex detection. However, the direct detection of charged molecules in liquids faces a significant limitation due to a charge screening effect in physiological solutions, which inhibits the realization of point-of-care applications. As an alternative, impedance spectroscopy with FET devices has the potential to enable measurements in physiological samples. Even though promising studies were published in the field, impedimetric detection with silicon FET devices is not well understood.
The first goal of this thesis was to understand the device performances and to relate the effects seen in biosensing experiments to device and biomolecule types. A model approach should help to understand the capability and limitations of the impedimetric measurement method with FET biosensors. In addition, to obtain experimental results, a high precision readout device was needed. Consequently, the second goal was to build up multi-channel, highly accurate amplifier systems that would also enable future multi-parameter handheld devices.
A PSPICE FET model for potentiometric and impedimetric detection was adapted to the experiments and further expanded to investigate the sensing mechanism, the working principle, and effects of side parameters for the biosensor experiments. For potentiometric experiments, the pH sensitivity of the sensors was also included in this modelling approach. For impedimetric experiments, solutions of different conductivity were used to validate the suggested theories and assumptions. The impedance spectra showed two pronounced frequency domains: a low-pass characteristic at lower frequencies and a resonance effect at higher frequencies. The former can be interpreted as a contribution of the source and double layer capacitances. The latter can be interpreted as a combined effect of the drain capacitance with the operational amplifier in the transimpedance circuit.
Two readout systems, one as a laboratory system and one as a point-of-care demonstrator, were developed and used for several chemical and biosensing experiments. The PSPICE model applied to the sensors and circuits were utilized to optimize the systems and to explain the sensor responses. The systems as well as the developed modelling approach were a significant step towards portable instruments with combined transducer principles in future healthcare applications.
European economic, social and territorial cohesion is one of the fundamental aims of the European Union (EU). It seeks to both reduce the effects of internal borders and enhance European integration. In order to facilitate territorial cohesion, the linkage of member states by means of efficient cross-border transport infrastructures and services is an important factor. Many cross-border transport challenges have historically existed in everyday life. They have hampered smooth passenger and freight flows within the EU.
Two EU policies, namely European Territorial Cooperation (ETC) and the Trans-European Transport Networks (TEN-T), promote enhancing cross-border transport through cooperation in soft spaces. This dissertation seeks to explore the influence of these two EU policies on cross-border transport and further European integration.
Based on an analysis of European, national and cross-border policy and planning documents, surveys with TEN-T Corridor Coordinators and INTERREG Secretariats and a high number of elite interviews, the dissertation will investigate how the objectives of the two EU policies were formally implemented in both soft spaces and the EU member states as well as which practical implementations have taken place. Thereby, the initiated Europeanisation and European integration processes will be evaluated. The analysis is conducted in nine preliminary case studies and two in-depth case studies. The cases comprise cross-border regions funded by the ETC policy that are crossed by a TEN-T corridor. The in-depth analysis explores the Greater Region Saar-Lor-Lux+ and the Brandenburg-Lubuskie region. The cases are characterised by different initial situations.
The research determined that the two EU policies support cross-border transport on different levels and, further, that they need to be better intertwined in order to make effective use of their complementarities. Moreover, it became clear that the EU policies have a distinct influence on domestic policy and planning documents of different administrative levels and countries as well as on the practical implementation. The final implementation of the EU objectives and the cross-border transport initiatives was strongly influenced by the member states’ initial situations – particularly, the regional and local transport needs. This dissertation concludes that the two EU policies cannot remove the entirety of the cross-border transport-related challenges. However, in addition to their financial investments in concrete projects, they promote the importance of cross-border transport and facilitate cooperation, learning and exchange processes. These are all of high relevance to cross-border transport development, driven by member states, as well as to further European integration.
The dissertation recommends that the transport planning competences of the EU in addition to the TEN-T network should not be enlarged in the future, but rather further transnational transport development tasks should be decentralised to transnational transport planning committees that are aware of regional needs and can coordinate a joint transport development strategy. The latter should be implemented with the support of additional EU funds for secondary and tertiary cross-border connections. Moreover, the potential complementarities of the transnational regions and transport corridors as well as the two EU policy fields should be made better use of by improving communication. This means that soft spaces, the TEN-T and ETC Policy as well as the domestic transport ministries and the domestic administrations that are responsible for the two EU policies need to intensify their cooperation. Furthermore, a focus of future ETC projects on topics that are of added value for the whole cross-border region or else that can be applied in different territorial contexts is recommended rather than investing in small-scale scattered expensive infrastructures and services that are only of benefit for a small part of the region. Additionally, the dissemination of project results should be enhanced so that the developed tools can be accessed by potential users and benefits become more visible to a wider society, despite the fact that they might not be measurable in numbers. In addition, the research points at another success factor for more concrete outputs: the frequent involvement of transport and spatial planners in transnational projects could increase the relation to planning practice. Besides that, advanced training regarding planning culture could reduce cooperation barriers.
Epoxy belongs to a category of high-performance thermosetting polymers which have been used extensively in industrial and consumer applications. Highly cross-linked epoxy polymers offer excellent mechanical properties, adhesion, and chemical resistance. However, unmodified epoxies are prone to brittle fracture and crack propagation due to their highly crosslinked structure. As a result, epoxies are normally toughened to ensure the usability of these materials in practical applications.
This research work focuses on the development of novel modified epoxy matrices, with enhanced mechanical, fracture mechanical and thermal properties, suitable to be processed by filament winding technology, to manufacture composite based calender roller covers with improved performance in comparison to commercially available products.
In the first stage, a neat epoxy resin (EP) was modified using three different high functionality epoxy resins with two type of hardeners i.e. amine-based (H1) and anhydride-based (H2). Series of hybrid epoxy resins were obtained by systematic variation of high functionality epoxy resin contents with reference epoxy system. The resulting matrices were characterized by their tensile properties and the best system was chosen from each hardener system i.e. amine and anhydride. For tailored amine based system (MEP_H1) 14 % improvement was measured for bulk samples similarly, for tailored anhydride system (MEP_H2) 11 % improvement was measured when tested at 23 °C.
Further, tailored epoxy systems (MEP_H1 and MEP_H2) were modified using specially designed block copolymer (BCP), and core-shell rubber nanoparticles (CSR). Series of nanocomposites were obtained by systematic variation of filler contents. The resulting matrices were extensively characterized qualitatively and quantitatively to reveal the effect of each filler on the polymer properties. It was shown that the BCP confer better fracture properties to the epoxy resin at low filler loading without losing the other mechanical properties. These characteristics were accompanied by ductility and temperature stability. All composites were tested at 23 °C and at 80 °C to understand the effect of temperature on the mechanical and fracture properties.
Examinations on fractured specimen surfaces provided information about the mechanisms responsible for reinforcement. Nanoparticles generate several energy dissipating mechanisms in the epoxy, e.g. plastic deformation of the matrix, cavitation, void growth, debonding and crack pinning. These were closely related to the microstructure of the materials. The characteristic of the microstructure was verified by microscopy methods (SEM and AFM). The microstructure of neat epoxy hardener system was strongly influenced by the nanoparticles and the resulting interfacial interactions. The interaction of nanoparticles with a different hardener system will result in different morphology which will ultimately influence the mechanical and fracture mechanical properties of the nanocomposites. Hybrid toughening using a combination of the block-copolymer / core-shell rubber nanoparticles and block copolymer / TiO2 nanoparticles has been investigated in the epoxy systems. It was found out that addition of rigid phase with a soft phase recovers the loss of strength in the nanocomposites caused by a softer phase.
In order to clarify the relevant relationships, the microstructural and mechanical properties were correlated. The Counto’s, Halpin-Tsai, and Lewis-Nielsen equations were used to calculate the modulus of the composites and predicted modulus fit well with the measured values. Modeling was done to predict the toughening contribution from block copolymers and core-shell rubber nanoparticles. There was good agreement between the predicted values and the experimental values for the fracture energy.
Embedded reactive systems underpin various safety-critical applications wherein they interact with other systems and the environment with limited or even no human supervision. Therefore, design errors that violate essential system specifications can lead to severe unacceptable damages. For this reason, formal verification of such systems in their physical environment is of high interest. Synchronous programs are typically used to represent embedded reactive systems while hybrid systems serve to model discrete reactive system in a continuous environment. As such, both synchronous programs and hybrid systems play important roles in the model-based design of embedded reactive systems. This thesis develops induction-based techniques for safety property verification of synchronous and hybrid programs. The imperative synchronous language Quartz and its hybrid systems’ extensions are used to sustain the findings.
Deductive techniques for software verification typically use Hoare calculus. In this context, Verification Condition Generation (VCG) is used to apply Hoare calculus rules to a program whose statements are annotated with pre- and postconditions so that the validity of an obtained Verification Condition (VC) implies correctness of a given proof goal. Due to the abstraction of macro steps, Hoare calculus cannot directly generate VCs of synchronous programs unless it handles additional label variables or goto statements. As a first contribution, Floyd’s induction-based approach is employed to generate VCs for synchronous and hybrid programs. Five VCG methods are introduced that use inductive assertions to decompose the overall proof goal. Given the right assertions, the procedure can automatically generate a set of VCs that can then be checked by SMT solvers or automated theorem provers. The methods are proved sound and relatively complete, provided that the underlying assertion language is expressive enough. They can be applied to any program with a state-based semantics.
Property Directed Reachability (PDR) is an efficient method for synchronous hardware circuit verification based on induction rather than fixpoint computation. Crucial steps of the PDR method consist of deciding about the reachability of Counterexamples to Induction (CTIs) and generalizing them to clauses that cover as many unreachable states as possible. The thesis demonstrates that PDR becomes more efficient for imperative synchronous programs when using the distinction between the control- and dataflow. Before calling the PDR method, it is possible to derive additional program control-flow information that can be added to the transition relation such that less CTIs will be generated. Two methods to compute additional control-flow information are presented that differ in how precisely they approximate the reachable control-flow states and, consequently, in their required runtime. After calling the PDR method, the CTI identification work is reduced to its control-flow part and to checking whether the obtained control-flow states are unreachable in the corresponding extended finite state machine of the program. If so, all states of the transition system that refer to the same program locations can be excluded, which significantly increases the performance of PDR.
Grape powdery mildew, Erysiphe necator, is one of the most significant plant pathogens, which affects grape growing regions world-wide. Because of its short generation time and the production of large amounts of conidia throughout the season, E. necator is classified as a moderate to high risk pathogen with respect to the development of fungicide resistance. The number of fungicidal mode of actions available to control powdery mildew is limited and for some of them resistances are already known. Aryl-phenyl-ketones (APKs), represented by metrafenone and pyriofenone, and succinate-dehydrogenase inhibitors (SDHIs), composed of numerous active ingredients, are two important fungicide classes used for the control of E. necator. Over the period 2014 to 2016, the emergence and development of metrafenone and SDHI resistant E. necator isolates in Europe was followed and evaluated. The distribution of resistant isolates was thereby strongly dependent on the European region. Whereas the north-western part is still predominantly sensitive, samples from east European countries showed higher resistance frequencies.
Classical sensitivity tests with obligate biotrophs can be challenging regarding sampling, transport and especially the maintenance of the living strains. Whenever possible, molecular genetic methods are preferred for a more efficient monitoring. Such methods require the knowledge of the resistance mechanisms. The exact molecular target and the resistance mechanism of metrafenone is still unknown. Whole genome sequencing of metrafenone sensitive and resistant wheat powdery mildew isolates, as well as adapted laboratory mutants of Aspergillus nidulans, where performed with the aim to identify proteins potentially linked to the mode of action or which contribute to metrafenone resistance. Based on comparative SNP analysis, four proteins potentially associated with metrafenone resistance were identified, but validation studies could not confirm their role in metrafenone resistance. In contrast to APKs, the mode of action of SDHIs is well understood. Sequencing of the sdh-genes of less sensitive E. necator isolates identified four different target-site mutations, the B-H242R, B-I244V, C-G169D and C-G169S, in sdhB and sdhC, respectively. Based on this information it was possible to develop molecular genetic monitoring methods for the mutations B-H242R and C-G169D. In 2016, the B-H242R was thereby identified as by far the most frequent mutation. Depending on the analysed SDH compound and the sdh-genotype, different sensitivities were observed and revealed a complex cross-resistance pattern.
Growth competition assays without selection pressure, with mixtures of sensitive and resistant E. necator isolates, were performed to determine potential fitness costs associated with fungicide resistance. With the experimental setups used, a clear fitness disadvantage associated with metrafenone resistance was not identified, although a strong variability of fitness was observed among the tested resistant E. necator isolates. For isolates with a reduced sensitivity towards SDHIs, associated fitness costs were dependent on the sdh-genotype analysed. Competition tests with the B-H242R genotypes gave evidence that there are no fitness costs associated with this mutation. In contrast, the C-G169D genotypes were less competitive, indicating a restricted fitness compared to the tested sensitive partners. Competition assays of field isolates, which exhibited several resistances towards different fungicide classes, indicated that there are no fitness costs associated with a multiple resistant phenotype in E. necator. Overall, these results clearly indicate the importance to analyse a representative number of isolates with sensitive and resistant phenotypes.
Analyzing Centrality Indices in Complex Networks: an Approach Using Fuzzy Aggregation Operators
(2018)
The identification of entities that play an important role in a system is one of the fundamental analyses being performed in network studies. This topic is mainly related to centrality indices, which quantify node centrality with respect to several properties in the represented network. The nodes identified in such an analysis are called central nodes. Although centrality indices are very useful for these analyses, there exist several challenges regarding which one fits best
for a network. In addition, if the usage of only one index for determining central
nodes leads to under- or overestimation of the importance of nodes and is
insufficient for finding important nodes, then the question is how multiple indices
can be used in conjunction in such an evaluation. Thus, in this thesis an approach is proposed that includes multiple indices of nodes, each indicating
an aspect of importance, in the respective evaluation and where all the aspects of a node’s centrality are analyzed in an explorative manner. To achieve this
aim, the proposed idea uses fuzzy operators, including a parameter for generating different types of aggregations over multiple indices. In addition, several preprocessing methods for normalization of those values are proposed and discussed. We investigate whether the choice of different decisions regarding the
aggregation of the values changes the ranking of the nodes or not. It is revealed that (1) there are nodes that remain stable among the top-ranking nodes, which
makes them the most central nodes, and there are nodes that remain stable
among the bottom-ranking nodes, which makes them the least central nodes; and (2) there are nodes that show high sensitivity to the choice of normalization
methods and/or aggregations. We explain both cases and the reasons why the nodes’ rankings are stable or sensitive to the corresponding choices in various networks, such as social networks, communication networks, and air transportation networks.
In modern algebraic geometry solutions of polynomial equations are studied from a qualitative point of view using highly sophisticated tools such as cohomology, \(D\)-modules and Hodge structures. The latter have been unified in Saito’s far-reaching theory of mixed Hodge modules, that has shown striking applications including vanishing theorems for cohomology. A mixed Hodge module can be seen as a special type of filtered \(D\)-module, which is an algebraic counterpart of a system of linear differential equations. We present the first algorithmic approach to Saito’s theory. To this end, we develop a Gröbner basis theory for a new class of algebras generalizing PBW-algebras.
The category of mixed Hodge modules satisfies Grothendieck’s six-functor formalism. In part these functors rely on an additional natural filtration, the so-called \(V\)-filtration. A key result of this thesis is an algorithm to compute the \(V\)-filtration in the filtered setting. We derive from this algorithm methods for the computation of (extraordinary) direct image functors under open embeddings of complements of pure codimension one subvarieties. As side results we show
how to compute vanishing and nearby cycle functors and a quasi-inverse of Kashiwara’s equivalence for mixed Hodge modules.
Describing these functors in terms of local coordinates and taking local sections, we reduce the corresponding computations to algorithms over certain bifiltered algebras. It leads us to introduce the class of so-called PBW-reduction-algebras, a generalization of the class of PBW-algebras. We establish a comprehensive Gröbner basis framework for this generalization representing the involved filtrations by weight vectors.
The simulation of cutting process challenges established methods due to large deformations and topological changes. In this work a particle finite element method (PFEM) is presented, which combines the benefits of discrete modeling techniques and methods based on continuum mechanics. A crucial part of the PFEM is the detection of the boundary of a set of particles. The impact of this boundary detection method on the structural integrity is examined and a relation of the key parameter of the method to the eigenvalues of strain tensors is elaborated. The influence of important process parameters on the cutting force is studied and a comparison to an empirical relation is presented.
The aim of this dissertation is to explain processes in recruitment by gaining a better understanding of how perceptions evolve and how recruitment outcomes and perceptions are influenced. To do so, this dissertation takes a closer look at the formation of fit perceptions, the effects of top employer awards on pre-hire recruitment outcomes, and on how perceptions about external sources are influenced.
The gas phase infrared and fragmentation spectra of a systematic group of trimetallic oxo-centered
transition metal complexes are shown and discussed, with formate and acetate bridging ligands and
pyridine and water as axial ligands.
The stability of the complexes, as predicted by appropriate ab initio simulations, is demonstrated to
agree with collision induced dissociation (CID) measurements.
A broad range of DFT calculations are shown. They are used to simulate the geometry, the bonding
situation, relative stability and flexibility of the discussed complexes, and to specify the observed
trends. These simulations correctly predict the trends in the band splitting of the symmetric and
asymmetric carboxylate stretch modes, but fail to account for anharmonic effects observed specifically
in the mid IR range.
The infrared spectra of the different ligands are introduced in a brief literature review. Their changes
in different environments or different bonding situations are discussed and visualized, especially the
interplay between fundamental-, overtone-, and combination bands, as well as Fermi resonances
between them.
A new variation on the infrared multi photon dissociation (IRMPD) spectroscopy method is proposed
and evaluated. In addition to the commonly considered total fragment yield, the cumulative fragment
yield can be used to plot the wavelength dependent relative abundance of different fragmentation
products. This is shown to include valuable additional information on the excited chromophors, and
their coupling to specific fragmentation channels.
High quality homo- and heterometallic IRMPD spectra of oxo centered carboxylate complexes of
chromium and iron show the impacts of the influencing factors: the metal centers, the bridging ligands,
their carboxylate stretch modes and CH bend modes, and the terminal ligands.
In all four formate spectra, anharmonic effects are necessary to explain the observed spectra:
combination bands of both carboxylate stretch modes and a Fermi resonance of the fundamental of
the CH stretch mode, and a combination band of the asymmetric carboxylate stretch mode with the
CH bend mode of the formate bridging ligand.
For the water adduct species, partial hydrolysis is proposed to account for the changes in the observed
carboxylic stretch modes.
Appropriate experiments are suggested to verify the mode assignments that are not directly explained
by the ab initio calculations, the available experimental results or other means like deuteration
experiments.
Certain brain tumours are very hard to treat with radiotherapy due to their irregular shape caused by the infiltrative nature of the tumour cells. To enhance the estimation of the tumour extent one may use a mathematical model. As the brain structure plays an important role for the cell migration, it has to be included in such a model. This is done via diffusion-MRI data. We set up a multiscale model class accounting among others for integrin-mediated movement of cancer cells in the brain tissue, and the integrin-mediated proliferation. Moreover, we model a novel chemotherapy in combination with standard radiotherapy.
Thereby, we start on the cellular scale in order to describe migration. Then we deduce mean-field equations on the mesoscopic (cell density) scale on which we also incorporate cell proliferation. To reduce the phase space of the mesoscopic equation, we use parabolic scaling and deduce an effective description in the form of a reaction-convection-diffusion equation on the macroscopic spatio-temporal scale. On this scale we perform three dimensional numerical simulations for the tumour cell density, thereby incorporating real diffusion tensor imaging data. To this aim, we present programmes for the data processing taking the raw medical data and processing it to the form to be included in the numerical simulation. Thanks to the reduction of the phase space, the numerical simulations are fast enough to enable application in clinical practice.
In modern algebraic geometry solutions of polynomial equations are studied from a qualitative point of view using highly sophisticated tools such as cohomology, \(D\)-modules and Hodge structures. The latter have been unified in Saito’s far-reaching theory of mixed Hodge modules, that has shown striking applications including vanishing theorems for cohomology. A mixed Hodge module can be seen as a special type of filtered \(D\)-module, which is an algebraic counterpart of a system of linear differential equations. We present the first algorithmic approach to Saito’s theory. To this end, we develop a Gröbner basis theory for a new class of algebras generalizing PBW-algebras.
The category of mixed Hodge modules satisfies Grothendieck’s six-functor formalism. In part these functors rely on an additional natural filtration, the so-called \(V\)-filtration. A key result of this thesis is an algorithm to compute the \(V\)-filtration in the filtered setting. We derive from this algorithm methods for the computation of (extraordinary) direct image functors under open embeddings of complements of pure codimension one subvarieties. As side results we show how to compute vanishing and nearby cycle functors and a quasi-inverse of Kashiwara’s equivalence for mixed Hodge modules.
Describing these functors in terms of local coordinates and taking local sections, we reduce the corresponding computations to algorithms over certain bifiltered algebras. It leads us to introduce the class of so-called PBW-reduction-algebras, a generalization of the class of PBW-algebras. We establish a comprehensive Gröbner basis framework for this generalization representing the involved filtrations by weight vectors.
The Symbol Grounding Problem (SGP) is one of the first attempts to proposed a hypothesis about mapping abstract concepts and the real world. For example, the concept "ball" can be represented by an object with a round shape (visual modality) and phonemes /b/ /a/ /l/ (audio modality).
This thesis is inspired by the association learning presented in infant development.
Newborns can associate visual and audio modalities of the same concept that are presented at the same time for vocabulary acquisition task.
The goal of this thesis is to develop a novel framework that combines the constraints of the Symbol Grounding Problem and Neural Networks in a simplified scenario of association learning in infants. The first motivation is that the network output can be considered as numerical symbolic features because the attributes of input samples are already embedded. The second motivation is the association between two samples is predefined before training via the same vectorial representation. This thesis proposes to associate two samples and the vectorial representation during training. Two scenarios are considered: sample pair association and sequence pair association.
Three main contributions are presented in this work.
The first contribution is a novel Symbolic Association Model based on two parallel MLPs.
The association task is defined by learning that two instances that represent one concept.
Moreover, a novel training algorithm is defined by matching the output vectors of the MLPs with a statistical distribution for obtaining the relationship between concepts and vectorial representations.
The second contribution is a novel Symbolic Association Model based on two parallel LSTM networks that are trained on weakly labeled sequences.
The definition of association task is extended to learn that two sequences represent the same series of concepts.
This model uses a training algorithm that is similar to MLP-based approach.
The last contribution is a Classless Association.
The association task is defined by learning based on the relationship of two samples that represents the same unknown concept.
In summary, the contributions of this thesis are to extend Artificial Intelligence and Cognitive Computation research with a new constraint that is cognitive motivated. Moreover, two training algorithms with a new constraint are proposed for two cases: single and sequence associations. Besides, a new training rule with no-labels with promising results is proposed.
The growing computational power enables the establishment of the Population Balance Equation (PBE)
to model the steady state and dynamic behavior of multiphase flow unit operations. Accordingly, the twophase
flow
behavior inside liquid-liquid extraction equipment is characterized by different factors. These
factors include: interactions among droplets (breakage and coalescence), different time scales due to the
size distribution of the dispersed phase, and micro time scales of the interphase diffusional mass transfer
process. As a result of this, the general PBE has no well known analytical solution and therefore robust
numerical solution methods with low computational cost are highly admired.
In this work, the Sectional Quadrature Method of Moments (SQMOM) (Attarakih, M. M., Drumm, C.,
Bart, H.-J. (2009). Solution of the population balance equation using the Sectional Quadrature Method of
Moments (SQMOM). Chem. Eng. Sci. 64, 742-752) is extended to take into account the continuous flow
systems in spatial domain. In this regard, the SQMOM is extended to solve the spatially distributed
nonhomogeneous bivariate PBE to model the hydrodynamics and physical/reactive mass transfer
behavior of liquid-liquid extraction equipment. Based on the extended SQMOM, two different steady
state and dynamic simulation algorithms for hydrodynamics and mass transfer behavior of liquid-liquid
extraction equipment are developed and efficiently implemented. At the steady state modeling level, a
Spatially-Mixed SQMOM (SM-SQMOM) algorithm is developed and successfully implemented in a onedimensional
physical spatial domain. The integral spatial numerical flux is closed using the mean mass
droplet diameter based on the One Primary and One Secondary Particle Method (OPOSPM which is the
simplest case of the SQMOM). On the other hand the hydrodynamics integral source terms are closed
using the analytical Two-Equal Weight Quadrature (TEqWQ). To avoid the numerical solution of the
droplet rise velocity, an analytical solution based on the algebraic velocity model is derived for the
particular case of unit velocity exponent appearing in the droplet swarm model. In addition to this, the
source term due to mass transport is closed using OPOSPM. The resulting system of ordinary differential
equations with respect to space is solved using the MATLAB adaptive Runge–Kutta method (ODE45). At
the dynamic modeling level, the SQMOM is extended to a one-dimensional physical spatial domain and
resolved using the finite volume method. To close the mathematical model, the required quadrature nodes
and weights are calculated using the analytical solution based on the Two Unequal Weights Quadrature
(TUEWQ) formula. By applying the finite volume method to the spatial domain, a semi-discreet ordinary
differential equation system is obtained and solved. Both steady state and dynamic algorithms are
extensively validated at analytical, numerical, and experimental levels. At the numerical level, the
predictions of both algorithms are validated using the extended fixed pivot technique as implemented in
PPBLab software (Attarakih, M., Alzyod, S., Abu-Khader, M., Bart, H.-J. (2012). PPBLAB: A new
multivariate population balance environment for particulate system modeling and simulation. Procedia
Eng. 42, pp. 144-562). At the experimental validation level, the extended SQMOM is successfully used
to model the steady state hydrodynamics and physical and reactive mass transfer behavior of agitated
liquid-liquid extraction columns under different operating conditions. In this regard, both models are
found efficient and able to follow liquid extraction column behavior during column scale-up, where three
column diameters were investigated (DN32, DN80, and DN150). To shed more light on the local
interactions among the contacted phases, a reduced coupled PBE and CFD framework is used to model
the hydrodynamic behavior of pulsed sieve plate columns. In this regard, OPOSPM is utilized and
implemented in FLUENT 18.2 commercial software as a special case of the SQMOM. The dropletdroplet
interactions
(breakage
and
coalescence)
are
taken
into
account
using
OPOSPM,
while
the
required
information
about
the
velocity
field
and
energy
dissipation
is
calculated
by
the
CFD
model.
In
addition
to
this,
the proposed coupled OPOSPM-CFD framework is extended to include the mass transfer. The
proposed framework is numerically tested and the results are compared with the published experimental
data. The required breakage and coalescence parameters to perform the 2D-CFD simulation are estimated
using PPBLab software, where a 1D-CFD simulation using a multi-sectional gird is performed. A very
good agreement is obtained at the experimental and the numerical validation levels.
Numerical Godeaux surfaces are minimal surfaces of general type with the smallest possible numerical invariants. It is known that the torsion group of a numerical Godeaux surface is cyclic of order \(m\leq 5\). A full classification has been given for the cases \(m=3,4,5\) by the work of Reid and Miyaoka. In each case, the corresponding moduli space is 8-dimensional and irreducible.
There exist explicit examples of numerical Godeaux surfaces for the orders \(m=1,2\), but a complete classification for these surfaces is still missing.
In this thesis we present a construction method for numerical Godeaux surfaces which is based on homological algebra and computer algebra and which arises from an experimental approach by Schreyer. The main idea is to consider the canonical ring \(R(X)\) of a numerical Godeaux surface \(X\) as a module over some graded polynomial ring \(S\). The ring \(S\) is chosen so that \(R(X)\) is finitely generated as an \(S\)-module and a Gorenstein \(S\)-algebra of codimension 3. We prove that the canonical ring of any numerical Godeaux surface, considered as an \(S\)-module, admits a minimal free resolution whose middle map is alternating. Moreover, we show that a partial converse of this statement is true under some additional conditions.
Afterwards we use these results to construct (canonical rings of) numerical Godeaux surfaces. Hereby, we restrict our study to surfaces whose bicanonical system has no fixed component but 4 distinct base points, in the following referred to as marked numerical Godeaux surfaces.
The particular interest of this thesis lies on marked numerical Godeaux surfaces whose torsion group is trivial. For these surfaces we study the fibration of genus 4 over \(\mathbb{P}^1\) induced by the bicanonical system. Catanese and Pignatelli showed that the general fibre is non-hyperelliptic and that the number \(\tilde{h}\) of hyperelliptic fibres is bounded by 3. The two explicit constructions of numerical Godeaux surfaces with a trivial torsion group due to Barlow and Craighero-Gattazzo, respectively, satisfy \(\tilde{h} = 2\).
With the method from this thesis, we construct an 8-dimensional family of numerical Godeaux surfaces with a trivial torsion group and whose general element satisfy \(\tilde{h}=0\).
Furthermore, we establish a criterion for the existence of hyperelliptic fibres in terms of a minimal free resolution of \(R(X)\). Using this criterion, we verify experimentally the
existence of a numerical Godeaux surface with \(\tilde{h}=1\).
This research explores the development of web based reference software for
characterisation of surface roughness for two-dimensional surface data. The reference software used for verification of surface characteristics makes the evaluation methods easier for clients. The algorithms used in this software
are based on International ISO standards. Most software used in industrial measuring
instruments may give variations in the parameters calculated due to numerical changes in
calculation. Such variations can be verified using the proposed reference software.
The evaluation of surface roughness is carried out in four major steps: data capture, data
align, data filtering and parameter calculation. This work walks through each of these steps
explaining how surface profiles are evaluated by pre-processing steps called fitting and
filtering. The analysis process is then followed by parameter evaluation according to DIN EN
ISO 4287 and DIN EN ISO 13565-2 standards to extract important information from the
profile to characterise surface roughness.
If gradient based derivative algorithms are used to improve industrial products by reducing their target functions, the derivatives need to be exact.
The last percent of possible improvement, like the efficiency of a turbine, can only be gained if the derivatives are consistent with the solution process that is used in the simulation software.
It is problematic that the development of the simulation software is an ongoing process which leads to the use of approximated derivatives.
If a derivative computation is implemented manually, it will be inconsistent after some time if it is not updated.
This thesis presents a generalized approach which differentiates the whole simulation software with Algorithmic Differentiation (AD), and guarantees a correct and consistent derivative computation after each change to the software.
For this purpose, the variable tagging technique is developed.
The technique checks at run-time if all dependencies, which are used by the derivative algorithms, are correct.
Since it is also necessary to check the correctness of the implementation, a theorem is developed which describes how AD derivatives can be compared.
This theorem is used to develop further methods that can detect and correct errors.
All methods are designed such that they can be applied in real world applications and are used within industrial configurations.
The process described above yields consistent and correct derivatives but the efficiency can still be improved.
This is done by deriving new derivative algorithms.
A fixed-point iterator approach, with a consistent derivation, yields all state of the art algorithms and produces two new algorithms.
These two new algorithms include all implementation details and therefore they produce consistent derivative results.
For detecting hot spots in the application, the state of the art techniques are presented and extended.
The data management is changed such that the performance of the software is affected only marginally when quantities, like the number of input and output variables or the memory consumption, are computed for the detection.
The hot spots can be treated with techniques like checkpointing or preaccumulation.
How these techniques change the time and memory consumption is analyzed and it is shown how they need to be used in selected AD tools.
As a last step, the used AD tools are analyzed in more detail.
The major implementation strategies for operator overloading AD tools are presented and implementation improvements for existing AD tools are discussed.
The discussion focuses on a minimal memory consumption and makes it possible to compare AD tools on a theoretical level.
The new AD tool CoDiPack is based on these findings and its design and concepts are presented.
The improvements and findings in this thesis make it possible, that an automatic, consistent and correct derivative is generated in an efficient way for industrial applications.
Mobility has become an integral feature of many wireless networks. Along with this mobility comes the need for location awareness. A prime example for this development are today’s and future transportation systems. They increasingly rely on wireless communications to exchange location and velocity information for a multitude of functions and applications. At the same time, the technological progress facilitates the widespread availability of sophisticated radio technology such as software-defined radios. The result is a variety of new attack vectors threatening the integrity of location information in mobile networks.
Although such attacks can have severe consequences in safety-critical environments such as transportation, the combination of mobility and integrity of spatial information has not received much attention in security research in the past. In this thesis we aim to fill this gap by providing adequate methods to protect the integrity of location and velocity information in the presence of mobility. Based on physical effects of mobility on wireless communications, we develop new methods to securely verify locations, sequences of locations, and velocity information provided by untrusted nodes. The results of our analyses show that mobility can in fact be exploited to provide robust security at low cost.
To further investigate the applicability of our schemes to real-world transportation systems, we have built the OpenSky Network, a sensor network which collects air traffic control communication data for scientific applications. The network uses crowdsourcing and has already achieved coverage in most parts of the world with more than 1000 sensors.
Based on the data provided by the network and measurements with commercial off-the-shelf hardware, we demonstrate the technical feasibility and security of our schemes in the air traffic scenario. Moreover, the experience and data provided by the OpenSky Network allows us to investigate the challenges for our schemes in the real-world air traffic communication environment. We show that our verification methods match all
requirements to help secure the next generation air traffic system.
Road accidents remain as one of the major causes of death and injuries globally. Several million people die every year due to road accidents all over the world. Although the number of accidents in European region have reduced in the past years, road safety still remains a major challenge. Especially in case of commercial trucks, due to the size and load of the vehicle, even minor collisions with other road users would lead to serious injuries or death. In order to reduce number of accidents, automotive industry is rapidly developing advanced driver assistance systems (ADAS) and automated driving technologies. Efficient and reliable solutions are required for these systems to sense, perceive and react to different environmental conditions. For vehicle safety applications such as collision avoidance with vulnerable road users (VRUs), it is not only important for the system to efficiently detect and track the objects in the vicinity of the vehicle but should also function robustly.
An environment perception solution for application in commercial truck safety systems and for future automated driving is developed in this work. Thereby a method for integrated tracking and classification of road users in the near vicinity of the vehicle is formulated. The drawbacks in conventional multi-object tracking algorithms with respect to state, measurement and data association uncertainties have been addressed with the recent advancements in the field of unified multi-object tracking solutions based on random finite sets (RFS). Gaussian mixture implementation of the recently developed labeled multi-Bernoulli (LMB) filter [RSD15] is used as the basis for multi-object tracking in this work. Measurement from an high-resolution radar sensor is used as the main input for detecting and tracking objects.
On one side, the focus of this work is on tracking VRUs in the near vicinity of the truck. As it is beneficial for most of the vehicle safety systems to also know the category that the object belongs to, the focus on the other side is also to classify the road users. All the radar detections believed to originate from a single object are clustered together with help of density based spatial clustering for application with noise (DBSCAN) algorithm. Each cluster of detections would have different properties based on the respective object characteristics. Sixteen distinct features based on radar detections, that are suitable for separating pedestrians, bicyclists and passenger car categories are selected and extracted for each of the cluster. A machine learning based classifier is constructed, trained and parameterised for distinguishing the road users based on the extracted features.
The class information derived from the radar detections can further be used by the tracking algorithm, to adapt the model parameters used for precisely predicting the object motion according to the category of the object. Multiple model labeled multi-Bernoulli filter (MMLMB) is used for modelling different object motions. Apart from the detection level, the estimated state of an object on the tracking level also provides information about the object class. Both these informations are fused using Dempster-Shafer theory (DST) of evidence, based on respective class probabilities Thereby, the output of the integrated tracking and classification with MMLMB filter are classified tracks that can be used by truck safety applications with better reliability.
The developed environment perception method is further implemented as a real-time prototypical system on a commercial truck. The performance of the tracking and classification approaches are evaluated with the help of simulation and multiple test scenarios. A comparison of the developed approaches to a conventional converted measurements Kalman filter with global nearest neighbour association (CMKF-GNN) shows significant advantages in the overall accuracy and performance.
Increasing costs due to the rising attrition of drug candidates in late developmental phases alongside post-marketing withdrawal of drugs challenge the pharmaceutical industry to further improve their current preclinical safety assessment strategies. One of the most common reasons for the termination of drug candidates is drug induced hepatotoxicity, which more often than not remains undetected in early developmental stages, thus emphasizing the necessity for improved and more predictive preclinical test systems. One reason for the very limited value of currently applied in vitro test systems for the detection of potential hepatotoxic liabilities is the lack of organotypic and tissue-specific physiology of hepatocytes cultured in ordinary monolayer culture formats.
The thesis at hand primarily deals with the evaluation of both two- and three-dimensional cell culture approaches with respect to their relative ability to predict the hepatotoxic potential of drug candidates in early developmental phases. First, different hepatic cell models, which are routinely used in pharmaceutical industry (primary human hepatocytes as well as the three cell lines HepG2, HepaRG and Upcyte hepatocytes), were investigated in conventional 2D monolayer culture with respect to their ability to detect hepatotoxic effects in simple cytotoxicity studies. Moreover, it could be shown that the global protein expression levels of all cell lines substantially differ from that of primary human hepatocytes, with the least pronounced difference in HepaRG cells.
The introduction of a third dimension through the cultivation of spheroids enables hepatocytes to recapitulate their typical native polarity and furthermore dramatically increases the contact surface of adjacent cells. These differences in cellular architecture have a positive influence on hepatocyte longevity and the expression of drug metabolizing enzymes and transporters, which could be proven via immunofluorescent (IF) staining for at least 14 days in PHH and at least 28 days in HepaRG spheroids, respectively. Additionally, the IF staining of three different phase III transporters (MDR1, MRP2 and BSEP) indicated a bile canalicular network in spheroids of both cell models. A dose-dependent inducibility of important cytochrome P450 isoenzymes in HepaRG spheroids could be shown on the protein level via IF for at least 14 days. CYP inducibility of HepaRG cells cultured in 2D and 3D was compared on the mRNA level for up to 14 days and inducibility was generally lower in 3D compared to 2D under the conditions of this study. In a comparative cytotoxicity study, both PHH and HepaRG spheroids as well as HepaRG monolayers have been treated with five hepatotoxic drugs for up to 14 days and viability was measured at three time points (days 3, 7 and 14). A clear time- and dose-dependent onset of the drug-induced hepatotoxic effects was observable in all conditions tested, indicated by a shift of the respective EC50 value towards lower doses by increasing exposure. The observed effects were most pronounced in PHH spheroids, thus indicating those as the most sensitive cell model in this study. Moreover, HepaRG cells were more sensitive in spheroid culture compared to monolayers, which suggests a potential application of spheroids as long-term test system for the detection of hepatotoxicities with slow onset. Finally, the basal protein expression levels of three antigens (CYP1A2, CYP3A4 and NAT 1/2) were analyzed via Western Blotting in HepaRG cells cultured in three different cell culture formats (2D, 3D and QV) in order to estimate the impact of the cell culture conditions on protein expression levels. In the QV system enables a pump-driven flow of cell culture media, which introduces both mechanical stimuli through shear and molecular stimuli through dynamic circulation to the monolayer. Those stimuli resulted in a clearly positive effect on the expression levels of the selected antigens by an increased expression level in comparison to both 2D and 3D. In contrast, HepaRG spheroids showed time-dependent differences with the overall highest levels at day 7.
The studies presented in this thesis delivered valuable information on the increased physiological relevance in dependence on the cell culture format: three-dimensionality as well as the circulation of media lead to a more differentiated phenotype in hepatic cell models. Those cell culture formats are applicable in preclinical drug development in order to obtain more relevant information at early developmental stages and thus help to create a more efficient drug development process. Nonetheless, further studies are necessary to thoroughly characterize, validate and standardize such novel cell culture approaches prior to their routine application in industry.
This thesis consists of five chapters. Chapter one elaborates on the principle of cognitive consistency and provides an overview of what extant research refers to as cognitive consistency theories (e.g., Abelson et al., 1968; Harmon-Jones & Harmon-Jones, 2007; Simon, Stenstrom, & Read, 2015). Moreover, it describes the most prominent theoretical representatives in this context, namely balance theory (Heider, 1946, 1958), congruity theory (Osgood & Tannenbaum, 1955), and cognitive dissonance theory (Festinger, 1957). Chapter one further outlines the role of individuals’ preference for cognitive consistency in the context of financial resource acquisition, the recruitment of employees and the acquisition of customers in the entrepreneurial context.
Chapter two is co-authored by Prof. Dr. Matthias Baum and presents two separate studies in which we empirically investigate the hypothesis that social entrepreneurs face a systematic disadvantage, compared to for-profit entrepreneurs, when seeking to acquire financial resources. Further, our work goes beyond existing research by introducing biased perceptions as a factor that may constrain social enterprise resource acquisition and therefore possibly stall the process of social value creation. On the foundation of role congruity theory (Eagly & Karau, 2002), we emphasize on the question whether social entrepreneurs provide signals which are less congruent with the stereotype of successful entrepreneurs and, in such, are perceived as less competent. We further test whether such biased competency perceptions feed forward into a lower probability to receive funding.
Chapter three is also co-authored by Prof. Dr. Matthias Baum as well as by Eva Henrich. The aim of this chapter is to further our understanding of the early recruitment phase and to contribute to the current debate about how firms should orchestrate their recruitment channels in order to enhance the creation of employer knowledge. We introduce the concept of integrated marketing communication into the recruitment field and examine how the level of consistency regarding job or organization information affects the recall and the recognition of that information. We additionally test whether information consistency among multiple recruitment channels influences information recognition failure quota. Answering this question is important as by failing to remember the source of recruitment information, job seekers may attribute job information to the wrong firm and thus create an incorrect employer knowledge.
Chapter four, which is co-authored by Prof. Dr. Matthias Baum, introduces customer congruity perceptions between a brand and a reward in the context of customer referral programs as an essential driver of the effectiveness of such programs. More precisely, we posit and empirically test a model according to which the decision-making process of the customer recommending a firm involves multiple mental steps and assumes reward perceptions to be an immediate antecedent of brand evaluation, which then, ultimately shapes the likelihood of recommendation. The level of congruity/incongruity is set up as an antecedent state and affects the perceived attractiveness of the reward. Our work contributes to the discussion on the optimal level of congruity between a prevailing schema in the mind of the customer and a stimulus presented. In addition, chapter four introduces customer referral programs as a strategic tool for brand managers. Chapter four is further published in Psychology & Marketing.
Chapter five first proposes that marketing strategies specifically designed to induce word-of-mouth (WOM) behavior are particular relevant for new ventures. Against the background that previous research suggests that customer perceptions of young firm age may influence customer behavior and the degree to which customers support new ventures (e.g., Choi & Shepherd, 2005; Stinchcombe, 1965), we secondly conduct an experiment to examine the causal mechanisms linking firm age and customer WOM. Chapter five, too, is co-authored by Prof. Dr. Matthias Baum.
The transfer of substrates between to enzymes within a biosynthesis pathway is an effective way to synthesize the specific product and a good way to avoid metabolic interference. This process is called metabolic channeling and it describes the (in-)direct transfer of an intermediate molecule between the active sites of two enzymes. By forming multi-enzyme cascades the efficiency of product formation and the flux is elevated and intermediate products are transferred and converted in a correct manner by the enzymes.
During tetrapyrrole biosynthesis several substrate transfer events occur and are prerequisite for an optimal pigment synthesis. In this project the metabolic channeling process during the pink pigment phycoerythrobilin (PEB) was investigated. The responsible ferredoxin-dependent bilin reductases (FDBR) for PEB formation are PebA and PebB. During the pigment synthesis the intermediate molecule 15,16-dihydrobiliverdin (DHBV) is formed and transferred from PebA to PebB. While in earlier studies a metabolic channeling of DHBV was postulated, this work revealed new insights into the requirements of this protein-protein interaction. It became clear, that the most important requirement for the PebA/PebB interaction is based on the affinity to their substrate/product DHBV. The already high affinity of both enzymes to each other is enhanced in the presence of DHBV in the binding pocket of PebA which leads to a rapid transfer to the subsequent enzyme PebB. DHBV is a labile molecule and needs to be rapidly channeled in order to get correctly further reduced to PEB. Fluorescence titration experiments and transfer assays confirmed the enhancement effect of DHBV for its own transfer.
More insights became clear by creating an active fusion protein of PebA and PebB and comparing its reaction mechanism with standard FDBRs. This fusion protein was able to convert biliverdin IXα (BV IXα) to PEB similar to the PebS activity, which also can convert BV IXα via DHBV to PEB as a single enzyme. The product and intermediate of the reaction were identified via HPLC and UV-Vis spectroscopy.
The results of this work revealed that PebA and PebB interact via a proximity channeling process where the intermediate DHBV plays an important role for the interaction. It also highlights the importance of substrate channeling in the synthesis of PEB to optimize the flux of intermediates through this metabolic pathway.
Computational problems that involve dynamic data, such as physics simulations and program development environments, have been an important
subject of study in programming languages. Recent advances in self-adjusting
computation made progress towards achieving efficient incremental computation by providing algorithmic language abstractions to express computations that respond automatically to dynamic changes in their inputs. Selfadjusting programs have been shown to be efficient for a broad range of problems via an explicit programming style, where the programmer uses specific
primitives to identify, create and operate on data that can change over time.
This dissertation presents implicit self-adjusting computation, a type directed technique for translating purely functional programs into self-adjusting
programs. In this implicit approach, the programmer annotates the (toplevel) input types of the programs to be translated. Type inference finds
all other types, and a type-directed translation rewrites the source program
into an explicitly self-adjusting target program. The type system is related to
information-flow type systems and enjoys decidable type inference via constraint solving. We prove that the translation outputs well-typed self-adjusting
programs and preserves the source program’s input-output behavior, guaranteeing that translated programs respond correctly to all changes to their
data. Using a cost semantics, we also prove that the translation preserves the
asymptotic complexity of the source program.
As a second contribution, we present two techniques to facilitate the processing of large and dynamic data in self-adjusting computation. First, we
present a type system for precise dependency tracking that minimizes the
time and space for storing dependency metadata. The type system improves
the scalability of self-adjusting computation by eliminating an important assumption of prior work that can lead to recording spurious dependencies.
We present a type-directed translation algorithm that generates correct selfadjusting programs without relying on this assumption. Second, we show a
probabilistic-chunking technique to further decrease space usage by controlling the fundamental space-time tradeoff in self-adjusting computation.
We implement implicit self-adjusting computation as an extension to Standard ML with compiler and runtime support. Using the compiler, we are able
to incrementalize an interesting set of applications, including standard list
and matrix benchmarks, ray tracer, PageRank, sparse graph connectivity, and
social circle counts. Our experiments show that our compiler incrementalizes existing code with only trivial amounts of annotation, and the resulting
programs bring asymptotic improvements to large datasets from real-world
applications, leading to orders of magnitude speedups in practice.
Tables or ranked lists summarize facts about a group of entities in a concise and structured fashion. They are found in all kind of domains and easily comprehensible by humans. Some globally prominent examples of such rankings are the tallest buildings in the World, the richest people in Germany, or most powerful cars. The availability of vast amounts of tables or rankings from open domain allows different ways to explore data. Computing similarity between ranked lists, in order to find those lists where entities are presented in a similar order, carries important analytical insights. This thesis presents a novel query-driven Locality Sensitive Hashing (LSH) method, in order to efficiently find similar top-k rankings for a given input ranking. Experiments show that the proposed method provides a far better performance than inverted-index--based approaches, in particular, it is able to outperform the popular prefix-filtering method. Additionally, an LSH-based probabilistic pruning approach is proposed that optimizes the space utilization of inverted indices, while still maintaining a user-provided recall requirement for the results of the similarity search. Further, this thesis addresses the problem of automatically identifying interesting categorical attributes, in order to explore the entity-centric data by organizing them into meaningful categories. Our approach proposes novel statistical measures, beyond known concepts, like information entropy, in order to capture the distribution of data to train a classifier that can predict which categorical attribute will be perceived suitable by humans for data categorization. We further discuss how the information of useful categories can be applied in PANTHEON and PALEO, two data exploration frameworks developed in our group.
Though environmental inequality research has gained extensive interest in the United States, it has received far less attention in Europe and Germany. The main objective of this book is to extend the research on environmental inequality in Germany. This book aims to shed more light on the question of whether minorities in Germany are affected by a disproportionately high burden of environmental pollution, and to increase the general knowledge about the causal mechanisms, which contribute to the unequal distribution of environmental hazards across the population.
To improve our knowledge about environmental inequality in Germany, this book extends previous research in several ways. First, to evaluate the extent of environmental inequality, this book relies on two different data sources. On the on hand, it uses household-level survey data and self-reports about the impairment through air pollution. On the other hand, it combines aggregated census data and objective register-based measures of industrial air pollution by using geographic information systems (GIS). Consequently, this book offers the first analysis of environmental inequality on the national level that uses objective measures of air pollution in Germany. Second, to evaluate the causes of environmental inequality, this book applies a panel data analysis on the household level, thereby offering the first longitudinal analysis of selective migration processes outside the United States. Third, it compares the level of environmental inequality between German metropolitan areas and evaluates to which extent the theoretical arguments of environmental inequality can explain differing levels of environmental inequality across the country. By doing so, this book not only investigates the impact of indicators derived by the standard strand of theoretical reasoning but also includes structural characteristics of the urban space.
All studies presented in this book confirm the disproportionate exposure of minorities to environmental pollution. Minorities live in more polluted areas in Germany but also in more polluted parts of the communities, and this disadvantage is most severe in metropolitan regions. Though this book finds evidence for selective migration processes contributing to the disproportionate exposure of minorities to environmental pollution, it also stresses the importance of urban conditions. Especially cities with centrally located industrial facilities yield a high level of environmental inequality. This poses the question of whether environmental inequality might be the result of two independent processes: 1) urban infrastructure confines residential choices of minorities to the urban core, and 2) urban infrastructure facilitates centrally located industries. In combination, both processes lead to a disproportionate burden of minority households.
In recent years, enormous progress has been made in the field of Artificial Intelligence (AI). Especially the introduction of Deep Learning and end-to-end learning, the availability of large datasets and the necessary computational power in form of specialised hardware allowed researchers to build systems with previously unseen performance in areas such as computer vision, machine translation and machine gaming. In parallel, the Semantic Web and its Linked Data movement have published many interlinked RDF datasets, forming the world’s largest, decentralised and publicly available knowledge base.
Despite these scientific successes, all current systems are still narrow AI systems. Each of them is specialised to a specific task and cannot easily be adapted to all other human intelligence tasks, as would be necessary for Artificial General Intelligence (AGI). Furthermore, most of the currently developed systems are not able to learn by making use of freely available knowledge such as provided by the Semantic Web. Autonomous incorporation of new knowledge is however one of the pre-conditions for human-like problem solving.
This work provides a small step towards teaching machines such human-like reasoning on freely available knowledge from the Semantic Web. We investigate how human associations, one of the building blocks of our thinking, can be simulated with Linked Data. The two main results of these investigations are a ground truth dataset of semantic associations and a machine learning algorithm that is able to identify patterns for them in huge knowledge bases.
The ground truth dataset of semantic associations consists of DBpedia entities that are known to be strongly associated by humans. The dataset is published as RDF and can be used for future research.
The developed machine learning algorithm is an evolutionary algorithm that can learn SPARQL queries from a given SPARQL endpoint based on a given list of exemplary source-target entity pairs. The algorithm operates in an end-to-end learning fashion, extracting features in form of graph patterns without the need for human intervention. The learned patterns form a feature space adapted to the given list of examples and can be used to predict target candidates from the SPARQL endpoint for new source nodes. On our semantic association ground truth dataset, our evolutionary graph pattern learner reaches a Recall@10 of > 63 % and an MRR (& MAP) > 43 %, outperforming all baselines. With an achieved Recall@1 of > 34% it even reaches average human top response prediction performance. We also demonstrate how the graph pattern learner can be applied to other interesting areas without modification.
Fast Internet content delivery relies on two layers of caches on the request path. Firstly, content delivery networks (CDNs) seek to answer user requests before they traverse slow Internet paths. Secondly, aggregation caches in data centers seek to answer user requests before they traverse slow backend systems. The key challenge in managing these caches is the high variability of object sizes, request patterns, and retrieval latencies. Unfortunately, most existing literature focuses on caching with low (or no) variability in object sizes and ignores the intricacies of data center subsystems.
This thesis seeks to fill this gap with three contributions. First, we design a new caching system, called AdaptSize, that is robust under high object size variability. Second, we derive a method (called Flow-Offline Optimum or FOO) to predict the optimal cache hit ratio under variable object sizes. Third, we design a new caching system, called RobinHood, that exploits variances in retrieval latencies to deliver faster responses to user requests in data centers.
The techniques proposed in this thesis significantly improve the performance of CDN and data center caches. On two production traces from one of the world's largest CDN AdaptSize achieves 30-91% higher hit ratios than widely-used production systems, and 33-46% higher hit ratios than state-of-the-art research systems. Further, AdaptSize reduces the latency by more than 30% at the median, 90-percentile and 99-percentile.
We evaluate the accuracy of our FOO analysis technique on eight different production traces spanning four major Internet companies.
We find that FOO's error is at most 0.3%. Further, FOO reveals that the gap between online policies and OPT is much larger than previously thought: 27% on average, and up to 43% on web application traces.
We evaluate RobinHood with production traces from a major Internet company on a 50-server cluster. We find that RobinHood improves the 99-percentile latency by more than 50% over existing caching systems.
As load imbalances grow, RobinHood's latency improvement can be more than 2x. Further, we show that RobinHood is robust against server failures and adapts to automatic scaling of backend systems.
The results of this thesis demonstrate the power of guiding the design of practical caching policies using mathematical performance models and analysis. These models are general enough to find application in other areas of caching design and future challenges in Internet content delivery.
Nowadays, the increasing demand for ever more customizable products has emphasized the need for more flexible and fast-changing manufacturing systems. In this environment, simulation has become a strategic tool for the design, development, and implementation of such systems. Simulation represents a relatively low-cost and risk-free alternative for testing the impact and effectiveness of changes in different aspects of manufacturing systems.
Systems that deal with this kind of data for its use in decision making processes are known as Simulation-Based Decision Support Systems (SB-DSS). Although most SB-DSS provide a powerful variety of tools for the automatic and semi-automatic analysis of simulations, visual and interactive alternatives for the manual exploration of the results are still open to further development.
The work in this dissertation is focused on enhancing decision makers’ analysis capabilities by making simulation data more accessible through the incorporation of visualization and analysis techniques. To demonstrate how this goal can be achieved, two systems were developed. The first system, viPhos – standing for visualization of Phos: Greek for light –, is a system that supports lighting design in factory layout planning. viPhos combines simulation, analysis, and visualization tools and techniques to facilitate the global and local (overall factory or single workstations, respectively) interactive exploration and comparison of lighting design alternatives.
The second system, STRAD - standing for Spatio-Temporal Radar -, is a web-based systems that considers the spatio/attribute-temporal analysis of event data. Since decision making processes in manufacturing also involve the monitoring of the systems over time, STRAD enables the multilevel exploration of event data (e.g., simulated or historical registers of the status of machines or results of quality control processes).
A set of four case studies and one proof of concept prepared for both systems demonstrate the suitability of the visualization and analysis strategies adopted for supporting decision making processes in diverse application domains. The results of these case studies indicate that both, the systems as well as the techniques included in the systems can be generalized and extended to support the analysis of different tasks and scenarios.
Der Fokus der vorliegenden Arbeit liegt auf endlosfaser- und langfaserverstärkten
thermoplastischen Materialien. Hierfür wurde das „multilayered hybrid
(MLH)“ Konzept entwickelt und auf zwei Halbzeuge, den MLH-Roving und die MLHMat
angewendet. Der MLH-Roving ist ein Roving (bestehend aus Endlosfasern), der
durch thermoplastische Folien in mehrere Schichten geteilt wird. Der MLH-Roving
wird durch eine neuartige Spreizmethode mit anschließender thermischen Fixierung
und abschließender mehrfacher Faltung hergestellt. Dadurch können verschiedene
Faser-Matrix-Konfigurationen realisiert werden. Die MLH-Mat ist ein
glasmattenverstärktes thermoplastisches Material, das für hohe Fasergehalte bis 45
vol. % und verschiedene Matrixpolymere, z.B. Polypropylen (PP) und Polyamide 6
(PA6) geeignet ist. Sie zeichnet sich durch eine hohe Homogenität in der
Flächendichte und in der Faserrichtung aus. Durch dynamische Crashversuche mit
auf MLH-Roving und MLH-Mat basierenden Probekörpern wurden das
Crashverhalten und die Performance untersucht. Die Ergebnisse der Crashkörper
basierend auf langfaserverstärktem Material (MLH-Mat) und endlosfaserverstärktem
Material (MLH-Roving) waren vergleichbar. Die PA6-Typen zeigten eine bessere
Crashperformance als PP-Typen.
The present work deals with continuous fiber- and long fiber reinforced thermoplastic
materials. The concept of multilayered hybrid (MLH) structure was developed and
applied to the so-called MLH-roving and MLH-mat. The MLH-roving is a continuous
fiber roving separated evenly into several sublayers by thermoplastic films, through
the sequential processes of spreading with a newly derived equation, thermal fixing,
and folding. It was aimed to satisfy the variety of material configuration as well as the
variety in intermediate product. The MLH-mat is a glass mat reinforced thermoplastic
(GMT)-like material that is suitable for high fiber contents up to 45 vol. % and various
matrix polymers, e.g. polypropylene (PP), polyamide 6 (PA6). It showed homogeneity
in areal density, random directional fiber distribution, and reheating stability required
for molding process. On the MLH-roving and MLH-mat materials, the crash behavior
and performance were investigated by dynamic crash test. Long fiber reinforced
materials (MLH-mat) were equivalent to continuous fiber reinforced materials (MLHroving),
and PA6 grades showed higher crash performance than PP grades.