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Efficient and predictable thread synchronization mechanisms for mixed-criticality systems on shared-memory multi-processor platforms (2021)
Züpke, Alexander
Real-time operating systems for mixed-criticality systems must support different types of software, such as real-time applications and general purpose applications, and, at the same time, must provide strong spatial and temporal isolation between independent software components. Therefore, state-of-the-art real-time operating systems focus mainly on predictability and bounded worst-case behavior. However, general purpose operating systems such as Linux often feature more efficient---but less deterministic---mechanisms that significantly improve the average execution time. This thesis addresses the combination of the two contradicting requirements and shows thread synchronization mechanisms with efficient average-case behavior, but without sacrificing predictability and worst-case behavior. This thesis explores and evaluates the design space of fast paths in the implementation of typical blocking synchronization mechanisms, such as mutexes, condition variables, counting semaphores, barriers, or message queues. The key technique here is to avoid unnecessary system calls, as system calls have high costs compared to other processor operations available in user space, such as low-level atomic synchronization primitives. In particular, the thesis explores futexes, the state-of-the-art design for blocking synchronization mechanisms in Linux that handles the uncontended case of thread synchronization by using atomic operations in user space and calls into the kernel only to suspend and wake up threads. The thesis also proposes non-preemptive busy-waiting monitors that use an efficient priority ceiling mechanism to prevent the lock holder preemption problem without using system calls, and according low-level kernel primitives to construct efficient wait and notify operations. The evaluation shows that the presented approaches improve the average performance comparable to state-of-the-art approaches in Linux. At the same time, a worst-case timing analysis shows that the approaches only need constant or bounded temporal overheads at the operating system kernel level. Exploiting these fast paths is a worthwhile approach when designing systems that not only have to fulfill real-time requirements, but also best-effort workloads.
Method development for the quantification of pharmaceuticals in aqueous environmental matrices (2021)
Boulard, Lise
As a consequence of the world population increase and the resulting water scarcity, water quality is the object of growing attention. In that context, organic anthropogenic molecules — often defined as micropollutants— represent a threat for water resources. Among them, pharmaceuticals are the object of particular concerns due to their permanent discharge, their increasing consumption and their effect-based structures. Pharmaceuticals are mainly introduced in the environment via wastewater treatment plants (WWTPs), along with their metabolites and the on-site formed transformation products (TPs). Once in the aquatic environment, they partition between the different environmental compartments in particular the aqueous phase, suspended particulate matter(SPM) and biota. In the last decades, pharmaceuticals have been widely investigated in the water phase. However, extreme polar pharmaceuticals have rarely been monitored due to the lack of robust analytical methods. Moreover, metabolites and TPs have seldom been included in routine analysis methods although their environmental relevance is proven. Furthermore, pharmaceuticals have been only sporadically investigated in SPM and biota and adequate multi-residue methods are lacking to obtain comprehensive results about their occurrence in these matrices. This thesis endeavors to cover these gaps of knowledge by the development of generic multi-residue methods for pharmaceuticals determination in the water phase, SPM and biota and to evaluate the occurrence and partition of pharmaceuticals into these compartments. For a complete overview, a particular focus was laid on extreme polar pharmaceuticals, pharmaceutical metabolites and TPs. In total, three innovative multi-residue methods were developed, they include analytes covering a broad range of physico-chemical properties. First, a reliable multi-residue method was developed for the analysis of extreme polar pharmaceuticals, metabolites and TPs dissolved in water. The selected analytes covered a significant range of elevated polarity and the method would be easily expendable to further analytes. This versatility could be achieved by the utilization of freeze-drying as sample preparation and zwitterionic hydrophilic interaction liquid chromatography (HILIC) in gradient elution mode. The suitability of HILIC chromatography to simultaneously quantify a large range of micropollutants in aqueous environmental samples was thoroughly studied. Several limitations were pointed out: a very complex and time-consuming method development, a very high sensitivity with regards to modification of the acetonitrile to water ratio in the eluent or the diluent and high positive matrix effects for certain analytes. However, these limitations can be overcome by the utilization of a precise protocol and appropriate labeled internal standards. They are overmatched by the benefits of HILIC which permits the chromatographic separation of extreme polar micropollutants. Investigation of environmental samples showed elevated concentrations of the analytes in the water phase. In particular, gabapentin, metformin, guanylurea and oxypurinol were measured at concentrations in the µg/L range in surface water. Subsequently, a reliable multi-residue method was established for the determination of 57 pharmaceuticals, 47 metabolites and TPs sorbed to SPM down to the low ng/g range. This method was conceived to cover a large range of polarity in particular with the inclusion of extreme polar pharmaceuticals. The extraction procedure was based on pressurized liquid extraction (PLE) followed by a clean-up via solvent exchange and detection via direct injection-reversed-phase LC-MS/MS and freeze-drying HILIC-MS/MS. Pharmaceutical sorption was examined using laboratory experiments. Derived distribution coefficients Kd varied by five orders of magnitude among the analytes and confirmed a high sorption potential for positively charged and nonpolar pharmaceuticals. The occurrence of pharmaceuticals in German rivers SPM was evaluated by the investigation of annual composite SPM samples taken at four sites at the river Rhine and one site at the river Saar between the years 2005 and 2015. It revealed the ubiquitous presence of pharmaceuticals sorbed to SPM in these rivers. In particular, positively charged analytes, even very polar and nonpolar pharmaceuticals showed appreciable concentrations. For many pharmaceuticals, a distinct correlation was observed between the annual quantities consumed in Germany and the concentrations measured in SPM. Studies of composite SPM spatial distribution permitted to get hints about specific industrial discharge by comparing the pollution pattern along the river. For the first time, these results showed the potential of SPM for the monitoring of positively charged and nonpolar pharmaceuticals in surface water. Finally, a reliable and generic multi residue method was developed to investigate 35 pharmaceuticals and 28 metabolites and TPs in fish plasma, fish liver and fish fillet. For this matrix, it was very challenging to develop an adequate clean-up allowing for the sufficient separation of the matrix disturbances from the analytes. In the final method, fish tissue extraction was performed by cell disruption followed by a non-discriminating clean-up based on silica gel solid-phase extraction(SPE) and restrictive access media (RAM) chromatography. Application of the developed method to the measurement of bream and carp tissues from German rivers revealed that even polar micropollutants such as pharmaceuticals are ubiquitously present in fish tissues. In total, 17 analytes were detected for the first time in fish tissues, including 10 metabolites/TPs. The importance of monitoring metabolites and TPs in fish tissues was confirmed with their detection at similar concentrations as their parents. Liver and fillet were shown to be appropriate for the monitoring of pharmaceuticals in fish, whereas plasma is more inconvenient due to very low concentrations and collection difficulties. Elevated concentrations of certain metabolites suggest possible formation of human metabolites in fish. Measured concentrations indicate a low bioaccumulation potential for pharmaceuticals in fish tissues.
Effects of damming and reservoir operation on hydrodynamics and thermal regimes in large cascade reservoirs of the Yangtze River, China (2021)
Long, Lianghong
Rivers play an important role in the global water cycle, support biodiversity and ecological integrity. However, river flow and thermal regimes are heavily altered in dammed rivers. These impacts are being exacerbated and become more apparent in rivers fragmented by multiple dams. Recent studies mainly focused on evaluating the cumulative impact of cascade reservoirs on flow or thermal regimes, but the role of upstream reservoirs in shaping the hydrology and hydrodynamics of downstream reservoirs remains poorly understood. To improve the understanding of the hydrodynamics in cascade reservoirs, long-term observational data are used in combination with numerical modeling to investigate the changes in flow and thermal regime in three cascade reservoirs at the upper reach of the Yangtze River. The three studied reservoirs are Xiluodu (XLD), Xiangjiaba (XJB) and Three Gorges Reservoir (TGR). In addition, the effects of single reservoir operation (at seasonal/daily time scale) on hydrodynamics are examined in a large tributary of TGR. The results show that the inflow of TGR has been substantially altered by the two upstream reservoirs with a higher discharge in spring and winter and a reduced peak flow in summer. XJB had no obvious contribution to the variations in inflow of TGR. The seasonal water temperature of TGR was also widely affected by the upstream two reservoirs, i.e., an increase in winter and decrease in spring, associated with a delay in water temperature rise and fall. These effects will probably be intensified in the coming years due to the construction of new reservoirs. The study also underlines the importance of reservoir operation in shaping the hydrodynamics of TGR. The seasonal dynamics of density currents in a tributary bay of TGR are closely related to seasonal reservoir operations. In addition, high-frequency water level fluctuations and flow velocity variations were observed in response to periodic tributary bay oscillations, which are driven by the diurnal discharge variations caused by the operation of TGR. As another consequence of operation of cascade reservoirs, the changes in TGR inflow weakened spring thermal stratification and caused warming in spring, autumn and winter. In response to this change, the intrusions from TGR occurred more frequently as overflow and earlier in spring, which caused a sharp reduction in biomass and frequency of phytoplankton blooms in tributary bays of TGR. This study suggests that high-frequency bay oscillations can potentially be used as an efficient management strategy for controlling algal blooms, which can be included in future multi-objective ecological conservation strategies.
Handling Inconsistency in Business Rule Bases (2021)
Corea, Carl
Within the field of Business Process Management, business rules are commonly used to model company decision logic and govern allowed company behavior. An exemplary business rule in the financial sector could be for example: ”A customer with a mental condition is not creditworthy”. Business rules are usually created and maintained collaboratively and over time. In this setting, modelling errors can occur frequently. A challenging problem in this context is that of inconsistency, i.e., contradictory rules which cannot hold at the same time. For instance, regarding the exemplary rule above, an inconsistency would arise if a (second) modeller entered an additional rule: ”A customer with a mental condition is always creditworthy”, as the two rules cannot hold at the same time. In this thesis, we investigate how to handle such inconsistencies in business rule bases. In particular, we develop methods and techniques for the detection, analysis and resolution of inconsistencies in business rule bases
Junges Forschen der Universität in Koblenz (2020)
In dieser wiederkehrenden Zeitschriftenreihe wollen wir die Arbeit junger Wissenschaftlerinnen und Wissenschaftler an der Universität Koblenz-Landau kommunizieren und Studierenden Austausch- und Publikationsmöglichkeiten für den wissenschaftlichen Werdegang eröffnen. In dieser Ausgabe: Exner, Maik. Bedeutung und Musik: Konstitutionsprozesse von musikkulturellen Bedeutungen und Bedeutsamkeiten in interaktionaler, biographischer und historischer Perspektive. Henne, Arthur. Analysis of the Transition from Traditional Closed Innovation Systems to Open Innovation. von Schönebeck, Sandra. #TrauDichDeutschland: Die Sprache der AfD im multimodalen (Online-) Bundestagswahlkampf 2017 – Eine Untersuchung sprachlicher und visueller Strategien sowie der Reaktionen potenzieller Wählerinnen und Wähler. Michaelis, Kent. Das “Templerhaus” in Boppard: Kunsthistorische Untersuchung eines spätromanischen Baudenkmals. Koops, Sarah M. J.. Lässt sich eine Obergrenze für die Aufnahme von Flüchtlingen durch Nationalstaaten ethisch rechtfertigen?. Rosemann, Raphaela S.. Masquerade and Disguise in the Works of Eliza Haywood.
What impedes Consumers’ Delivery Drone Service Adoption? (2020)
Knobloch, Marius ; Schaarschmidt, Mario
Despite widespread plans of big companies like Amazon and Google to develop unmanned delivery drones, scholarly research in this field is scarce, especially in the information systems field. From technical and legal perspectives, drone delivery in last-mile scenarios is in a quite mature state. However, estimates of user acceptance are varying between high skepticism and exaggerated optimism. This research follows a mixed method approach consisting both qualitative and quantitative research, to identify and test determinants of consumer delivery drone service adoption. The qualitative part rests on ten interviews among average consumers, who use delivery services on a regular basis. Insights gained from the qualitative part were used to develop an online survey and to assess the influence of associated risks on adoption intentions. The quantitative results show that especially financial and physical risks impede drone delivery service adoption. Delivery companies who are currently thinking about providing a delivery drone service may find these results useful when evaluating usage behaviors in the future market for delivery drones.
GeKOS - Gemeinsam entdecken Kinder ihren Ort mit Studierenden, 4. Zwischenbericht (2020)
de Boer, Heike ; Braß, Benjamin ; Falmann, Peter
Dieses Dokument umfasst den dritten Zwischenbericht zum Projekt GeKOS – Gemeinsam entdecken Kinder ihren Ort mit Studierenden, der im Oktober 2019 an die Schöpflin-Stiftung übergeben wurde. Das Projekt GeKOS wird vom Ministerium für Wissenschaft, Weiterbildung und Kultur des Landes Rheinland-Pfalz im Rahmen der Programmbudgets Hochschulpakt III sowie von der Schöpflin-Stiftung mit Sitz in Lörrach von 2016 bis 2020 finanziell gefördert. Zudem gewährte das rheinland-pfälzische Ministerium für Integration, Familie, Kinder, Jugend und Frauen im Jahr 2015 eine Anschubfinanzierung.
Mitteilungsblatt der Universität Koblenz-Landau Nr. 1/2020 (2020)
Satzung für den steuerbegünstigten Betrieb gewerblicher Art: Kinderbetreuungseinrichtungen Redaktionelle Korrektur betreffend die Dritte Ordnung zur Änderung der Ordnung für die Prüfung im Bachelorstudiengang und im Masterstudiengang Erziehungswissenschaft an der Universität Koblenz-Landau, Campus Landau Ordnung zur Änderung der Beitragsordnung des Studierendenwerks Koblenz Siebte Ordnung zur Änderung der Prüfungsordnung für den Bachelorstudiengang und den Masterstudiengang „Sozial- und Kommunikationswissenschaften“ des Fachbereichs 6: Kultur- und Sozialwissenschaften an der Universität Koblenz-Landau Sechsundzwanzigste Ordnung zur Änderung der Prüfungsordnung für die Prüfung im lehramtsbezogenen Bachelorstudiengang an der Universität Koblenz-Landau
Mitteilungsblatt der Universität Koblenz-Landau Nr. 2/2020 (2020)
Erste Ordnung zur Änderung der Promotionsordnung des Fachbereiches 1: Bildungswissenschaften der Universität Koblenz–Landau Siebte Satzung zur Änderung der Satzung der Universität Koblenz-Landau über das Auswahlverfahren in zulassungsbeschränkten Studiengängen
Technologiefrüherkennung im Umfeld der Railways Diagnostic and Monitoring Technologies (2020)
Ory, Leon
This thesis deals with the approach, the structure and the variety of methods in the field of technology forecasting. Furthermore insights into the environment of Railways Diagnostics and Monitoring Technologies (RDMT), their technology management and industryspecific requirements for technology forecasting (especially in the area SMEs) are given. Combining those a recommendation for practical use of research results in companies of this size and industry is developed. In order to initiate the previously mentioned research elements a literature research was operated in the field of innovation management and the railway environment. In addition, an interview with an expert of a medium-sized technology manufacturer of RDMT industry was performed. The most important finding was that a single method cannot fulfill the requirements on its own, thus a combination of methods and organizational forms is necessary to achieve an effective technology forecasting.
Analyse zur Schätzung von Unfallkosten im Schienenverkehr in Deutschland (2020)
Gilles, Oliver
Accidents annually cause high economic damages for concerned persons, companies and the state. To determine the exact costs of a damage is a challenge. Scientific studies differ from each other because of different models of calculation. Due to the fact of a low number of accidents concerning rail transport there are not many studies about how to calculate the costs an accident causes. The aim of this thesis is to give an overview about methods when dealing with these costs and to point out occurring difficulties. Generally, costs of accident can be divided in two categories. One category deals with personal injuries whereas the other focuses on material damages. Personal injuries contain material and immaterial damages. This leads to difficulties in calculation. The main aspect when dealing with personal damages is the loss of manpower, the costs of medical supply and the costs of the recovery of the legal situation. Currently there is no model of how to calculate personal damages concerning rail transport in Germany. The “Bundesamt für Straßenverkehr” developed an extensive model for calculations of costs of accident concerning traffic. It turned out that the death of people has costs round about 1.1 million euro. Severely and slightly injured people cause damages about 106,000 euro and 5,000 euro. This thesis declares that the model is important regarding different aspects of rail transport and that it is based on statistically collected key performance indicators. Furthermore, some approaches, which analyse the value of life, are mentioned. There are large derivations between them. To make a calculation of material damage the current value of the object must be respected. When dealing with the limitation of material damages the focus is on damages concerning infrastructure. In addition, railway infrastructure can be mentioned. With the help of the “Kostenkennwertekatalog” of Deutsche Bahn AG acquisitions costs for certain components of infrastructure can be determined. As a result, they offer a basis for calculating damages.
Evaluation der Einsatz- und Forschungsgebiete von Predictive Maintenance anhand einer qualitativen Videoanalyse (2020)
Wick, Natalie
The maintenance strategy “predictive maintenance”, which is characterized by predicting the failure behavior of technical units based on modern sensor technology, plays a key role in smart factories against the background of an industry 4.0. This paper contains an evaluation of the current state of research on this strategy and gives an overview of the areas of application to date. With the aid of a qualitative video analysis, the implementation in the industries and company divisions involved and the type of goods monitored are examined. The analyzed video clips were uploaded to YouTube for example for marketing purposes by various companies with different perspectives on predictive maintenance. The video analysis was realized by applying a previously defined coding plan to the video material. The results show a predominant application in the manufacturing industry, in which predictive maintenance is used to monitor plants and machines. In addition, the strategy is also mainly applied to means of transport used for freight and passenger transport in various infrastructures. As a result of the video analysis, the currently high need for explanation of predictive maintenance becomes visible. By looking at these explanations, one also learns something about the special features that distinguish it from other maintenance strategies.
Grundlagen der Systemtheorie zur Anwendung transdisziplinärer Verfahren der Technikfolgenabschätzung (2020)
Kowalczyk, Michaela
The technological progress is highly responsible for how people live their everyday life. Technical innovations provide new opportunities to re-design all areas of life and because of that the society has to adjust to these changes permanently. These days, due to the fact that there is a changeover from analog into digital processes, this circumstance is highly relevant. However, it is not always clear whether a technological innovation just entails chances or involves risks, too. The research field of technology assessment pursues the goal to examine the influence of technological innovations on the society. For this purpose, unpredictable consequences of a technology need to be anticipated in advance to provide the opportunity of earlier reactions. The core of this thesis a discussion about a project based approach of technology assessment. Additionally, it is being investigated whether and how systems theory approaches can be used to improve predictions in the research area of technology assessment. Therefore, the question of how reliable forecasts are in this kind of context will be answered. Moreover, there is an investigation if an added-value can be created through performing system thinking. As a methodical approach a literature review has been performed. Furthermore, experts were questioned in an interview and by e-mail to gain an insight in the practical work of technology assessment. Based on the elaborated project structure, for each part of the project was examined if significant results can be maintained through the sophisticated use of principles of the systems theory. The analysis of this paper has shown that the results of a technology assessment may have more reliable forecast value in comparison to an investigation without proper consideration of system thinking. Especially, the understanding of a system during the phase of conception of a project can be crucial for the positive outcome for the results of technology assessment. This master thesis represents the theoretical point of view regarding topics technology assessment and systems theory. An application test for the validation of the results in the practical work of technology assessment is recommended.
Railway Safety Research – A Cross-Disciplinary Literature Review (2020)
Schneider, André
Railway safety is a topic which gains the public attention only if major railway accidents happen. This is because railway is considered as a safe mode of travel by the public. However, to ensure the safety of the railway system railway companies as well as universities conduct a broad spectrum of research. An overview of this research has not yet been provided in the scholarly literature. Therefore, this thesis follows two objectives. First an overview and ranking of railway safety research universities should be provided. Second, based on these universities, it should be identified which are the most relevant and influential research topics. The ranking is based on the research method “literature review” which forms the methodical basis for this thesis. To evaluate the universities based on a measurable and objective criterion, the number of citations of the researchers from each university is gathered. As a result, the University of Leuven for the civil engineering, Milan Politechnico for mechanical enginering and the University of Loughborough for electrical engineering are identified as the leading university in their field of railway safety research. The top universities for each discipline are distributed all over Europe, North America and Asia. However, a clear focus on the US and British universities is observed. For identification of the most relevant and influential topics the keywords from the publications which are considered in the ranking procedure are analyzed. Focus areas among these keywords are revealed by calculating the count of each keyword. High-speed trains as well as maintenance are recognized as the highly relevant topics in both civil and mechanical engineering. Furthermore, the topic of railway dynamics for mechanical engineering and noise and vibration for civil engineering are identified as the leading topics in the respective discipline. Achieving both research goals required exploratory approaches. Therefore, this thesis leaves open space for future research to deepen the individual topics which are approached in each section. A validation of the results through experts interviews as well as a deepening of the analysis through increasing the number of analyzed universities as well as applying statistical methods is recommended.
Potenziale der Digitalisierung für kleine und mittlere Unternehmen (2020)
Hohl, Fabienne
Digital Transformation is a main enabler for technological change in today’s society and corporate structures. Companies of all sizes have to face up the change. The com-plexity of the innovations is constantly growing. More and more information and knowledge are needed to build a basis for renewal. Different capabilities, such as highly qualified employees, material resources and the correct handling with these information, constitute the background for the advancement. Compared to large companies, small and medium sized companies (SMEs) are struggling more with these circum-stances. This leaves potential capabilities to optimize daily routines unused. Challenges here are different internal and external barriers. Examples for that are the lack of IT expertise and innovation culture. Hence it is very important, to show SMEs the advantages of the innovation process within the scope of digital transformation. Cost savings, improvement of IT infrastructure or optimization of their business processes, are drivers that should be adopted in the awareness of SMEs. Recommendations for action are needed, also with the support of information management. This includes information management, strategic management for external an internal information and the selection of an appropriate IT infrastructure. However dynamic management skills and sufficient IT expertise also complement the digitization process. This becomes clear from the literature analysis following the principles of Webster and Watson (2002). The Concept mapping and the concept matrix serves to support the process. They are presenting the key words and showing the most important works of the bachelor thesis. The argumentation of the bachelor thesis based on this.
Model-based privacy by design (2020)
Ahmadian, Amirshayan
Nowadays, almost any IT system involves personal data processing. In such systems, many privacy risks arise when privacy concerns are not properly addressed from the early phases of the system design. The General Data Protection Regulation (GDPR) prescribes the Privacy by Design (PbD) principle. As its core, PbD obliges protecting personal data from the onset of the system development, by effectively integrating appropriate privacy controls into the design. To operationalize the concept of PbD, a set of challenges emerges: First, we need a basis to define privacy concerns. Without such a basis, we are not able to verify whether personal data processing is authorized. Second, we need to identify where precisely in a system, the controls have to be applied. This calls for system analysis concerning privacy concerns. Third, with a view to selecting and integrating appropriate controls, based on the results of system analysis, a mechanism to identify the privacy risks is required. Mitigating privacy risks is at the core of the PbD principle. Fourth, choosing and integrating appropriate controls into a system are complex tasks that besides risks, have to consider potential interrelations among privacy controls and the costs of the controls. This thesis introduces a model-based privacy by design methodology to handle the above challenges. Our methodology relies on a precise definition of privacy concerns and comprises three sub-methodologies: model-based privacy analysis, modelbased privacy impact assessment and privacy-enhanced system design modeling. First, we introduce a definition of privacy preferences, which provides a basis to specify privacy concerns and to verify whether personal data processing is authorized. Second, we present a model-based methodology to analyze a system model. The results of this analysis denote a set of privacy design violations. Third, taking into account the results of privacy analysis, we introduce a model-based privacy impact assessment methodology to identify concrete privacy risks in a system model. Fourth, concerning the risks, and taking into account the interrelations and the costs of the controls, we propose a methodology to select appropriate controls and integrate them into a system design. Using various practical case studies, we evaluate our concepts, showing a promising outlook on the applicability of our methodology in real-world settings.
Environmental processes transforming inorganic nanoparticles: implications on aquatic invertebrates (2020)
Lüderwald, Simon
Engineered inorganic nanoparticles (EINPs) are produced and utilized on a large scale and will end up in surface waters. Once in surface waters, EINPs are subjected to transformations induced by environmental processes altering the particles’ fate and inherent toxicity. UV irradiation of photoactive EINPs is defined as one effect-inducing pathway, leading to the formation of reactive oxygen species (ROS), increasing EINP toxicity by exerting oxidative stress in aquatic life. Simultaneously, UV irradiation of photoactive EINP alters the toxicity of co-occurring micropollutants (e.g. pesticides) by affecting their degradation. The presence of natural organic matter (NOM) reduces the agglomeration and sedimentation of EINPs, extending the exposure of pelagic species, while delaying the exposure of benthic species living in and on the sediment, which is suggested as final sink for EINPs. However, the joint impact of NOM and UV irradiation on EINP-induced toxicity, but also EINP-induced degradation of micropollutants, and the resulting risk for aquatic biota, is poorly understood. Although potential effects of EINPs on benthic species are increasingly investigated, the importance of exposure pathways (waterborne or dietary) is unclear, along with the reciprocal pathway of EINPs, i.e. the transport back from aquatic to terrestrial ecosystems. Therefore, this thesis investigates: (i) how the presence of NOM affects the UV-induced toxicity of the model EINP titanium dioxide (nTiO2) on the pelagic organism Daphnia magna, (ii) to which extent UV irradiation of nTiO2 in the presence and absence of NOM modifies the toxicity of six selected pesticides in D. magna, (iii) potential exposure pathway dependent effects of nTiO2 and silver (nAg) EINPs on the benthic organism Gammarus fossarum, and (iv) the transport of nTiO2 and gold EINPs (nAu) via the merolimnic aquatic insect Chaetopteryx villosa back to terrestrial ecosystems. nTiO2 toxicity in D. magna increased up to 280-fold in the presence of UV light, and was mitigated by NOM up to 12-fold. Depending on the pesticide, UV irradiation of nTiO2 reduced but also enhanced pesticide toxicity, by (i) more efficient pesticide degradation, and presumably (ii) formation of toxic by-products, respectively. Likewise, NOM reduced and increased pesticide toxicity, induced by (i) protection of D. magna against locally acting ROS, and (ii) mitigation of pesticide degradation, respectively. Gammarus’ energy assimilation was significantly affected by both EINPs, however, with distinct variation in direction and pathway dependence between nTiO2 and nAg. EINP presence delayed C. villosa emergence by up to 30 days, and revealed up to 40% reduced lipid reserves, while the organisms carried substantial amounts of nAu (~1.5 ng/mg), and nTiO2 (up to 2.7 ng/mg). This thesis shows, that moving test conditions of EINPs towards a more field-relevant approach, meaningfully modifies the risk of EINPs for aquatic organisms. Thereby, more efforts need to be made to understand the relative importance of EINP exposure pathways, especially since a transferability between different types of EINPs may not be given. When considering typically applied risk assessment factors, adverse effects on aquatic systems might already be expected at currently predicted environmental EINP concentrations in the low ng-µg/L range.
Deep learning techniques applied to constituency parsing of German (2020)
Rajasekaran, Kandhasamy
Constituent parsing attempts to extract syntactic structure from a sentence. These parsing systems are helpful in many NLP applications such as grammar checking, question answering, and information extraction. This thesis work is about implementing a constituent parser for German language using neural networks. Over the past, recurrent neural networks have been used in building a parser and also many NLP applications. In this, self-attention neural network modules are used intensively to understand sentences effectively. With multilayered self-attention networks, constituent parsing achieves 93.68% F1 score. This is improved even further by using both character and word embeddings as a representation of the input. An F1 score of 94.10% was the best achieved by constituent parser using only the dataset provided. With the help of external datasets such as German Wikipedia, pre-trained ELMo models are used along with self-attention networks achieving 95.87% F1 score.
Study on Data Placement Strategies in Distributed RDF Stores (2020)
Janke, Daniel
The distributed setting of RDF stores in the cloud poses many challenges. One such challenge is how the data placement on the compute nodes can be optimized to improve the query performance. To address this challenge, several evaluations in the literature have investigated the effects of existing data placement strategies on the query performance. A common drawback in theses evaluations is that it is unclear whether the observed behaviors were caused by the data placement strategies (if different RDF stores were evaluated as a whole) or reflect the behavior in distributed RDF stores (if cloud processing frameworks like Hadoop MapReduce are used for the evaluation). To overcome these limitations, this thesis develops a novel benchmarking methodology for data placement strategies that uses a data-placement-strategy-independent distributed RDF store to analyze the effect of the data placement strategies on query performance. With this evaluation methodology the frequently used data placement strategies have been evaluated. This evaluation challenged the commonly held belief that data placement strategies that emphasize local computation, such as minimal edge-cut cover, lead to faster query executions. The results indicate that queries with a high workload may be executed faster on hash-based data placement strategies than on, e.g., minimal edge-cut covers. The analysis of the additional measurements indicates that vertical parallelization (i.e., a well-distributed workload) may be more important than horizontal containment (i.e., minimal data transport) for efficient query processing. Moreover, to find a data placement strategy with a high vertical parallelization, the thesis tests the hypothesis that collocating small connected triple sets on the same compute node while balancing the amount of triples stored on the different compute nodes leads to a high vertical parallelization. Specifically, the thesis proposes two such data placement strategies. The first strategy called overpartitioned minimal edge-cut cover was found in the literature and the second strategy is the newly developed molecule hash cover. The evaluation revealed a balanced query workload and a high horizontal containment, which lead to a high vertical parallelization. As a result these strategies showed a better query performance than the frequently used data placement strategies.
Analysis of medical images using deep learning (2020)
Utegulov, Almat
Since the invention of U-net architecture in 2015, convolutional networks based on its encoder-decoder approach significantly improved results in image analysis challenges. It has been proven that such architectures can also be successfully applied in different domains by winning numerous championships in recent years. Also, the transfer learning technique created an opportunity to push state-of-the-art benchmarks to a higher level. Using this approach is beneficial for the medical domain, as collecting datasets is generally a difficult and expensive process. In this thesis, we address the task of semantic segmentation with Deep Learning and make three main contributions and release experimental results that have practical value for medical imaging. First, we evaluate the performance of four neural network architectures on the dataset of the cervical spine MRI scans. Second, we use transfer learning from models trained on the Imagenet dataset and compare it to randomly initialized networks. Third, we evaluate models trained on the bias field corrected and raw MRI data. All code to reproduce results is publicly available online.
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