Refine
Year of publication
- 2019 (45) (remove)
Document Type
- Master's Thesis (20)
- Doctoral Thesis (15)
- Bachelor Thesis (8)
- Habilitation (1)
- Part of Periodical (1)
Language
- English (45) (remove)
Keywords
- Internet of Things (2)
- 2019 European Parliament Election (1)
- Agrarlandschaft (1)
- Association Rules (1)
- BPM (1)
- Belief change, concept contraction, EL (1)
- Biodiversität (1)
- Business Process Management Recommender Systems Survey (1)
- Business Process Modeling (1)
- Calcium (1)
- Challenges (1)
- Cold Chain (1)
- Densimetric Measurement (1)
- Dichtemessung (1)
- Dredging (1)
- ECSA (1)
- Ebullition (1)
- Effectiveness (1)
- Elektronenmikroskopie (1)
- Empfehlungssystem (1)
- Entity Component System Architecture (1)
- Food Transportation System (1)
- Foodstuff (1)
- Freeze Coring (1)
- GRAF1 (1)
- Gas storage capacity (1)
- Gefrierkernverfahren (1)
- Handsfree editing (1)
- Human resources management (1)
- International organization (1)
- Kryo (1)
- Lake Kinneret (1)
- Maschinelles Lernen (1)
- Minimalschnitt (1)
- Nanoröhren (1)
- Nassbaggerung (1)
- Nützlinge (1)
- OPD-SHRM (1)
- Oligomer (1)
- Parteienkommunikation (1)
- Pestizid (1)
- Political Communication (1)
- Probabilistic finite automata (1)
- Proteinstrukturanalyse (1)
- Recommender System (1)
- Recommender Systems, Business Process Modeling, Literature Review (1)
- Reservoir Sedimentation (1)
- Schädlingskontrolle (1)
- Sediment (1)
- Solutions (1)
- Stauseeverlandung (1)
- Sustainability (1)
- Wahlen zum europäischen Parlament (EU-Wahlen) (1)
- Weinbau (1)
- agriculture (1)
- beneficial insects (1)
- biocide (1)
- biodiversity (1)
- chironomids (1)
- decision support tool (1)
- ecotoxicity (1)
- environmental risk assessment (1)
- evolution (1)
- fungus resistant grapevine (1)
- groundwater remediation (1)
- leap motion (1)
- long-living systems (1)
- machine learning (1)
- minimal pruning (1)
- model-based (1)
- mosquito control (1)
- non-target effects (1)
- pelzresistente Rebsorten (1)
- periphyton (1)
- pest control (1)
- pesticide (1)
- punishment goals (1)
- regulation (1)
- risk assessment (1)
- security (1)
- software engineering (1)
- student misbehavior (1)
- tracking (1)
- uptake (1)
- virtual reality (1)
- viticulture (1)
Institute
- Institut für Management (8)
- Institut für Wirtschafts- und Verwaltungsinformatik (8)
- Institut für Computervisualistik (7)
- Institute for Web Science and Technologies (7)
- Fachbereich 7 (4)
- Fachbereich 8 (2)
- Institut für Integrierte Naturwissenschaften, Abt. Biologie (2)
- Institut für Softwaretechnik (2)
- Institut für Umweltwissenschaften (2)
- Fachbereich 4 (1)
Sediment transport contributes to the movement of inorganic and organic material in rivers. The construction of a dam interrupts the continuity of this sediment transport through rivers, causing sediments to accumulate within the reservoir. Reservoirs can also act as carbon sinks and methane can be released when organic matter in the sediment is degraded under anoxic conditions. Reservoir sedimentation poses a great threat to the sustainability of reservoirs worldwide, and can emit the potent greenhouse gas methane into the atmosphere. Sediment management measures to rehabilitate silted reservoirs are required to achieve both better water quantity and quality, as well as to mitigate greenhouse gas emissions.
This thesis aims at the improvement of sediment sampling techniques to characterize sediment deposits as a basis for accurate and efficient water jet dredging and to monitor the dredging efficiency by measuring the sediment concentration. To achieve this, we investigated freeze coring as a method to sample (gas-bearing) sediment in situ. The freeze cores from three reservoirs obtained were scanned using a non-destructive X-Ray CT scan technique. This allows the determination of sediment stratification and character-ization of gas bubbles to quantify methane emissions and serve as a basis for the identi-fication of specific (i.e. contaminated) sediment layers to be dredged. The results demon-strate the capability of freeze coring as a method for the characterization of (gas-bearing) sediment and overcomes certain limitations of commonly used gravity cores. Even though the core’s structure showed coring disturbances related to the freezing process, the general core integrity seems to not have been disturbed. For dredging purposes, we analyzed the impact pressure distribution and spray pattern of submerged cavitating wa-ter jets and determined the effects of impinging distances and angles, pump pressures and spray angles. We used an adapted Pressure Measurement Sensing technique to enhance the spatial distribution, which proved to be a comparatively easy-to-use meas-urement method for an improved understanding of the governing factors on the erosional capacity of cavitating water jets. Based on this data, the multiple linear regression model can be used to predict the impact pressure distribution of those water jets to achieve higher dredging accuracy and efficiency. To determine the dredging operational efficien-cy, we developed a semi-continuous automated measurement device to measure the sediment concentration of the slurry. This simple and robust device has lower costs, compared to traditional and surrogate sediment concentration measurement technolo-gies, and can be monitored and controlled remotely under a wide range of concentrations and grain-sizes, unaffected by entrained gas bubbles
Commonsense reasoning can be seen as a process of identifying dependencies amongst events and actions. Understanding the circumstances surrounding these events requires background knowledge with sufficient breadth to cover a wide variety of domains. In the recent decades, there has been a lot of work in extracting commonsense knowledge, a number of these projects provide their collected data as semantic networks such as ConceptNet and CausalNet. In this thesis, we attempt to undertake the Choice Of Plausible Alternatives (COPA) challenge, a problem set with 1000 questions written in multiple-choice format with a premise and two alternative choices for each question. Our approach differs from previous work by using shortest paths between concepts in a causal graph with the edge weight as causality metric. We use CausalNet as primary network and implement a few design choices to explore the strengths and drawbacks of this approach, and propose an extension using ConceptNet by leveraging its commonsense knowledge base.
While the existing literature on cooperative R&D projects between firms and public research institutes (PRI) has made valuable contributions by examining various factors and their influence on different outcome measures, there has been no investigation of cooperative R&D project success between firms and PRI from a product competitive advantage perspective. However, insights into the development of a meaningful and superior product (i.e., product competitive advantage) are particularly important in the context of cooperative R&D projects between PRI and (mainly small and medium-sized) firms in the biotechnology industry in response to increasing competition to raise capital funds necessary for survival.
The objectives of this thesis are: (1) to elaborate the theoretical foundations which explain the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, (2) to identify and empirically evaluate the determining factors for achieving a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI, and (3) to show how cooperative R&D projects between biotechnology firms and PRI should be designed and executed to support the achievement of a product competitive advantage.
To accomplish these objectives, a model of determinants of product competitive advantage in cooperative R&D projects between biotechnology firms and PRI is developed by drawing from the theoretical foundations of resource-based theory and information-processing theory. The model is evaluated using data from 517 questionnaires on cooperative R&D projects between at least one biotechnology firm and one PRI. The data are analyzed using variance-based structural equation modeling (i.e., PLS-SEM) in order to conduct hypotheses testing. The evaluation of the empirical data includes an additional mediation analysis and the comparison of effects in subsamples.
The results demonstrate the importance of available resources and skills, as well as the proficient execution of marketing-related and technical activities for the achievement of a product competitive advantage in cooperative R&D projects between biotechnology firms and PRI. By identifying project-related and process-related factors affecting product competitive advantage and empirically testing their relationships, the research findings should be valuable for both researchers and practitioners. After discussing contributions and implications for research and practice, the present thesis concludes with limitations and avenues for future research.
Deformable Snow Rendering
(2019)
Accurate snow simulation is key to capture snow's iconic visuals. Intricate
methods exist that attempt to grasp snow behaviour in a holistic manner. Computational complexity prevents them from reaching real-time performance. This thesis presents three techniques making use of the GPU that focus on the deformation of a snow surface in real-time. The approaches are examined by their ability to scale with an increasing number of deformation actors and their visual portrayal of snow deformation. The findings indicate that the approaches maintain real-time performance well into several hundred individual deformation actors. However, these approaches each have their individual restrictions handicapping the visual results. An experimental approach is to combine the techniques at reduced deformation actor count to benefit from the detailed, merged deformation pattern.
The goal of this thesis is to create a recommender system (RS) for business processes, based on the existing ProM plugin RegPFA. To accomplish this task, firstly an interface must be created that sets up and expands a database receiving probabilistic finite automata (PFA) created by RegPFA in tsml format as input. Secondly, a Java program must be designed that uses said database to recommend the process elements that are most likely to follow a given sequence of process elements.
The development of a game engine is considered a non-trivial problem. [3] The architecture of such simulation software must be able to manage large amounts of simulation objects in real-time while dealing with “crosscutting concerns” [3,p. 36] between subsystems. The use of object oriented paradigms to model simulation objects in class hierarchies has been reported as incompatible with constantly changing demands during game development [2, p. 9], resulting in anti-patterns and eventual, messy refactoring.[13]
Alternative architectures using data oriented paradigms revolving around object composition and aggregation have been proposed as a result. [13, 9, 1, 11]
This thesis describes the development of such an architecture with the explicit goals to be simple, inherently compatible with data oriented design, and to make reasoning about performance characteristics possible. Concepts are formally defined to help analyze the problem and evaluate results. A functional implementation of the architecture is presented together with use cases common to simulation software.
Ecological assessment approaches based on benthic invertebrates in Euphrates tributaries in Turkey
(2019)
Sustainable water management requires methods for assessing ecological stream quality. Many years of limnological research are needed to provide a basis for developing such methods. However, research of this kind is still lacking in Turkey. Therefore, the aim of this doctoral thesis was to provide basic research in the field of aquatic ecology and to present methods for the assessment of ecological stream quality based on benthic invertebrates. For this purpose, I selected 17 tributaries of the Euphrates with a similar typology/water order and varying levels of pollution or not affected by pollution at all. The characterisation of the natural mountain streams was the first important step in the analysis of ecological quality. Based on community indices, I found that the five selected streams had a very good ecological status. I also compared the different biological indications, collected on two occasions ¬– once in spring (May) and once in autumn (September) – to determine the optimal sampling time. The macroinvertebrate composition differed considerably between the two seasons, with the number of taxa and Shannon index being significantly higher in autumn than in spring. In the final step, I examined the basal resources of the macroinvertebrates in the reference streams with an isotope analysis. I found that FPOM and biofilm were the most relevant basal resources of benthic invertebrates. Subsequently, based on the similarity of their community structures, I divided the 17 streams into three quality classes, supported by four community indices (EPT [%], EPTCBO [%], number of individuals, evenness). In this process, 23 taxa were identified as indicators for the three quality classes. In the next step, I presented two new or adapted indices for the assessment of quality class. Firstly, I adapted the Hindu Kush-Himalaya biotic index to the catchment area of the Euphrates and created a new, ecoregion-specific score list (Euph-Scores) for 93 taxa. The weighted ASPT values, which were renamed the Euphrates Biotic Score (EUPHbios) in this study, showed sharper differentiations of quality classes compared to the other considered ASPT values. Thus, this modified index has proved to be very effective and easy to implement in practical applications. As a second biological index, I suggested the proportion of habitat specialists. To calculate this index, the habitat preferences of the 20 most common benthic invertebrates were identified using the new habitat score. The proportion of habitat specialists differed significantly among the three quality classes with higher values in natural streams than in polluted streams. The methods and results presented in this doctoral thesis can be used in a multi-metric index for a Turkish assessment programme.
Engineering criminal agents
(2019)
This PhD thesis with the title "Engineering Criminal Agents" demonstrates the interplay of three different research fields captured in the title: In the centre are Engineering and Simulation, both set in relation with the application field of Criminology - and the social science aspect of the latter. More precisely,
this work intends to show how specific agent-based simulation models can be created using common methods from software engineering.
Agent-based simulation has proven to be a valuable method for social science since decades, and the trend to increasingly complex simulation models is apparent, not at least due to advancing computational and simulation techniques. An important cause of complexity is the inclusion of 'evidence' as basis of simulation models. Evidence can be provided by various stakeholders, reflecting their different viewpoints on the topic to model.
This poses a particular burden by interrelating the two relevant perspectives on the topic of simulation: on the one hand the user of the simulation model who provides the requirements and is interested in the simulation results, on the other hand the developer of the simulation model who has to program a verified and validated formal model. In order to methodically link these two perspectives, substantial efforts in research and development are needed, where this PhD thesis aims to make a contribution.
The practical results - in terms of software - were achieved by using the multi-faceted approach mentioned above: using methods from software engineering, in order to become able to apply methods from computational social sciences, in order to gain insights into social systems, such as in the internal dynamics of criminal networks.
The PhD thesis shows the research involved to create these practical results, and gives technical details and specifications of the developed software.
The frame for research and development to achieve these results was provided mainly by two research projects: OCOPOMO and GLODERS.
This dissertation deals with the opportunities and restrictions that parties face in an election campaign at the supranational level of the EU. Using communication science concepts of agenda-setting (focus: media) and agenda-building (focus: political parties), the first part of the study is based on the election campaign for the European Parliament (EP) in 2014. It analyses to what extent political parties put the EU on the agenda. Second, it is examined whether parties have used their structural advantage of being able to influence the media agenda at the supranational level during the election campaign in the context of the EP election campaign. Third, it is examined whether parties can gain an advantage for the visibility of their campaigns by rejecting EU integration and the associated conflictual communication. Fourth and final, it will be explored whether agenda-building can influence the rankings of specific policy issues on the media agenda in the European context.
First, the analyses show that a European political focus of election campaign communication can no longer be found only on the part of the small (eurosceptic) parties. Second, parties have a good chance of being present in media coverage if the they pursue a European political focus in their campaign communication. Third, a negative tone in party communication turns out not to be decisive for the parties' visibility in the election campaign. Fourth, a clear positioning on political issues also prepares parties for restrictions of the further development of a European thematic agenda. After a discussion of these results, the paper concludes with an assessment of the analysis limitations and an outlook on further research approaches.
Most social media platforms allow users to freely express their opinions, feelings, and beliefs. However, in recent years the growing propagation of hate speech, offensive language, racism and sexism on the social media outlets have drawn attention from individuals, companies, and researchers. Today, sexism both online and offline with different forms, including blatant, covert, and subtle lan- guage, is a common phenomenon in society. A notable amount of work has been done over identifying sexist content and computationally detecting sexism which exists online. Although previous efforts have mostly used peoples’ activities on social media platforms such as Twitter as a public and helpful source for collecting data, they neglect the fact that the method of gathering sexist tweets could be biased towards the initial search terms. Moreover, some forms of sexism could be missed since some tweets which contain offensive language could be misclassified as hate speech. Further, in existing hate speech corpora, sexist tweets mostly express hostile sexism, and to some degree, the other forms of sexism which also appear online was disregarded. Besides, the creation of labeled datasets with manual exertion, relying on users to report offensive comments with a tremendous effort by human annotators is not only a costly and time-consuming process, but it also raises the risk of involving discrimination under biased judgment.
This thesis generates a novel sexist and non-sexist dataset which is constructed via "UnSexistifyIt", an online web-based game that incentivizes the players to make minimal modifications to a sexist statement with the goal of turning it into a non-sexist statement and convincing other players that the modified statement is non-sexist. The game applies the methodology of "Game With A Purpose" to generate data as a side-effect of playing the game and also employs the gamification and crowdsourcing techniques to enhance non-game contexts. When voluntary participants play the game, they help to produce non-sexist statements which can reduce the cost of generating new corpus. This work explores how diverse individual beliefs concerning sexism are. Further, the result of this work highlights the impact of various linguistic features and content attributes regarding sexist language detection. Finally, this thesis could help to expand our understanding regarding the syntactic and semantic structure of sexist and non-sexist content and also provides insights to build a probabilistic classifier for single sentences into sexist or non-sexist classes and lastly find a potential ground truth for such a classifier.