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The mitral valve is one of four human heart valves. It is located in the left heart and acts as a unidirectional passageway for blood between the left atrium and the left ventricle. A correctly functioning mitral valve prevents a backflow of blood into the pulmonary circulation (lungs) and thus constitutes a vital part of the cardiac cycle. Pathologies of the mitral valve can manifest in a variety of symptoms with severity ranging from chest pain and fatigue to pulmonary edema (fluid accumulation in the tissue and air space of lungs), which may ultimately cause respiratory failure.
Malfunctioning mitral valves can be restored through complex surgical interventions, which greatly benefit from intensive planning and pre-operative analysis. Visualization techniques provide a possibility to enhance such preparation processes and can also facilitate post-operative evaluation. The work at hand extends current research in this field, building upon patient-specific mitral valve segmentations developed at the German Cancer Research Center, which result in triangulated 3D models of the valve surface. The core of this work will be the construction of a 2D-view of these models through global parameterization, a method that can be used to establish a bijective mapping between a planar parameter domain and a surface embedded in higher dimensions.
A flat representation of the mitral valve provides physicians with a view of the whole surface at once, similar to a map. This allows assessment of the valve's area and shape without the need for different viewing angles. Parts of the valve that are occluded by geometry in 3D become visible in 2D.
An additional contribution of this work will be the exploration of different visualizations of the 3D and 2D mitral valve representations. Features of the valve can be highlighted by associating them with specified colors, which can for instance directly convey pathology indicators.
Quality and effectiveness of the proposed methods were evaluated through a survey conducted at the Heidelberg University Hospital.
The Internet of Things is still one of the most relevant topics in the field of economics and research powered by the increasing demand of innovative services. Cost reductions in manufacturing of IoT hardware and the development of completely new communication ways has led to the point of bil-lions of devices connected to the internet. But in order to rule this new IoT landscape a standardized solution to conquer these challenges must be developed, the IoT Architecture.
This thesis examines the structure, purpose and requirements of IoT Architecture Models in the global IoT landscape and proposes an overview across the selected ones. For that purpose, a struc-tured literature analysis on this topic is conducted within this thesis, including an analysis on three existing research approaches trying to frame this topic and a tool supported evaluation of IoT Archi-tecture literature with over 200 accessed documents.
Furthermore, a coding of literature with the help of the specialised coding tool ATLAS.ti 8 is conduct-ed on 30 different IoT Architecture Models. In a final step these Architecture Models are categorized and compared to each other showing that the environment of IoT and its Architectures gets even more complex the further the research goes.
Der Apple ][ war einer der drei ersten kompletten Computersysteme auf dem Markt. Von April 1977 an wurde er rund 16 Jahre lang mehrere Millionen mal verkauft. Entwickelt wurde dieser 8 Bit Homecomputer von Steve Wozniak und Steve Jobs. Sie ebneten damit den Weg für den Macintosh und das heute gut bekannte Unternehmen Apple.
Diese Arbeit beschreibt die Implementierung eines Softwareemulators für das komplette Apple ][ Computersystem auf nur einem Atmel AVR Microcontroller. Die größte Herausforderung besteht darin, dass der Microcontroller nur eine geringfügig höhere Taktrate als die zu emulierende Hardware hat. Dies erfordert eine effiziente Emulation der CPU und Speicherverwaltung, die nachfolgend zusammen mit der Laufzeitumgebung für die Emulation vorgestellt wird. Weiterhin wird die Umsetzung des Emulators mit Display und Tastatur in Hardware naher erläutert.
Mit dieser Arbeit wird die erfolgreiche Entwicklung eines portablen Apple ][ Emulators, von der Software über die Hardware bis hin zu einem Prototypen, vorgestellt.
Autonomous systems such as robots already are part of our daily life. In contrast to these machines, humans an react appropriately to their counterparts. People can hear and interpret human speech, and interpret facial expressions of other people.
This thesis presents a system for automatic facial expression recognition with emotion mapping. The system is image-based and employs feature-based feature extraction. This thesis analyzes the common steps of an emotion recognition system and presents state-of-the-art methods. The approach presented is based on 2D features. These features are detected in the face. No neutral face is needed as reference. The system extracts two types of facial parameters. The first type consists of distances between the feature points. The second type comprises angles between lines connecting the feature points. Both types of parameters are implemented and tested. The parameters which provide the best results for expression recognition are used to compare the system with state-of-the-art approaches. A multiclass Support Vector Machine classifies the parameters.
The results are codes of Action Units of the Facial Action Coding System. These codes are mapped to a facial emotion. This thesis addresses the six basic emotions (happy, surprised, sad, fearful, angry, and disgusted) plus the neutral facial expression. The system presented is implemented in C++ and is provided with an interface to the Robot Operating System (ROS).
Only little information is available about the diffusion of cloud computing in German higher educational institutions. A better understanding of the state of the art in this field would support the modernization of the higher educational institutions in Germany and allow the development of more adequate cloud products and more appropriate business models for this niche. For this purpose, a literature research on Cloud Computing and IT-diffusion will be run and an empirical investigation with an online questionnaire addressed to higher educational institutions in Germany will be performed to illustrate the state of the art of Cloud Computing in German higher educational institutions as well as the threats and opportunities perceived by employees of higher educational institutions data centers connected to the usage of the cloud.
In addition to that, different experts from universities and businesses will be interviewed to complete the knowledge and information collected through the online questionnaire and during the research phase. The expected results will serve to create a recommendation for higher educational institutions in Germany about either they should migration to the cloud or not and introduce a list of guiding questions of critical issues to consider before using cloud-computing technologies.
This thesis is providing an overview over the current topics and influences of mobile components on Enterprise Content Management (ECM). With a literature review the core topics of enterprise mobility and ECM have been identified and projected on the context of using mobile Apps within the environment of ECM. An analysis of three ECM systems and their mobile software lead to an understanding of the functionalities and capabilities mobile systems are providing in the ECM environment. These findings lead to a better un- derstanding for the usage of mobile Enterprise Content Management and is preparation. The thesis focuses the most important topics, which need to be considered for the usage and adoption of mobile Apps in ECM.
Concept for a Knowledge Base on ICT for Governance and Policy Modelling regarding eGovPoliNet
(2013)
Abstract The EU project eGovPoliNet is engaged in research and development in the field of information and communication technologies (ICT) for governance and policy modelling. Numerous communities pursue similar goals in this field of IT-based, strategic decision making and simulation of social problem areas. Though, the existing research approaches and results so far are quite fragmented. The aim of eGovPoliNet is to overcome the fragmentation across disciplines and to establish an international, open dialogue by fostering the cooperation between research and practice. This dialogue will advance the discussion and development of various problem areas with the help of researchers from different disciplines, who share knowledge, expertise and best practice supporting policy analysis, modelling and governance. To support this dialogue, eGovPoliNet will provide a knowledge base, which's conceptual development is the subject of this thesis. The knowledge base is to be filled with content from the area of ICT for strategic decision making and social simulation, such as publications, ICT solutions and project descriptions. This content needs to be structured, organised and managed in a way, so that it generates added value and the knowledge base is used as source of accumulated knowledge, which consolidates the previously fragmented research and development results in a central location.
The aim of this thesis is the development of a concept for a knowledge base, which provides the structure and the necessary functionalities to gather and process knowledge concerning ICT solutions for governance and policy modelling. This knowledge needs to be made available to users and thereby motivate them to contribute to the development and maintenance of the knowledge base.
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 identification of experts for a specific technology or framework produces a large benefit for collaborative software projects. Hence it reduces the communication overhead that is required to identify an expert on the fly. Therefore this thesis describes a tool and approach that can be used to identify an expert that has a specific skill-set. It will mainly focus on the skills and expertise of developers that use the Django framework. By adding more rules to our framework that approach could easily be extended for different technologies or frameworks. The paper will close with a case study on an open source project.
Procedural content generation, the generation of video game content using pseudo-random algorithms, is a field of increasing business and academic interest due to its suitability for reducing development time and cost as well as the possibility of creating interesting, unique game spaces. Although many contemporary games feature procedurally generated content, the author perceived a lack of games using this approach to create realistic outer-space game environments, and the feasibility of employing procedural content generations in such a game was examined. Using current scientific models, a real-time astronomical simulation was developed in Python which generates star and planets object in a fictional galaxy procedurally to serve as the game space of a simple 2D space exploration game where the player has to search for intelligent life.
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.
Companies try to utilise Knowledge Management (KM) to gain more efficiency and effectiveness in business. The major problem is that most of these KM projects are not or rarely based on sustainable analyses or established theories about KM. Often there is a big gap between the expectations and the real outcome of such KM initiatives. So the research question to be answered is: What challenges arise in KM projects, which KM requirements can be derived from them and which recommendations support the goal of meeting the requirements for KM? As theoretical foundation a set of KM frameworks is examined. Subsequently KM challenges from literature are analysed and best practices from case studies are used to provide recommendations for action on this challenges. The main outcome of this thesis is a best practice guideline,which allows Chief Knowledge Officers (CKOs) and KM project managers to examine the challenges mentioned in this thesis closely, and to find a suitable method to master these challenge in an optimal way. This guideline shows that KM can be positively and negatively influenced in a variety of ways. Mastering Knowledge Management (KM) in a company is a big and far-reaching venture and that technology respectively Information Technology (IT) is only a part of the big picture.
Wikipedia is the biggest, free online encyclopaedia that can be expanded by any-one. For the users, who create content on a specific Wikipedia language edition, a social network exists. In this social network users are categorised into different roles. These are normal users, administrators and functional bots. Within the networks, a user can post reviews, suggestions or send simple messages to the "talk page" of another user. Each language in the Wikipedia domain has this type of social network.
In this thesis characteristics of the three different roles are analysed in order to learn how they function in one language network of Wikipedia and apply them to another Wikipedia network to identify bots. Timestamps from created posts are analysed to reveal noticeable characteristics referring to continuous messages, message rates and irregular behaviour of a user are discovered. Through this process we show that there exist differences between the roles for the mentioned characteristics.
Regarding the rapidly growing amount of data produced every year and the increasing acceptance of Enterprise 2.0 enterprises have to care about the management of their data more and more. Content created and stored in an uncoordinated manner can lead to data-silos (Williams & Hardy 2011, p.57), which result in long search times, inaccessible data and in consequence monetary losses. The "expanding digital universe" forces enterprises to develop new archiving solutions and records management policies (Gantz et al. 2007, p.13). Enterprise Content Management (ECM) is the research field that deals with these challenges. It is placed in the scientific context of Enterprise Information Management. This thesis aims to find out to what extent current Enterprise Content Management Systems (ECMS) support these new requirements, especially concerning the archiving of Enterprise 2.0 data. For this purpose, three scenarios were created to evaluate two different kinds of ECMS (one Open Source - and one proprietary system) chosen on the basis of a short marketrnresearch. The application of the scenarios reveals that the system vendors actually face the industry- concerns: both tools provide functionality for the archiving of data arising from online collaboration and also business records management capabilities but the integration of those topics is not, or is only inconsistently solved. At this point new questions - such as, "Which datarngenerated in an Enterprise 2.0 is worth being a record?" - arise and should be examined in future research.
How entrepreneurs become successful with their business ideas has been a topic of discussion within entrepreneurial research circles for many years. Business success has been related to psychological characteristics and many research findings have explained how people become entrepreneurs and furthermore, how they find success in regards to their business ventures. People always wanted to know what defines an entrepreneur and more importantly, what is needed to become a successful entrepreneur. Curious minds began to search for the recipe for success. Personality Traits have been researched for years, leading to the discovery of many diverse and distinct forms which are still recognized today. Researchers compared the Behavioral Approach or the analysis of demographical characteristics to success.
This raises the question of what an entrepreneur needs to become successful which is made more difficult due to the fact that entrepreneurship and who an entrepreneur is can be difficult do define exactly. Entrepreneurs are diverse and distinct individuals that each possess their own characteristics, behavior and reasons for starting a business. Many people assume that it is just someone who starts their own business. While partially correct, this only scratches the surface of what it is to be an entrepreneur.
This thesis answers the following three research questions: 1. Which personality traits were found in the almost sixty years of researching? 2. What triggers do entrepreneurs need for starting a new business? 3. Which factor makes the entrepreneur successful with their business idea? Also, reading the thesis, one may gain a better understanding of what entrepreneurship is, what defines an entrepreneur and what one needs to become a successful entrepreneur.
In this thesis the reviewing literature method developed by Wolfswinkel et al. (2011) was used to identify suitable literature and references for the main chapters. For that the five stages of the grounded-theory method for reviewing the literature were used in an iterative fashion. In step one inclusion and exclusion criterias for literature were defined. Then literature was searched matching the criterias of step one. In step three the samples were refined. Then in step four the found literature was analyzed and coded before the results of this research was presented in the following text. Many entrepreneurial personality traits were discovered and confirmed during the studies conducted over the last sixty years, these include but are not limited to Need for Achievement, Locus of Control, or risk taking propensity. Motivation is clearly the main trigger to start your own business. During the studies reasons were discovered of how and why an entrepreneur may become successful outside of posessing the right combination of traits. For example: having human, financial and social capital, an entrepreneurial behavior and the right economic conditions to start a business that will survive for more than five years.
In this thesis we present an approach to track a RGB-D camera in 6DOF andconstruct 3D maps. We first acquire, register and synchronize RGB and depth images. After preprocessing we extract FAST features and match them between two consecutive frames. By depth projection we regain the z-value for the inlier correspondences. Afterwards we estimate the camera motion by 3D point set alignment between the correspondence set using least-squares. This local motion estimate is incrementally applied to a global transformation. Additionally wernpresent methods to build maps based on point cloud data acquired by a RGB-D camera. For map creation we use the OctoMap framework and optionally create a colored point cloud map. The system is evaluated with the widespread RGB-D benchmark.
Im Rahmen dieser Bachelorarbeit wurde ein Back-Office für die elektronische Version des Europäischen Schadensberichtes erstellt. Es wurde bereits in anderen Arbeiten ein mobiler Client, welcher auf einem Windows Mobile Handy läuft, sowie ein Polizei Client erstellt. Diese greifen auf das Back-Office zu, um Daten, wie z.B. die Autodaten (Automarke, der Typ, das Baujahr und Bilder eines 3D-Modells des Autos) zu einem bestimmten Kennzeichen oder die Personendaten des jeweiligen Autobesitzers zu erhalten. Der mobile Client sendet zudem die Unfallakte an das Back-Office, damit die Daten über einen Unfall in diesem abgespeichert und weiter bearbeitet werden können. Ziel der Arbeit war es ein erweiterbares, modulares System zu entwickeln, welches später um weitere Module ergänzt werden kann, um neue Funktionen bereitstellen zu können. Diese Module können jeweils beliebige Daten in einer Datenbank abspeichern und diese von der Datenbank auch wieder abfragen, sowie verändern, ohne dass das relationale Schema der Datenbank verändert werden muss.
In this thesis we exercise a wide variety of libraries, frameworks and other technologies that are available for the Haskell programming language. We show various applications of Haskell in real-world scenarios and contribute implementations and taxonomy entities to the 101companies system. That is, we cover a broad range of the 101companies feature model and define related terms and technologies. The implementations illustrate how different language concepts of Haskell, such as a very strong typing system, polymorphism, higher-order functions and monads, can be effectively used in the development of information systems. In this context we demonstrate both advantages and limitations of different Haskell technologies.
Next word prediction is the task of suggesting the most probable word a user will type next. Current approaches are based on the empirical analysis of corpora (large text files) resulting in probability distributions over the different sequences that occur in the corpus. The resulting language models are then used for predicting the most likely next word. State-of-the-art language models are based on n-grams and use smoothing algorithms like modified Kneser-Ney smoothing in order to reduce the data sparsity by adjusting the probability distribution of unseen sequences. Previous research has shown that building word pairs with different distances by inserting wildcard words into the sequences can result in better predictions by further reducing data sparsity. The aim of this thesis is to formalize this novel approach and implement it by also including modified Kneser-Ney smoothing.
The goal of this Bachelor thesis is to implement and evaluate the "Simulating of Collective Misbelief"-model into the NetLogo programming language. Therefore, the model requirements have to be specified and implemented into the NetLogo environment. Further tool-related re-quirements have to be specified to enable the model to work in NetLogo. After implementation several simulations will be conducted to answer the research question stated above.
Abstract
This bachelor thesis delivers a comprehensive overview of the topic Internet of Things (IoT). With the help of a first literature review, important characteristics, architectures, and properties have been identified. The main aim of this bachelor thesis is to determine whether the use of IoT in the transport of food, considering the compliance with the cold chain, can provide advantages for companies to reduce food waste. For this purpose, a second literature review has been carried out with food transport systems without the use, as well as with the use of IoT. Based on the literature review, it is possible at the end to determine a theoretical ‘ideal’ system for food transport in refrigerated trucks. The respective used technologies are also mentioned. The findings of several authors have shown that often significant improvements can be achieved in surveillance, transport in general, or traceability of food, and ultimately food waste can be reduced. However, benefits can also be gained using new non-IoT-based technologies. Thus, the main knowledge of this bachelor thesis is that a theoretical ‘ideal’ transport system contains a sensible combination of technologies with and without IoT. This system includes the use of a Wireless Sensor Network (WSN) for real-time food monitoring, as well as an alarm function when the temperature exceeds a maximum. Real-time monitoring with GPS coupled with a monitoring center to prevent traffic jams is another task. Smart and energy-efficient packaging, and finally the use of the new supercooling-technology, make the system significantly more efficient in reducing food waste. These highlights, that when choosing a transport system, which is as efficient and profitable as possible for food with refrigerated transport, companies need not just rely on the use of IoT. On this basis, it is advisable to combine the systems and technologies used so far with IoT in order to avoid as much food waste as possible.
During the last couple of years the extension of the internet into the real world, also referred to as the Internet of Things (IoT), was positively affected by an ongoing digitalization (Mattern and Floerkemeier, 2010; Evans, 2013). Furthermore, one of the most active IoT domains is the personal health ecosystem (Steele and Clarke, 2013). However, this thesis proposes a gamification framework which is supported and enabled by IoT to bring personal health and IoT together in the context of health-insurances. By examining gamification approaches and identifying the role of IoT in such, a conceptual model of a gamification approach was created which indicates where and how IoT is ap-plicable to it. Hence, IoT acts as enabler and furthermore as enhancer of gamified activities. Especial-ly the necessity of wearable devices was highlighted. A stakeholder analysis shed light on respective benefits which concluded in the outcome, that IoT enabled two paradigm shifts for both, the insur-ance and their customer. While taking the results of the examination and the stakeholder analysis as input, the previously made insights were used to develop an IoT supported gamification framework. The framework includes a multi-level structure which is meant to guide through the process of creat-ing an approach but also to analyze already existing approaches. Additionally, the developed frame-work was instantiated based on the application Pokémon Go to identify occurring issues and explain why it failed to retain their customer in the long term. The thesis provides a foundation on which fur-ther context related research can be orientated.
This thesis describes the implementation of a Path-planning algorithm for multi-axle vehicles using machine learning algorithms. For that purpose, a general overview over Genetic Algorithms is given and alternative machine learning algorithms are briefly explained. The software developed for this purpose is based on the EZSystem Simulation Software developed by the AG Echtzeitysteme at the University Koblenz-Landau and a path correction algorithm developed by Christian Schwarz, which is also detailed in this paper. This also includes a description of the vehicle used in these simulations. Genetic Algorithms as a solution for path-planning in complex scenarios are then evaluated based on the results of the developed simulation software and compared to alternative, non-machine learning solutions, which are also shortly presented.
With global and distributed project teams being increasingly common Collaborative Project Management is becoming the prevalent paradigm for the work in most organisations. Software has for many years been one of the most used tools for supporting Project Management and with the focus on Collaborative Project Management and accompanied by the emergence of Enterprise Collaboration Systems (ECS), Collaborative Project Management Software (CPMS) is gaining increased attention. This thesis examines the capabilities of CPMS for the long-term management of information which not only includes the management of files within these systems, but the management of all types of digital business documents, particularly social business documents. Previous research shows that social content in collaboration software is often poorly managed which poses challenges to meeting performance and conformance objectives in a business. Based on literature research, requirements for the long-term management of information in CPMS are defined and 7 CPMS tools are analysed regarding the content they contain and the functionalities for the long-term management of this content they offer. The study shows that CPMS by and large are not able to meet the long-term information management needs of an organisation on their own and that only the tools geared towards enterprise customers have sufficient capabilities to support the implementation of an Enterprise Information Management strategy.
Colonoscopy is the gold standard for the detection of colorectal polyps that can progress into cancer. In such an examination, physicians search for polyps in endoscopic images. Thereby polyps can be removed. To support experts with a computer-aided diagnosis system, the University of Koblenz-Landau currently makes some efforts in research different methods for automatic detection. Comparable to traditional pattern recognition systems, features are initially extracted and a classifier is trained on such data. Afterwards, unknown endoscopic images can be classified with the previously trained classifier. This thesis concentrates on the extension of the feature extraction module in the existing system. New detection methods are compared to existing techniques. Several features are implemented, incorporating Graylevel Co-occurrence Matrices, Local Binary Patterns and Discrte Wavelet Transform. Different modifications on those features are applied and evaaluated.
In this study, the author evaluates four visualization methods (FlexViz, the Jambalaya applet, Experimental jOWL TouchGraph, and Plone ontology) from the pool of currently available web based visualization methods.
Further, this study attempts to answer of the following research questions: 1. What are the requirements for ontology visualization? 2. How is comparative analysis and evaluation carried out? 3. How can a chosen method be tested? Based on the results of the evaluation, the visualization method FlexViz was found to be the most suitable for the given scenario. The deployment of FlexViz was carried out and integrated within Plone CMS and logical parts of the VCD ontology are tested. Finally, FlexViz was analyzed from different stakeholder- perspectives. Results showed that FleViz is a reliable tool for visualizing, understanding and analyzing a developed ontology because of its user-friendly and interactive interface, but performs poorly in regards to the editing, extension and development process.
Molecular dynamics (MD) as a field of molecular modelling has great potential to revolutionize our knowledge and understanding of complex macromolecular structures. Its field of application is huge, reaching from computational chemistry and biology over material sciences to computer-aided drug design. This thesis on one hand provides insights into the underlying physical concepts of molecular dynamics simulations and how they are applied in the MD algorithm, and also briefly illustrates different approaches, as for instance the molecular mechanics and molecular quantum mechanics approaches.
On the other hand an own all-atom MD algorithm is implemented utilizing and simplifying a version of the molecular mechanics based AMBER force field published by \big[\cite{cornell1995second}\big]. This simulation algorithm is then used to show by the example of oxytocin how individual energy terms of a force field function. As a result it has been observed, that applying the bond stretch forces alone caused the molecule to be compacted first in certain regions and then as a whole, and that with adding more energy terms the molecule got to move with increasing flexibility.
This thesis explores a 3D object detection and pose estimation approach based on the point pair features method presented by Drost et. al. [Dro+10]. While pose estimation methods have shown good improvements, they still remain a crucial problem on the computer vision field. In this work, we implemented a program that takes point cloud scenes as input and returns the detected object with their estimated pose. The program fully covers an object detection pipeline by processing 3D models during an offline phase, extracting their point pair features and creating a global descriptor out of them. During an online phase, the same features are extracted from a point cloud scene and are matched to the model features. After the voting scheme, potential poses of the object are retrieved. The poses end being clustered together and post-processed to finally deliver a result. The program was tested using simulated and real data. We evaluate these tests and present the final results, by discussing the achieved accuracy of the detections and the estimated poses.
Over the past few decades society’s dependence on software systems has grown significantly. These systems are utilized in nearly every matter of life today and often handle sensitive, private data. This situation has turned software security analysis into an essential and widely researched topic in the field of computer science. Researchers in this field tend to make the assumption that the quality of the software systems' code directly affects the possibility for security gaps to arise in it. Because this assumption is based on properties of the code, proving it true would mean that security assessments can be performed on software, even before a certain version of it is released. A study based on this implication has already attempted to mathematically assess the existence of such a correlation, studying it based on quality and security metric calculations. The present study builds upon that study in finding an automatic method for choosing well-fitted software projects as a sample for this correlation analysis and extends the variety of projects considered for the it. In this thesis, the automatic generation of graphical representations both for the correlations between the metrics as well as for their evolution is also introduced. With these improvements, this thesis verifies the results of the previous study with a different and broader project input. It also focuses on analyzing the correlations between the quality and security metrics to real-world vulnerability data metrics. The data is extracted and evaluated from dedicated software vulnerability information sources and serves to represent the existence of proven security weaknesses in the studied software. The study discusses some of the difficulties that arise when trying to gather such information and link it to the difference in the information contained in the repositories of the studied projects. This thesis confirms the significant influence that quality metrics have on each other. It also shows that it is important to view them together as a whole and suppose that their correlation could influence the appearance of unwanted vulnerabilities as well. One of the important conclusions I can draw from this thesis is that the visualization of metric evolution graphs, helps the understanding of the values as well as their connection to each other in a more meaningful way. It allows for better grasp of their influence on each other as opposed to only studying their correlation values. This study confirms that studying metric correlations and evolution trends can help developers improve their projects and prevent them from becoming difficult to extend and maintain, increasing the potential for good quality as well as more secure software code.
This bachelor thesis deals with the comparison related to the similarity of recorded WiFi patterns during the tracing of a path through the streets of a large city. Both MAC address only comparison has been investigated as well as the incorporation of RSSI values, whereby the localization accuracy has been evaluated. Methods for the detection of different types and combinations of loops in the path are demonstrated likewise the attempt to estimate the degree of urban development in the environment of the user by assessing the received signal strength and signal-to-noise ratio of GPS satellites and GSM cell towers.
In order to observe a user- proximity to a certain spot on a large public square the absorption of WiFi signals by the human body has been taken into account. Finally, the results of a comparison of the computing performance of a modern smartphone versus the alternative of remote calculation on a server including data transmission via cellular data network are presented.
During olive oil production, large amounts of olive mill wastewater (OMW) are generated within a short period of time. OMW has a high nutrient content and could serve as fertilizer when applied on land. However, its fatty and phenolic constituents have adverse effects on soil properties. It is still unknown how seasonal fluctuations in temperature and precipitation influence the fate and effect of OMW components on soil properties in a long-term perspective. An appropriate application season could mitigate negative consequences of OMW while preserving its beneficial effects. In order to investigate this, 14 L OMW m-2 were applied to different plots of an olive plantation in winter, spring, and summer respectively. Hydrological soil properties (water drop penetration time, hydraulic conductivity, dynamic contact angle), physicochemical parameters (pH, EC, soluble ions, phenolic compounds, organic matter), and biological degradation (bait-lamina test) were measured to assess the soil state after OMW application. After one rainy season following OMW application, the soil quality of summer treatments significantly decreased compared to the control. This was particularly apparent in a three-times lower biodegradation performance, ten-fold higher soil water repellency, and a four-fold higher content of phenolic compounds. The soil properties of winter treatments were comparable to the control, which demonstrated the recovery potential of the soil ecosystem. Spring treatments resulted in an intermediate response compared to summer and winter treatments, but without any precipitation following OMW application. Significant accumulation or leaching effects to deeper soil were not observed. Therefore, the direct application of legally restricted OMW amounts to soil is considered acceptable during the moist seasons. Further research is needed to quantify the effect of spring treatments and to gain further insight into the composition and kinetics of organic OMW constituents in the soil.
Social media platforms such as Twitter or Reddit allow users almost unrestricted access to publish their opinions on recent events or discuss trending topics. While the majority of users approach these platforms innocently, some groups have set their mind on spreading misinformation and influencing or manipulating public opinion. These groups disguise as native users from various countries to spread frequently manufactured articles, strong polarizing opinions in the political spectrum and possibly become providers of hate-speech or extremely political positions. This thesis aims to implement an AutoML pipeline for identifying second language speakers from English social media texts. We investigate style differences of text in different topics and across the platforms Reddit and Twitter, and analyse linguistic features. We employ feature-based models with datasets from Reddit, which include mostly English conversation from European users, and Twitter, which was newly created by collecting English tweets from selected trending topics in different countries. The pipeline classifies language family, native language and origin (Native or non-Native English speakers) of a given textual input. We evaluate the resulting classifications by comparing prediction accuracy, precision and F1 scores of our classification pipeline to traditional machine learning processes. Lastly, we compare the results from each dataset and find differences in language use for topics and platforms. We obtained high prediction accuracy for all categories on the Twitter dataset and observed high variance in features such as average text length especially for Balto-Slavic countries.
101worker is the modular knowledge engineering component of the 101companies project. It has developed maintainability and performance problems due to growing organically, rather than following best software design practices. This thesis lays out these problems, drafts a set of requirements for refactoring the system and then describes and analyzes the resulting implementation. The solution involves collation of scattered and redundant information, setup of unit and functional test suites and incrementalization of the bus architecture of 101worker.
Real-time graphics applications are tending to get more realistic and approximate real world illumination gets more reasonable due to improvement of graphics hardware. Using a wide variation of algorithms and ideas, graphics processing units (GPU) can simulate complex lighting situations rendering computer generated imagery with complicated effects such as shadows, refraction and reflection of light. Particularly, reflections are an improvement of realism, because they make shiny materials, e.g. brushed metals, wet surfaces like puddles or polished floors, appear more realistic and reveal information of their properties such as roughness and reflectance. Moreover, reflections can get more complex, depending on the view: a wet surface like a street during rain for example will reflect lights depending on the distance of the viewer, resulting in more streaky reflection, which will look more stretched, if the viewer is locatedrnfarther away from the light source. This bachelor thesis aims to give an overview of the state-of-the-art in terms of rendering reflections. Understanding light is a basic need to understand reflections and therefore a physical model of light and its reflection will be covered in section 2, followed by the motivational section 2.2, that will give visual appealing examples for reflections from the real world and the media. Coming to rendering techniques, first, the main principle will be explained in section 3 followed by a short general view of a wide variety of approaches that try to generate correct reflections in section 4. This thesis will describe the implementation of three major algorithms, that produce plausible local reflections. Therefore, the developed framework is described in section 5, then three major algorithms will be covered, that are common methods in most current game and graphics engines: Screen space reflections (SSR), parallax-corrected cube mapping (PCCM) and billboard reflections (BBR). After describing their functional principle, they will be analysed of their visual quality and the possibilities of their real-time application. Finally they will be compared to each other to investigate the advantages and disadvantages over each other. In conclusion, the gained experiences will be described by summarizing advantages and disadvantages of each technique and giving suggestions for improvements. A short perspective will be given, trying to create a view of upcoming real-time rendering techniques for the creation of reflections as specular effects.
API migration refers to the change of a used API to a different API in a program. A special case is called wrapper-based API migration. The API change is done without touching the program but the old API is reimplemented by means of the from now on used one. This so called wrapper has the interface of the reimplemented API but uses the implementation of the new one.
This is an interesting approach because the wrapper can be used in each program, which uses the old API.
To make this approach reproducible we study a ranking-based method for implementing a wrapper, where we always implement the method with the highest priority depending on failing test cases. Thus, we can reconstruct each implementation step.
We first develop an infrastructure to run and log test suites of Java projects that use an API, which we want to change.
We then build a wrapper for a given API using the ranking-based approach.
The Internet of Things (IoT) is a concept in which connected physical objects are integrated into the virtual world to become active partakers of businesses and everyday processes (Uckelmann, Harrison and Michahelles, 2011; Shrouf, Ordieres and Miragliotta, 2014). It is expected to have a major impact on businesses (Council, Nic and Intelligence, 2008), but small and medium enterprises’ business models are threatened if they do not adopt the new concept (Sommer, 2015). Thus, this thesis aims to showcase a sample implementation of connected devices in a small enterprise, demonstrating its added benefits for the business.
Design Science Research (DSR) is used to develop a prototype based on a use case provided by a carpentry. The prototype comprises a hardware sensor and a web application which can be used by the wood shop to improve their processes. The thesis documents the iterative process of developing a prototype from the grounds up to useable hard- and software.
This contribution provides an example of how IoT can be used and implemented at a small business.
Part-of-Speech tagging is the process of assigning words with similar grammatical properties to a part of speech (PoS). In the English language, PoS-tagging algorithms generally reach very high accuracy. This thesis undertakes the task to test against these accuracies in PoS-tagging as a qualitative measure in classification capabilities for a recently developed neural network model, called graph convolutional network (GCN). The novelty proposed in this thesis is to translate a corpus into a graph as a direct input for the GCN. The experiments in this thesis serve as a proof of concept with room for improvements.
Texture-based text detection in digital images using wavelet features and support vector machines
(2010)
In this bachelor thesis a new texture-based approach for the detection of text in digital images is presented. The procedure can be essentially divided into two main tasks, in detection of text blocks and detection of individual words, whereby the individual words are extracted from the detected text blocks. Roughly, the developed method acts with multiple support vector machines, which classify possible text regions of an image into real text regions, using wavelet-based features. In the process the possible text regions are defifined by edge projections with diσerent orientations. The results of the approach are X/Y coordinates, width and height of rectangular regions of an image, which contains individual words. This knowledge can be further processed, for example by an optical character recognition software to get the important and useful text information.
Entrepreneurship plays a vital role in scientific literature and in public debates. Especially in these hightech and digitized times it happens more and more frequently that young entrepreneurs with a good idea make the breakthrough and set up an established company. Basically, there are an increasing number of start-ups and a trend towards independence. The economy of a country depends on young entrepreneurs in order to remain economically competitive in international competition. It follows that young entrepreneurs must be encouraged and supported. This support is expressed in various stages of foundation and through various fields of action. In the meantime, there are many offers for start-up support. These networks satisfy different fields of action along a foundation. However, a structured overview of these networks on which a young founder can orient himself and gain easily access to the offers of the networks, is missing until then.
This work attempts to present these offers clearly on a map and to categorize and present the commitment in the respective fields of action. In addition to this main objective, the following three key questions are investigated and answered in this work:
1. How can the Entrepreneurship Networks be assigned to the respective fields of action of Entrepreneurship Education?
2. What is the benefit of such a classification for potential entrepreneurs in detail?
3. Are these Entrepreneurship networks missing an important step? Might they improve their offer? Does the value chain cover every need a young entrepreneur might have?
For this purpose, the respective fields of action of the networks are first separated from each other along a founding and defined individually. Subsequently, a combination of quantitative and qualitative approaches was used to filter and analyze the contents of the websites of the networks. The results of this investigation were transformed in a classification
The aim of this work is to produce a map that displays the existing networks in the world clearly. The map also contains information that is more detailed and the classifica-tion of the networks in the respective fields of action.
This research examines information audit methodologies and information capturing methods for enterprise social software which are an elementary part of the audit process. Information auditing is lacking of a standardized definition and methodology because the scope of the audit process is diversified and dependent on the organization undertaking the audit. The benefits of information auditing and potential challenges of Enterprise 2.0 the audit can overcome are comprehensive and provide a major incentive for managers to conduct an audit. Information asset registers as a starting point for information auditing are not specifically focusing on social software assets. Therefore this research pro-ject combines asset registers from different areas to create a new register suitable for the requirements of Enterprise 2.0. The necssary adaptations caused by the new character of the assets are minor. The case study applying the asset register for the first time however reveals several problematic areas for information auditors completing the register. Rounding up the thesis a template is developed for setting up new work spaces on enterprise social software systems with appropriate metadata taking into account the meaningful metadata discovered in the asset register.
The following thesis analyses the functionality and programming capabilitiesrnof compute shaders. For this purpose, chapter 2 gives an introductionrnto compute shaders by showing how they work and how they can be programmed. In addition, the interaction of compute shaders and OpenGL 4.3 is shown through two introductory examples. Chapter 3 describes an NBodyrnsimulation that has been implemented in order to show the computational power of compute shaders and the use of shared memory. Then it is shown in chapter 4 how compute shaders can be used for physical simulationsrnand where problems may arise. In chapter 5 a specially conceived and implemented algorithm for detecting lines in images is described and then compared with the Hough transform. Lastly, a final conclusion is drawn in chapter 6.
This thesis connects the endeavors of the winemaker’s intention in perfect and profitable wine making with an innovative technological application to use Internet of Things. Thereby the winemaker’s work may be supported and enriched – and enables until recent years still unthinkable optimization of managing and planning of his business, including close state control of different areas of his vineyard, and more than that, not ending up with the single grapevine. It is exemplarily shown in this thesis how to measure, transmit, store and make data available, exemplarily demonstrated with “live” temperature, air and soil humidity values from the vineyard. A modular architecture was designed for the system presented, which allows the use of current sensors, and similar low-voltage sensors, which will be developed in the future.
By using IoT devices in the vineyard, the winemaker advances to a new quality of precision of forecasted data, starting from live data of his vineyard. Of more and more importance, the winemaker can start immediate action, when unforeseen heavy weather conditions occur. Immediate use of current data enabled by a Cloud Infrastructure. For this system, an open service infrastructure is employed. In contrast to other published commercial approaches, the described solution is based on open source.
As an alone-standing part of this work, a physical prototype for measuring relevant parameters in the vineyard was de-novo designed and developed until fulfilling the set of specifications. The outlined features and requirements for a functioning data collection and autonomously transmitting device was developed, described, and the fulfilment by the prototype device were demonstrated. Through literature research and supportive orientationally live interviews of winemakers, the theory and the practical application were synchronized and qualified.
For the development of the prototype the general principles of development of an electronic device were followed, in particular the Design Science Research development rules, and principles of Quality Function Deployment. As a characteristic of the prototype, some principles like re-use of approved construction and material price of the building blocks of the device were taken into consideration as well (e.g. housing; Arduino; PCB). Parts reduction principles, decomplexation and simplified assembly, testing and field service were integrated to the development process by the modular design of the functional vineyard device components, e.g. with partial reference to innovative electrical cabinet construction system Modular-3.
The software architectural concept is based on a three-layer architecture inclusive the TTN infrastructure. The front end is realized as a rich web client, using a WordPress plugin. WordPress was chosen due to the wide adoption through the whole internet, enabling fast and easy user familiarization. Relevant quality issues have been tested and discussed in the view of exemplary functionality, extensibility, requirements fulfilment, as usability and durability of the device and the software.
The prototype was characterized and tested with success in the laboratory and in field exposition under different conditions, in order to allow a measurement and analysis of the fulfilment of all requirements by the selected and realized electronic construction and layout.
The solution presented may serve as a basis for future development and application in this special showcase and within similar technologies. A prognosis of future work and applications concludes this work.
This work describes a novel software tool for visualizing anatomical segmentations of medical images. It was developed as part of a bachelor's thesis project, with a view to supporting research into automatic anatomical brain image segmentation. The tool builds on a widely-used visualization approach for 3D image volumes, where sections in orthogonal directions are rendered on screen as 2D images. It implements novel display modes that solve common problems with conventional viewer programs. In particular, it features a double-contour display mode to aid the user's spatial orientation in the image, as well as modes for comparing two competing segmentation labels pertaining to one and the same anatomical region. The tool was developed as an extension to an existing open-source software suite for medical image processing. The visualization modes are, however, suitable for implementation in the context of other viewer programs that follow a similar rendering approach.
The modified code can be found here: soundray.org/mm-segmentation-visualization.tar.gz.
We are entering the 26th year from the time the World Wide Web (WWW) became reality. Since the birth of the WWW in 1990, the Internet and therewith websites have changed the way businesses compete, shifting products, services and even entire markets.
Therewith, gathering and analysing visitor traffic on websites can provide crucial information to un- derstand customer behavior and numerous other aspects.
Web Analytics (WA) tools offer a quantity of diverse functionality, which calls for complex decision- making in information management. Website operators implement Web Analytic tools such as Google Analytics to analyse their website for the purpose of identifying web usage to optimise website design and management. The gathered data leads to emergent knowledge, which provides new marketing opportunities and can be used to improve business processes and understand customer behavior to increase profit. Moreover, Web Analytics plays a significant role to measure performance and has therefore become an important component in web-based environments to make business decisions.
However, many small and medium –sized enterprises try to keep up with the web business competi- tion, but do not have the equivalent resources in manpower and knowledge to stand the pace, there- fore some even resign entirely on Web Analytics.
This research project aims to develop a Web Analytics framework to assist small and medium-sized enterprises in making better use of Web Analytics. By identifying business requirements of SMEs and connecting them to the functionality of Google Analytics, a Web Analytics framework with attending guidelines is developed, which guides SMEs on how to proceed in using Google Analytics to achieve actionable outcomes.