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The main goal of this work was to experimentally characterize the hot air-drying process of agricultural products (Potato, Carrot, Tomato) and verify it with numerical solutions at single layer and industrial scale dryer using Comsol Multiphysics® 5.3.
Input parameters at single layer dryer effects on quality attributes were examined. Two strategies of drying were applied on batch dryer to examine the input effects on quality attributes. Constant input parameters strategy was designed by using central composite design formulation and optimized by Response Surface Methodology (RSM). The second strategy was applied for further optimization of the selected region by using square wave profile of the air temperature and relative humidity. Similarly, numerical method for single layer dryer, unsteady-state partial differential equations have been solved by means of the Finite Elements Method coupled to the Arbitrary Lagrangian-Eulerian (ALE). Also, for batch dryer, the mechanistic mathematical models of coupled heat and mass transfer were developed and solved as solid porous moist material.
With this work, the process of convective drying of agricultural products could be optimized. Furthermore, important knowledge about the basic mechanisms of the drying process was found and implemented in the numerical models.
This thesis presents the development of two different state-feedback controllers to solve the trajectory tracking problem, where the vessel needs to reach and follow a time-varying reference trajectory. This motion problem was addressed to a real-scaled fully actuated surface vessel, whose dynamic model had unknown hydrodynamic and propulsion parameters that were identified by applying an experimental maneuver-based identification process. This dynamic model was then used to develop the controllers. The first one was the backstepping controller, which was designed with a local exponential stability proof. For the NMPC, the controller was developed to minimize the tracking error, considering the thrusters’ constraints. Moreover, both controllers considered the thruster allocation problem and counteracted environmental disturbance forces such as current, waves and wind.The effectiveness of these approaches was verified in simulation using Matlab/Simulink and GRAMPC (in the case of the NMPC), and in experimental scenarios, where they were applied to the vessel, performing docking maneuvers at the Rhine River in Constance (Germany).
Cyberspace: a world at war. Our privacy, freedom of speech, and with them the very foundations of democracy are under attack. In the virtual world frontiers are not set by nations or states, they are set by those, who control the flows of information. And control is, what everybody wants.
The Five Eyes are watching, storing, and evaluating every transmission. Internet corporations compete for our data and decide if, when, and how we gain access to that data and to their pretended free services. Search engines control what information we are allowed - or want - to consume. Network access providers and carriers are fighting for control of larger networks and for better ways to shape the traffic. Interest groups and copyright holders struggle to limit access to specific content. Network operators try to keep their networks and their data safe from outside - or inside - adversaries.
And users? Many of them just don’t care. Trust in concepts and techniques is implicit. Those who do care try to take back control of the Internet through privacy-preserving techniques.
This leads to an arms race between those who try to classify the traffic, and those who try to obfuscate it. But good or bad lies in the eye of the beholder, and one will find himself fighting on both sides.
Network Traffic Classification is an important tool for network security. It allows identification of malicious traffic and possible intruders, and can also optimize network usage. Network Traffic Obfuscation is required to protect transmissions of important data from unauthorized observers, to keep the information private. However, with security and privacy both crumbling under the grip of legal and illegal black hat crackers, we dare say that contemporary traffic classification and obfuscation techniques are fundamentally flawed. The underlying concepts cannot keep up with technological evolution. Their implementation is insufficient, inefficient and requires too much resources.
We provide (1) a unified view on the apparently opposed fields of traffic classification and obfuscation, their deficiencies and limitations, and how they can be improved. We show that (2) using multiple classification techniques, optimized for specific tasks improves overall resource requirements and subsequently increases classification speed. (3) Classification based on application domain behavior leads to more accurate information than trying to identify communication protocols. (4) Current approaches to identify signatures in packet content are slow and require much space or memory. Enhanced methods reduce these requirements and allow faster matching. (5) Simple and easy to implement obfuscation techniques allow circumvention of even sophisticated contemporary classification systems. (6) Trust and privacy can be increased by reducing communication to a required minimum and limit it to known and trustworthy communication partners.
Our techniques improve both security and privacy and can be applied efficiently on a large scale. It is but a small step in taking back the Web.
Nachhaltiges Wirtschaften und insbesondere nachhaltigerer Konsum sind längst als zentrale Herausforderung des 21. Jahrhunderts erkannt worden. Unternehmen und Verbraucher/innen sind dabei gleichermaßen gefordert, sich gegenseitig in Prozessen gemeinsamer Wertschöpfung zu befähigen. Das Potential dieser Prozesse liegt jedoch nicht alleine in einer klugen Mäßigung der Akteure, sondern in einer sichtbaren Aufwertung der vielfältigen nachhaltigen Konsumoptionen. Eine Möglichkeit, dies zu erreichen, liegt darin, Nachhaltigkeit als Qualität für ein breites Spektrum von Konsumgütern erkennbar und erlebbar werden zu lassen. Eine Nachhaltigkeitsdeklarierung kann dabei weit mehr leisten als nur eine weitere visuelle Auszeichnung. Unternehmen können die kulturellen Kontexte von Verbraucher/innen erkennen und zielgerichtet agieren. Dabei können die vielfältigen Möglichkeiten digitaler Medien hilfreich sein. Die vorliegende Arbeit schlägt vor, dies stets mit Blick auf die lebendige Realität auf Anbieter- und Nachfragerseite zu tun.
Autonomous moving systems require very detailed information about their environment and potential colliding objects. Thus, the systems are equipped with high resolution sensors. These sensors have the property to generate more than one detection per object per time step. This results in an additional complexity for the target tracking algorithm, since standard tracking filters assume that an object generates at most one detection per object. This requires new methods for data association and system state filtering.
As new data association methods, in this thesis two different extensions of the Joint Integrated Probabilistic Data Association (JIPDA) filter to assign more than one detection to tracks are proposed.
The first method that is introduced, is a generalization of the JIPDA to assign a variable number of measurements to each track based on some predefined statistical models, which will be called Multi Detection - Joint Integrated Probabilistic Data Association (MD-JIPDA).
Since this scheme suffers from exponential increase of association hypotheses, also a new approximation scheme is presented. The second method is an extension for the special case, when the number and locations of measurements are a priori known. In preparation of this method, a new notation and computation scheme for the standard Joint Integrated Data Association is outlined, which also enables the derivation of a new fast approximation scheme called balanced permanent-JIPDA.
For state filtering, also two different concepts are applied: the Random Matrix Framework and the Measurement Generating Points. For the Random Matrix framework, first an alternative prediction method is proposed to account for kinematic state changes in the extension state prediction as well. Secondly, various update methods are investigated to account for the polar to Cartesian noise transformation problem. The filtering concepts are connected with the new MD-JIPDA and their characteristics analyzed with various Monte Carlo simulations.
In case an object can be modeled by a finite number of fixed Measurement Generating Points (MGP), also a proposition to track these object via a JIPDA filter is made. In this context, a fast Track-to-Track fusion algorithm is proposed as well and compared against the MGP-JIPDA.
The proposed algorithms are evaluated in two applications where scanning is done using radar sensors only. The first application is a typical automotive scenario, where a passenger car is equipped with six radar sensors to cover its complete environment.
In this application, the location of the measurements on an object can be considered stationary and that is has a rectangular shape. Thus, the MGP based algorithms are applied here. The filters are evaluated by tracking especially vehicles on nearside lanes.
The second application covers the tracking of vessels on inland waters. Here, two different kind of Radar systems are applied, but for both sensors a uniform distribution of the measurements over the target's extent can be assumed. Further, the assumption that the targets have elliptical shape holds, and so the Random Matrix Framework in combination with the MD-JIPDA is evaluated.
Exemplary test scenarios also illustrate the performance of this tracking algorithm.
In this thesis, the recognition problem and the properties of eigenvalues and eigenvectors of matrices which are strictly sign-regular of a given order, i.e., matrices whose minors of a given order have the same strict sign, are considered. The results are extended to matrices which are sign-regular of a given order, i.e., matrices whose minors of a given order have the same sign or are allowed to vanish. As a generalization, a new type of matrices called oscillatory of a specific order, are introduced. Furthermore, the properties for this type are investigated. Also, same applications to dynamic systems are given.
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Koordination des Wissenstransfers in Service-Netzwerken transnationaler Investitionsgüterhersteller
(2017)
IT-Compliance in KMU
(2023)
Integrität in Unternehmen
(2018)
Unternehmen stehen in der Verantwortung, eine Vielzahl an Werten in ihrem Geschäft zu beachten, allen voran den der Integrität. Das Buch beantwortet die Frage, was Integrität für Unternehmen bedeutet und wie integres Unternehmenshandeln erreicht werden kann. Die Autorin entwickelt einen theoretisch fundierten und praktisch anwendbaren Ansatz der Unternehmensintegrität und gibt Orientierung, wie dieser durch vielfältige Maßnahmen im Rahmen von Integrity Management umgesetzt werden kann. Dabei werden klassische Compliance-Ansätze um eine werteorientierte Perspektive ergänzt, damit Unternehmen ihre je eigene Verantwortung wahrnehmen können.
InnoCrowd, a Product Classification System for Design Decision in a Crowdsourced Product Innovation
(2021)
System engineering focuses on how to design and manage complex systems. Meanwhile, in the era of Industry 4.0 and Internet of Things (IoT), systems are getting more complex. Contributors to higher complexity include the usage of modern components (e.g. mechatronics), new manufacturing technologies (e.g. 3D Print) and new engineering product development processes, e.g. open innovation. Open innovation is enabled by IoT, where people and devices are easily connected, and it supports development of more innovative products through ideas gained from predecessors and collaborators world wide. Some researchers suggest this approach is up to three times faster and five times cheaper than conventional approaches [Gassmann, 2012], [Howe, 2008], [Kusumah, 2018]. Because open innovation is relatively new, many managers do not know how to employ it effectively in some phases of product development [Schenk, 2009], [Afuah, 2017], including requirements definition, design and engineering processes (task assignment) through quality assurance. Also, they have trouble estimating and controlling development time and cost [Nevo, 2020], [Thanh, 2015]. As a consequence, the acceptance of this new approach in the industry is limited. Research activities addressing this new approach mainly address high-level and qualitive issues. Few effective methods are available to estimate project risk and to decide whether to initiate a project.
We propose InnoCrowd, a decision support system that uses an improved method to support these tasks and make decisions about crowdsourced engineering product development.
InnoCrowd uses natural language processing and machine learning to build a knowledgebase of crowdsourced product developments. InnoCrowd presents a manager with results of similar projects to show which practices led to good results. A manager of a new project can use this guidance to employ best practices for product requirements definition, project schedule, and other aspects, thereby reducing risk and increasing chances for success.
Die Entwicklung der Elektromobilität, als alternative Fortbewegungsform ist seit geraumer Zeit eine nicht nur regional, sondern weltweit und unter den verschiedensten Aspekten (Technik, Umwelt, Wirtschaft, Energiewende etc.) intensiv betrachtete und untersuchte Thematik. Hierbei spielt der mögliche positive Effekt auf die Umwelt und die Energiewende hin zu nicht fossilen Energieträgern eine zentrale Rolle für Politik und Forschung bei der Förderung dieser Technologie. Die vorliegende Arbeit untersucht die Elektromobilität im Bodenseetourismus. Ziel der Arbeit ist es, die Potenziale für die Integration der Elektromobilität im Bodenseetourismus darzustellen. Hierfür wird die Elektromobilität im Bodenseetourismus als innovative Mobilitätsform postuliert, verstanden und untersucht. Die Betrachtung der Diffusion der Innovation wird vor dem Hintergrund heterogener Akteursgruppen im Dreiländereck D-A-CH untersucht.