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We identify 74 generic, reusable technical requirements based on the GDPR that can be applied to software products which process personal data. The requirements can be traced to corresponding articles and recitals of the GDPR and fulfill the key principles of lawfulness and transparency. Therefore, we present an approach to requirements engineering with regard to developing legally compliant software that satisfies the principles of privacy by design, privacy by default as well as security by design.
We consider the problem of increasing the informative value of electrocardiographic (ECG) surveys using data from multichannel electrocardiographic leads, that include both recorded electrocardiosignals and the coordinates of the electrodes placed on the surface of the human torso. In this area, we were interested in reconstruction of the surface distribution of the equivalent sources during the cardiac cycle at relatively low hardware cost. In our work, we propose to reconstruct the equivalent electrical sources by numerical methods, based on integral connection between the density of electrical sources and potential in a conductive medium. We consider maps of distributions of equivalent electric sources on the heart surface (HSSM), presenting source distributions in the form of a simple or double electrical layer. We indicate the dynamics of the heart electrical activity by the space-time mapping of equivalent electrical sources in HSSM.
Die Putzstrukturen an Fassaden werden maßgeblich durch die Fachhandwerker geprägt. Deshalb wird ihre Ebenmäßigkeit auch nie mit der von industriell gefertigten Fassadenplatten und Ähnlichem vergleichbar sein – aber genau das macht einen Teil des Charmes von Putzfassaden aus. Dies ist auch bei der Bearbeitung von Schadstellen zu berücksichtigen.
In tourism, energy demands are particularly high.Tourism facilities such as hotels require large amounts ofelectric and heating resp. cooling energy. Their supply howeveris usually still based on fossil energies. This research approachanalyses the potential of promoting renewable energies in BlackForest tourism. It focuses on a combined and hence highlyefficient production of both electric and thermal energy bybiogas plants on the one hand and its provision to local tourismfacilities via short distance networks on the other. Basing onsurveys and qualitative empiricism and considering regionalresource availability as well as socio-economic aspects, it thusexamines strengths, weaknesses, opportunities and threats thatcan arise from such a cooperation.
In tourism, energy demands are particularly high. Tourism facilities such as hotels require large amounts of electric and heating / cooling energy while their supply is usually still based on fossil energies.
This research approach analyses the potential of promoting renewable energies in tourism. It focuses on a combined and hence highly efficient production of both electric and thermal energy by biogas plants on the one hand and its provision to local tourism facilities via short distance networks on the other. Considering regional resource availability as well as socio-economic aspects, it thus examines strengths, weaknesses, opportunities and threats that can arise from such a micro-cooperation. The research aim is to provide an actor-based, spatially transferable feasibility analysis.
The overall goal of this work is to detect and analyze a person's movement, breathing and heart rate during sleep in a common bed overnight without any additional physical contact. The measurement is performed with the help of
sensors placed between the mattress and the frame. A two-stage pattern classification algorithm based has been implemented that applies statistics analysis to recognize the position of patients. The system is implemented in a sensors-network, hosting several nodes and communication end-points to support quick and efficient classification. The overall tests show convincing results for the position recognition and a reasonable overlap in matching.
Der Einsatz von Plagiatssoftware sollte auf die Zielgruppe abgestimmt sein. Da die Beurteilung des digitalen Prüfberichts Expertenwissen voraussetzt, erscheint ein unbegleiteter Zugriff nicht sinnvoll. Da meist nicht mit Betrugsabsicht, sondern aus Regelunkenntnis plagiiert wird, ist eine Beschränkung auf eine flächendeckende Detektion keine Lösung. Umfassendes Regelwissen, ein Verständnis für die grundlegende Bedeutung intertextueller Bezüge sowie selbstverantwortliches Handeln sind Vermittlungsziele der HTWG-Schreibberatung. Zu diesem Zweck macht das HTWG-Modell den Schreibkursbesuch zur Zulassungsvoraussetzung für die freiwillige Plagiatskontrolle und behält sich die Deutungshoheit über den Prüfbericht vor.
According to the World Food Organization, nearly half of all root and tuber crops worldwide are not consumed, but are lost due to inappropriate storage and post-harvest losses. In developing countries such as Ethiopia, potatoes have not been dried, but are traditionally stored in potato clamps. So far, dried potatoes have not been converted into usable foods.
The aim of the present work is to convert potatoes - perishable rootlets and tubers - into stable products by hot air drying. Hot air dryers are economical to operate in industrialized countries. In Africa, this is reserved for larger industrial companies only. In regions with a tropical climate, however, the use of solar tunnel dryers is worthwhile. These are a good choice for farming and small industries and wherever electrical energy is difficult or impossible to obtain.
In a first part of the work, the drying process of potatoes was investigated, in particular with regard to the change of thermal, mechanical and chemical quality parameters. In an evaluation of the literature it was found that potatoes are not subject to quality changes if the water activityis below a value of 0.2. In order to determine the water content associated with this value at storage temperature, the known equations for the sorption equilibrium were evaluated and verified with own experimental investigations. This determined the end point of the drying process.
The following experimental investigations showed a process-dependent change of the quality criteria such as color, shrinkage, and mechanical properties as well as the content of valuedetermining substances such as vitamin C and starch. The differences in the course and magnitude of the quality changes were attributed to the glass transition that takes place during the drying process. For the determination of the glass transition temperature a new, simple method based on the measurement of mechanical properties could be developed. The knowledge of the glass transition temperature allowed optimizing the drying process. The drying process could be carried out in the rubbery or glassy region, depending on the expected quality changes. Thus, all information was available to produce high quality dried potatoes in an industrial process.
Since the production of potato products in less industrialized regions without sufficient supply of electrical energy should be included, potatoes were dried with a solar tunnel dryer. Examination of the quality properties mentioned above confirmed the process-dependent quality changes.
Finally, the dried product was ground and with the flour thus produced, wheat flour was replaced for baking bread. An evaluation of the finished bread by a panel showed that the acceptance of the bread according to the new recipe was high, also with regard to baking volume, taste, texture and color.
This work shows that by drying potatoes can be transformed a well accepted, storable and easily transportable product. The risk of losses or degradation is minimized. It can be produced on an industrial as well as on farm level. If the influence of the glass transition is taken into account, it is possible to optimize the quality of the product.
Optical surface inspection: A novelty detection approach based on CNN-encoded texture features
(2018)
In inspection systems for textured surfaces, a reference texture is typically known before novel examples are inspected. Mostly, the reference is only available in a digital format. As a consequence, there is no dataset of defective examples available that could be used to train a classifier. We propose a texture model approach to novelty detection. The texture model uses features encoded by a convolutional neural network (CNN) trained on natural image data. The CNN activations represent the specific characteristics of the digital reference texture which are learned by a one-class classifier. We evaluate our novelty detector in a digital print inspection scenario. The inspection unit is based on a camera array and a flashing light illumination which allows for inline capturing of multichannel images at a high rate. In order to compare our results to manual inspection, we integrated our inspection unit into an industrial single-pass printing system.
A constructive nonlinear observer design for self-sensing of digital (ON/OFF) single coil electromagnetic actuators is studied. Self-sensing in this context means that solely the available energizing signals, i.e., coil current and driving voltage are used to estimate the position and velocity trajectories of the moving plunger. A nonlinear sliding mode observer is considered, where the stability of the reduced error dynamics is analyzed by the equivalent control method. No simplifications are made regarding magnetic saturation and eddy currents in the underlying dynamical model. The observer gains are constructed by taking into account some generic properties of the systems nonlinearities. Two possible choices of the observer gains are discussed. Furthermore, an observer-based tracking control scheme to achieve sensorless soft landing is considered and its closed-loop stability is studied. Experimental results for observer-based soft landing of a fast-switching solenoid valve under dry conditions are presented to demonstrate the usefulness of the approach.
Infolge des Klimawandels sind entlang der Gewässer Baden-Württembergs verschärfte Niedrigwassersituationen zu erwarten, die unter Umständen zu Wassernutzungskonflikten der lokalen Akteure führen. Anhand des Kochers und der Murg wurden mit Hilfe einer Stakeholder-Analyse solche Konflikte identifiziert sowie erste Handlungsoptionen für eine Niedrigwasservorsorge bzw. ein Niedrigwassermanagement erarbeitet. Den Erhebungen zufolge treten Wassernutzungskonkurrenzen in fast allen Nutzergruppen auf, jedoch mit unterschiedlicher Ausprägung. Hierbei stehen bestimmte Sektoren teilweise mit mehreren Stakeholder-Gruppen im Widerstreit, andere Gruppen haben dagegen keine Erfahrung mit Konkurrenzsituationen. Weiterhin ist auffällig, dass Niedrigwasserereignisse an beiden Flüssen lediglich einen Teil der Nutzungskonflikte auslösen. Ein Großteil der Streitfragen wird durch anthropogene Einflüsse verursacht.
Sleep study can be used for detection of sleep quality and in general bed behaviors. These results can helpful for regulating sleep and recognizing different sleeping disorders of human. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this work is a non-invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable Actigraphy devices tends to be uncomfortable. Besides, these methods not only decrease practicality due to the process of having to put them on, but they are also very expensive. The system proposed in this paper classifies respiration and body movement with only one type of sensor and also in a noninvasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed excellent results in the classification of breathing rate and body movements.
Der Bodensee und das in ihm gespeicherte Wasser dient vielen Zwecken: Neben seiner ökologischen Bedeutung für die Region ist er Trinkwasserquelle und Schifffahrtsweg, wird für Freizeit und Naherholung genutzt. Die Schifffahrt stellt eine der zentralen Attraktionen am Bodensee dar – sie zieht Tagesausflügler und Naherholungssuchende ebenso an wie Urlauber. Der Tourismus ist dabei eine der zentralen Einkommensquellen am Bodensee. Während der Niedrigwasserereignisse der letzten Jahre wurden jedoch die verschiedenen Schifffahrtstypen beeinträchtigt. Dies traf den Tourismus wie auch Berufspendler, Häfen, anliegende Gemeinden und den Gütertransport. Der Beitrag verdeutlicht die Bedeutung der Bodenseeschifffahrt und nennt einige Folgen der Niedrigwasserereignisse der letzten Jahre.
Product development and product manufacturing are entering a new era, namely an era where engineering tasks are executed under collaboration of all involved parties. Engineers and potential customers work together mainly in a virtual world for the design and realization of the product. We address this so called “crowdsourcing” trend in the automotive industry that lowers cost and accelerates production of new car. Current practice and prior studies fail to handle data management and collaboration aspects in sufficient detail. We propose a PLM based crowdsourcing platform that applies best practices to the established approach and adapt it with new methods for handling specific requirements. Our work provides a basis for establishing an improved collaboration platform to support a Gig Economy in the automotive industry.
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.
This paper focuses on the multivariable control of a drawing tower process. The nature of the process together with the differences in measurement noise levels that affect the variables to be controlled motivated the development of a new MPC algorithm. An extension of a multivariable predictive control algorithm with separated prediction horizons is proposed. The obtained experimental results show the usefulness of the proposed algorithm..
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.
Offline handwriting recognition systems often use LSTM networks, trained with line- or word-images. Multi-line text makes it necessary to use segmentation to explicitly obtain these images. Skewed, curved, overlapping, incorrectly written text, or noise can lead to errors during segmentation of multi-line text and reduces the overall recognition capacity of the system. Last year has seen the introduction of deep learning methods capable of segmentation-free recognition of whole paragraphs. Our method uses Conditional Random Fields to represent text and align it with the network output to calculate a loss function for training. Experiments are promising and show that the technique is capable of training a LSTM multi-line text recognition system.
Embodiments are generally related to the field of channel and source coding of data to be sent over a channel, such as a communication link or a data memory. Some specific embodiments are related to a method of encoding data for transmission over a channel, a corresponding decoding method, a coding device for performing one or both of these methods and a computer program comprising instructions to cause said coding device to perform one or both of said methods.
Mauermörtel und Putze
(2018)
It is widely recognized that sustainability is a new challenge for many manufacturing companies. In this paper, we tackle this issue by presenting an approach that deals with material and substance compliance within Product Lifecycle Management in a complex value chain. Our analysis explains why, how and when sustainable manufacturing arises, and it identifies, quantifies and evaluates the environmental impact of a new product. We propose (I) a Life Cycle Assessment tool (LCA) and (II) a model to validate this approach and evaluate the risk of noncompliance in supply chain. Our LCA approach provides comprehensive information on environmental impacts of a product.
Product and materials cycles are parallel and intersecting, making it challenging to integrate Material Selection Process across Product Lifecycle Management, Integration of LCA with PLM. We provide only a foundation. Further research in systems engineering is necessary. LCA is sensitive to data quality. Outsourcing production and having problems in supplier cooperation can result in material mismatch (such as property, composition mismatching) in the production process due to that may cause misleading of LCA results.
This paper also describes research challenges using riskbased due diligence.
It is widely recognized that sustainability is a new challenge for many manufacturing companies. In this paper, we tackle this issue by presenting an approach that deals with material and substance compliance within Product Lifecycle Management in a complex value chain. Our analysis explains why, how and when sustainable manufacturing arises, and it identifies, quantifies and evaluates the environmental impact of a new product. We propose (I) a Life Cycle Assessment tool (LCA) and (II) a model to validate this approach and evaluate the risk of non-compliance in supply chain. Our LCA approach provides comprehensive information on environmental impacts of a product.
Product and materials cycles are parallel and intersecting, making it challenging to integrate Material Selection Process across Product Lifecycle Management, Integration of LCA with PLM. We provide only a foundation. Further research in systems engineering is necessary. LCA is sensitive to data quality. Outsourcing production and having problems in supplier cooperation can result in material mismatch (such as property, composition mismatching) in the production process due to that may cause misleading of LCA results. This paper also describes research challenges using risk-based due diligence.
Marketingrecht
(2018)
Dieses Buch legt eine umfassende Gesamtdarstellung des Marketingrechts vor und sensibilisiert für mögliche Rechtsprobleme im Marketing. Verantwortliche im Marketingmanagement, die Entscheidungen oft auch schnell treffen müssen, werden hier mit den Grundlagen rechtlicher Rahmenbedingungen vertraut gemacht. Der marketingspezifische Aufbau und die Entscheidungsorientierung gewährleisten dem Marketingmanagement als Hauptzielgruppe einen hohen Praxisnutzen. Der Leser erhält wertvolle Hinweise, wie er im Marketing effektiver und zielgerichteter mit der Rechtsabteilung oder externen Rechtsberatern kommunizieren kann.
Algorithms for calculating the string edit distance are used in e.g. information retrieval and document analysis systems or for evaluation of text recognizers. Text recognition based on CTC-trained LSTM networks includes a decoding step to produce a string, possibly using a language model, and evaluation using the string edit distance. The decoded string can further be used as a query for database search, e.g. in document retrieval. We propose to closely integrate dictionary search with text recognition to train both combined in a continuous fashion. This work shows that LSTM networks are capable of calculating the string edit distance while allowing for an exchangeable dictionary to separate learned algorithm from data. This could be a step towards integrating text recognition and dictionary search in one deep network.
This work proposes a construction for low-density parity-check (LDPC) codes over finite Gaussian integer fields. Furthermore, a new channel model for codes over Gaussian integers is introduced and its channel capacity is derived. This channel can be considered as a first order approximation of the additive white Gaussian noise channel with hard decision detection where only errors to nearest neighbors in the signal constellation are considered. For this channel, the proposed LDPC codes can be decoded with a simple non-probabilistic iterative decoding algorithm similar to Gallager's decoding algorithm A.
Knot placement for curve approximation is a well known and yet open problem in geometric modeling. Selecting knot values that yield good approximations is a challenging task, based largely on heuristics and user experience. More advanced approaches range from parametric averaging to genetic algorithms.
In this paper, we propose to use Support Vector Machines (SVMs) to determine suitable knot vectors for B-spline curve approximation. The SVMs are trained to identify locations in a sequential point cloud where knot placement will improve the approximation error. After the training phase, the SVM can assign, to each point set location, a so-called score. This score is based on geometric and differential geometric features of points. It measures the quality of each location to be used as knots in the subsequent approximation. From these scores, the final knot vector can be constructed exploring the topography of the score-vector without the need for iteration or optimization in the approximation process. Knot vectors computed with our approach outperform state of the art methods and yield tighter approximations.
We propose a novel end-to-end neural network architecture that, once trained, directly outputs a probabilistic clustering of a batch of input examples in one pass. It estimates a distribution over the number of clusters k, and for each 1≤k≤kmax, a distribution over the individual cluster assignment for each data point. The network is trained in advance in a supervised fashion on separate data to learn grouping by any perceptual similarity criterion based on pairwise labels (same/different group). It can then be applied to different data containing different groups. We demonstrate promising performance on high-dimensional data like images (COIL-100) and speech (TIMIT). We call this “learning to cluster” and show its conceptual difference to deep metric learning, semi-supervise clustering and other related approaches while having the advantage of performing learnable clustering fully end-to-end.
Im Sinne einer dialogischen, transdisziplinären Auseinandersetzung zwischen künstlerischer Praxis, Kultur- und Ingenieurwissenschaften geht es bei diesem Projekt um die Entwicklung einer künstlerisch-wissenschaftlichen Fallstudie mit den Zielen der konkreten Erarbeitung eines Kunstwerks unter den Bedingungen digitaler Medien - und um eine Befragung dieser Medien aus der Perspektive der
künstlerischen Praxis, der Interfacegestaltung und der Entwurfswissenschaften (Teil der UDK Berlin).
Bericht aus dem Freistellungssemester Sommer 2018
Know when you don't know
(2018)
Deep convolutional neural networks show outstanding performance in image-based phenotype classification given that all existing phenotypes are presented during the training of the network. However, in real-world high-content screening (HCS) experiments, it is often impossible to know all phenotypes in advance. Moreover, novel phenotype discovery itself can be an HCS outcome of interest. This aspect of HCS is not yet covered by classical deep learning approaches. When presenting an image with a novel phenotype to a trained network, it fails to indicate a novelty discovery but assigns the image to a wrong phenotype. To tackle this problem and address the need for novelty detection, we use a recently developed Bayesian approach for deep neural networks called Monte Carlo (MC) dropout to define different uncertainty measures for each phenotype prediction. With real HCS data, we show that these uncertainty measures allow us to identify novel or unclear phenotypes. In addition, we also found that the MC dropout method results in a significant improvement of classification accuracy. The proposed procedure used in our HCS case study can be easily transferred to any existing network architecture and will be beneficial in terms of accuracy and novelty detection.