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The aim of this paper is to show to what extent Artificial Intelligence can be used to optimize forecasting capability in procurement as well as to compare AI with traditional statistic methods. At the same time this article presents the status quo of the research project ANIMATE. The project applies Artificial Intelligence to forecast customer orders in medium-sized companies.
Precise forecasts are essential for companies. For planning, decision making and controlling. Forecasts are applied, e.g. in the areas of supply chain, production or purchasing. Medium-sized companies have major challenges in using suitable methods to improve their forecasting ability.
Companies often use proven methods such as classical statistics as the ARIMA algorithm. However, simple statistics often fail while applied for complex non-linear predictions.
Initial results show that even a simple MLP ANN produces better results than traditional statistic methods. Furthermore, a baseline (Implicit Sales Expectation) of the company was used to compare the performance. This comparison also shows that the proposed AI method is superior.
Until the developed method becomes part of corporate practice, it must be further optimized. The model has difficulties with strong declines, for example due to holidays. The authors are certain that the model can be further improved. For example, through more advanced methods, such as a FilterNet, but also through more data, such as external data on holiday periods.
Ever since the 1980s, researchers in computer science and robotics have been working on making autonomous cars. Due to recent breakthroughs in research and devel- opment, such as the Bertha Benz Project [ZBS+14], the goal of fully autonomous vehicles seems closer than ever before. Yet a lot of questions remain unanswered. Especially now that the automotive industry moves towards autonomous systems in series production vehicles, the task of precise localization has to be solved with automotive grade sensors and keep memory and processing consumption at a mini- mum. This thesis investigates the Simultaneous Localization and Mapping (SLAM) prob- lem for autonomous driving scenarios on a parking lot using low cost automotive sensors. The main focus is herby devoted to the RAdio Detection And Ranging (RADAR) sensor, which has not been widely analyzed in an autonomous driving scenario so far, even though they are abundant in the automotive industry for ap- plications such as Adaptive Cruise Control (ACC). Due to the high noise floor, the radar sensor has widely been disregarded in the Intelligent Transportation Systems and Robotics communities with regards to SLAM applications. However in this thesis, it is shown that the RADAR sensor proves to be an affordable, robust and precise sensor, when modeling its physical properties correctly. In this regard, a GraphSLAM based framework is introduced, which extracts features from the RADAR sensor and generates an optimized map of the surroundings using the RADAR sensor alone. This framework is used to enable crowd based localization, which is not limited to the RADAR sensor alone. By integrating an automotive Light Detection and Ranging (LiDAR) and stereo camera sensor, a robust and precise localization system can be built that that is suitable for autonomous driving even in complex parking lot scenarios. It it is thereby shown that the RADAR sensor is strongly contributing to obtaining good results in a sensor fusion setup. These results were obtained on an extensive dataset on a parking lot, which has been recorded over the course of several months. It contains different weather conditions, different configurations of parked cars and a multitude of different trajectories to validate the approaches described in this thesis and to come to the conclusion that the RADAR sensor is a reliable sensor in series autonomous driving systems, both in a multi sensor framework and as a single component for localization.
The digital age makes it possible to be globally networked at any time. Digital communication is therefore an important aspect of today’s world. Hence, the further development and expansion of this is becoming increasingly important. Even within a wireless system, copper channels are important as part of the overall network. Given the need to keep pushing at the current limitations, careful design of the cables in connection with an adapted coding of the bits is essential to transmit more and more data.
One of the most popular and widespread cabling technologies is symmetrical copper cabling [1, pp. 8-15]. It is also known as Twisted Pair and it is of immense importance for the cabling of communication networks.
At the time of writing this thesis, data rates of up to 10 GBit/s over a transmission distance of 100 m and 40 GBit/s over a transmission distance of 30 m are standardized for symmetrical copper cabling [2]. Other lengths are not standardized. Short lengths in particular are of great interest for copper cables, because copper cables are usually used for short distances, such as between computers and the campus network or within data centres.
This work has focused on the transmission of higher order Pulse Amplitude Modulation and the associated transmission performance. The central research question is:“how well can we optimize the transmission technique in order to be able to maximise the data bandwidth over Ethernet cable and, given that remote powering is also a significant application of these cables, how much will the resulting heating affect this transmission and what can be done to mitigate that?”
To answer this question, the cable parameters are first examined. A series of spectral measurements, such as Insertion Loss, Return Loss, Near End Crosstalk and Far End Crosstalk, provide information about the electromagnetic interference and the influence of the ohmic resistance on the signal. Based on these findings, the first theoretical statements and calculations can be made. In the next step, data transmissions over different transmission lengths are realized. The examination of the eye diagrams of the different transmission approaches ultimately provides information about the signal quality of the transmissions. An overview of the maximum transmission rate depending on the transmission distance shows the potential for different applications.
Furthermore, the simultaneous transmission of energy and data is a significant advantage of copper. However, the resulting heat development has an influence on the data transmission. Therefore, the influence of the ambient temperature of cables is investigated in the last part and changes in the signal quality are clarified.
Frost reduction in mechanical balanced ventilation by efficient means of preheating cold supply air
(2019)
This study has focused on evaluating the financial potential of wastewater and geothermal heat recovery systems in a multi-family building. The recovered heat was used to improve the performance of mechanical ventilation with heat recovery (MVHR) system during the coldest days in central Sweden. The main issue, which was targeted with these solutions, was to reduce frost formation in the system and hence increase its thermal efficiency. By looking at the life cycle cost over a lifespan of 20 years, the observed systems were being evaluated economically. Furthermore, statistical analyses were carried-out to counter the uncertainty that comes with the calculation. It was found that the studied wastewater systems have a high possibility of generating savings in this period, while the one fed by geothermal energy is less likely to compensate for its high initial cost. All designed systems however, managed to reduce operational cost by 35-45% due to lower energy usage.
The aim of this work was to investigate the mean fill weight control of a continuous capsule-filling process, whether it is possible to derive controller settings from an appendant process model. To that end, a system composed out of fully automated capsule filler and an online gravimetric scale was used to control the filled weight. This setup allows to examine challenges associated with continuous manufacturing processes, such as variations in the amount of active pharmaceutical ingredient (API) in the mixture due to fluctuations of the feeders or due to altered excipient batch qualities. Two types of controllers were investigated: a feedback control and a combination of feedback and feedforward control. Although both of those are common in the industry, determining the optimal parameter settings remains an issue. In this study, we developed a method to derive the control parameters based on process models in order to obtain optimal control for each filled product. Determined via rapid automated process development (RAPD), this method is an effective and fast way of determining control parameters. The method allowed us to optimize the weight control for three pharmaceutical excipients. By conducting experiments, we verified the feasibility of the proposed method and studied the dynamics of the controlled system. Our work provides important basic data on how capsule filler can be implemented into continuous manufacturing systems.
Most antimicrobial peptides (AMPs) and their synthetic mimics (SMAMPs) are thought to act by permeabilizing cell membranes. For antimicrobial therapy, selectivity for pathogens over mammalian cells is a key requirement. Understanding membrane selectivity is thus essential for designing AMPs and SMAMPs to complement classical antibiotics in the future. This study focuses on membrane permeabilization induced by SMAMPs and their selectivity for membranes with different lipid compositions. We measure release and fluorescence lifetime of a self-quenching dye in lipid vesicles. Apart from the dose-response, we quantify the strength of individual leakage events, and, employing cumulative kinetics, categorize permeabilization behavior. We propose that differing selectivities in a series of SMAMPs arise from a combination of the effect of the antimicrobial agent and the susceptibility of the membrane (with a given lipid composition) for certain types of leakage behavior. The unselective and hemolytic SMAMP is found to act mainly by the asymmetry stress mechanism, mediated by hydrophobic insertion of SMAMPs into lipid layers. The more selective SMAMPs induced leakage events occurring stochastically over several hours. Lipid intrinsic properties might additionally amplify the efficiency of leakage events. Leakage behavior changes with both the design of the SMAMP and the lipid composition of the membrane. Understanding how leakage behavior contributes to the selectivity and activity of antimicrobial agents will aid the design and screening of antimicrobials. An understanding of the underlying processes facilitates the comparison of membrane permeabilization across in vitro and in vivo assays.
Digitalization changes the manufacturing dramatically. In regard of employees’ demands, global trends and the technological vision of future factories, automotive manufacturing faces a huge number of diverse challenges. Currently, research focuses on technological aspects of future factories in terms of digitalization. New ways of work and new organizational models for future factories have not been described yet. There are assumptions on how to develop the organization of work in a future factory but up to now, literature shows deficits in scientifically substantiated answers in this research area. Consequently, the objective of this paper is to present an approach on a work organization design for automotive Industry 4.0 manufacturing. Future requirements were analyzed and deducted to criteria that determine future agile organization design. These criteria were then transformed into functional mechanisms, which define the approach for shopfloor organization design
In spite of many studies, knowledge about the fundamental factors influencing adhesion between addition curing silicones and aluminum substrates is very limited. The aim of this publication is to evaluate the influence of the formulation and the surface state of the adherend on bond strength. For this purpose, the composition of an addition curing silicone was systematically varied and the effects on both material and bond properties were examined. Additionally, the influence of surface aging at different humidities (0% r. h., 34% r. h., 82% r. h.) of acid etch pretreated aluminum substrates was considered. It is shown that the mechanical properties of the silicone material can be easily adjusted over a wide range by changing the formulation. Although high tensile strengths up to 9.2 MPa for the silicone material can be achieved, lap-shear strengths remain moderate at approximately 3.5 MPa. Predominant adhesive failures show the limited adhesive strength of the basic formulation without additives. Basic ingredients of addition curing silicones without additives are able to reach a certain adhesive strength. However, this strength was quite limited and adhesion promoters are required to further improve adhesion. The humidity at which the pretreated substrates are stored has an overall minor influence on bond strength. Surprisingly, bond strength tends to increase with the storage time of aluminum substrates despite lower surface energies in comparison to freshly pretreated substrates. All in all, the storage conditions of aluminum had a rather small influence on adhesion, whereas the composition of the silicone adhesive strongly influences bond strength.
In addition to increased safety by detecting possible overload, continuous component monitoring by sensor integration makes the use of fiber reinforced plastics more cost-effective. Since the components are continuously monitored, one can switch from time-based to condition-based maintenance. However, the integration of conventional sensor components causes weak points, as foreign objects are inserted into the reinforcing structure. In this paper, we examine the use of the textile reinforcement as a sensor in itself. We describe how bending sensors can be formed by slightly modifying in the composite’s reinforcement structure. We investigated two different sensor principles. (1) The integration of textile plate capacitors into the structure; (2) The construction of textile piezo elements as part of the reinforcing structure. The bending test results reveal that textile plate capacitors show a load-dependent signal output. The samples with textile piezo elements show a significant increase in signal strength.
Im Frühjahr 1817 unternahm der damalige Professor Friedrich List an der Universität Tübingen eine Reise nach Frankfurt a. M., wo zu dieser Zeit die berühmte Ostermesse stattfand. Dort traf er mit den Anführern der Kaufleute zusammen, die darüber klagten, dass die zaghafte wirtschaftliche Entwicklung unter den vielen Zollschranken und den Billigimporten aus England stark zu leiden habe. Deshalb forderten sie die Abschaffung der Binnenzölle und die Bildung einer Wirtschaftsunion. Im Auftrag der Kaufleute verfasste List seine berühmt gewordene Petition an die Bundesversammlung, die lose Interessenvertretung des Deutschen Bundes in Frankfurt. Als die Petition mit großem Beifall aufgenommen wurde, gründete List im Hochgefühl seines Erfolges spontan den "Allgemeinen Deutschen Handels- und Gewerbsverein" – die erste Interessenvertretung deutscher Kaufleute. Er legte damit den Grundstein für den politischen Prozess zur Gründung des Zollvereins von 1834, der wiederum die Vorstufe zur Gründung des Deutschen Reiches von 1871 bildete. Lists damalige Forderungen sind zurzeit wieder hoch aktuell.
Exogenous factors of influence on exhaled breath analysis by ion-mobility spectrometry (MCC/IMS)
(2019)
The interpretation of exhaled breath analysis needs to address to the influence of exogenous factors, especially to a transfer of confounding analytes by the test persons. A test person who was exposed to a disinfectant had exhaled breath analysis by MCC/IMS (Bioscout®) after different time intervals. Additionally, a new sampling method with inhalation of synthetic air before breath analysis was tested. After exposure to the disinfectant, 3-Pentanone monomer, 3-Pentanone dimer, Hexanal, 3-Pentanone trimer, 2-Propanamine, 1-Propanol, Benzene, Nonanal showed significantly higher intensities, in exhaled breath and air of the examination room, compared to the corresponding baseline measurements. Only one ingredient of the disinfectant (1-Propanol) was identical to the 8 analytes. Prolonging the time intervals between exposure and breath analysis showed a decrease of their intensities. However, the half-time of the decrease was different. The inhalation of synthetic air - more than consequently airing the examination room with fresh air - reduced the exogenous and also relevant endogenous analytes, leading to a reduction and even changing polarity of the alveolar gradient. The interpretation of exhaled breath needs further knowledge about the former residence of the proband and the likelihood and relevance of the inhalation of local, site-specific and confounding exogenous analytes by him. Their inhalation facilitates a transfer to the examination room and a detection of high concentrations in room air and exhaled breath, but also the exhalation of new analytes. This may lead to a misinterpretation of these analytes as endogenous resp. disease-specific ones.
Standardisation of breath sampling is important for application of breath analysis in clinical settings. By studying the effect of room airing on indoor and breath analytes and by generating time series of room air with different sampling intervals we sought to get further insights into room air metabolism, to detect the relevance of exogenous VOCs and to make conclusions about their consideration for the interpretation of exhaled breath. Room air and exhaled breath of a healthy subject were analysed before and after room airing. Furthermore a time series of room air with doors and windows closed was taken over 84 h by an automatic sampling every 180 min. A second times series studied room air analytes over 70 h with samples taken every 16.5 min. For breath and room air measurements an IMS coupled to a multi-capillary column (IMS/MCC) [Bio-Scout® - B&S Analytik GmbH, Dortmund, Germany] was used. The peaks were characterized using the Software Visual Now (B&S Analytik, Dortmund Germany) and identified using the software package MIMA (version 1.1, provided by the Max Planck Institute for Informatics, Saarbrücken, Germany) and the database 20160426_SubstanzDbNIST_122 (B & S Analytik GmbH, Dortmund, Germany). In the morning 4 analytes (Decamethylcylopentasiloxane [541-02-6]; Pentan-2-one [107-87-9] – Dimer; Hexan-1-al [66-25-1]; Pentan-2-one [107-87-9]) – Monomer showed high intensities in the room air and exhaled breath. They were significantly but not equally reduced by room airing. The time series about 84 h showed a time dependent decrease of analytes (limonen-monomer and -dimer; Decamethylcylopentasiloxane, Butan-1-ol, Butan-1-ol) as well as increase (Pentan-2-one [107-87-9] – Dimer). Shorter sampling intervals exhibited circadian variations of analyte concentrations for many analytes. Breath sampling in the morning needs room airing before starting. Then the variation of the intensity of indoor analytes can be kept small. The time series of indoor analytes show, that their intensities have a different behaviour, with time dependent declines, constant increases and circadian variations, dependent on room airing. This has implications on the breath sampling procedure and the intrepretation of exhaled breath.
Woven piezoelectric sensors as part of the textile reinforcement of fiber reinforced plastics
(2019)
Sensor integration in fiber reinforced plastic (FRP) structures enables online process and structural health monitoring (SHM). This paper describes the development and application of woven fabric-based piezoelectric impact and bending sensors for integration into FRP. The work focuses on design and characterization of woven piezoelectric sensors, especially as a part of the reinforcement structure. The reinforcement of the component acts as a sensor in itself and therefore no additional external objects in the form of sensor components or sensor fibers, which could create unwanted weak points within the FRP, are added. The bending test results reveal a direct relationship between the applied load and the sensor signal. Furthermore, the appropriate sensor position in the component cross section was determined and the influence of thermal polarization on the sensor properties was investigated.
We propose a method for recognizing dynamic gestures using a 3D sensor. New aspects of the developed system include problem-adapted data conversion and compression as well as automatic detection of different variants of the same gesture via clustering with a suitable metric inspired by Jaccard metric. The combination of Hidden Markov Models and clustering leads to robust detection of different executions based on a small set of training data. We achieved an increase of 5% recognition rate compared to regular Hidden Markov Models. The system has been used for human-machine interaction and might serve as an assistive system in physiotherapy and neurological or orthopedic diagnosis.
Urban platforms are essential for smart and sustainable city planning and operation. Today they are mostly designed to handle and connect large urban data sets from very different domains. Modelling and optimisation functionalities are usually not part of the cities software infrastructure. However, they are considered crucial for transformation scenario development and optimised smart city operation. The work discusses software architecture concepts for such urban platforms and presents case study results on the building sector modelling, including urban data analysis and visualisation. Results from a case study in New York are presented to demonstrate the implementation status.
Der Halo-Effekt im Fußball
(2019)
Der Halo-Effekt ist eine aus der Sozialpsychologie bekannte kognitive Verzerrung. Ein Halo-Effekt tritt dann auf, wenn ein globaler Eindruck oder eine Information über ein hervorstechendes Merkmal die Beurteilung anderer Eigenschaften prägt. Im vorliegenden Beitrag wird der Frage nachgegangen: Gibt es einen Halo-Effekt im Fußball? Überstrahlt der sportliche Erfolg bzw. Misserfolg die Wahrnehmung der Fans womöglich sogar hinsichtlich nicht-sportlicher Aspekte? Der Beitrag gibt den aktuellen Stand zur Halo-Forschung wider und präsentiert die Ergebnisse einer empirischen Untersuchung, in deren Rahmen Fans von Vereinen aus der deutschen Fußball-Bundesliga befragt werden.
Additive manufacturing (AM) is a promising manufacturing method for many industrial sectors. For this application, industrial requirements such as high production volumes and coordinated implementation must be taken into account. These tasks of the internal handling of production facilities are carried out by the Production Planning and Control (PPC) information system. A key factor in the planning and scheduling is the exact calculation of manufacturing times. For this purpose we investigate the use of Machine Learning (ML) for the prediction of manufacturing times of AM facilities.
Computers are increasingly used in teams in various contexts, for example in negotiations. Especially when using computer-support for decision making processes, it is an important question whether active collaboration within the team - for example via audio-conference - has additional benefits beyond the supply of full task-relevant information via computer. In team negotiations, team representatives are only able to represent the whole team, if diverse preferences of the team members are aligned prior to the negotiation. In an experimental study with 150 participants, we provided team members with the complete information about each other's preferences during an either collaboratively (computer-mediated) or seperately conducted computer-supported negotiation preparation and subsequently asked them for their priorities as representatives of the team. Our results showed that providing complete task-relevant information via computer is insufficient to compensate for the absence of active collaboration within the team.
Die Erfindung betrifft ein Verfahren zur extrinsischen Kalibrierung wenigstens eines bildgebenden Sensors, wonach eine Pose des wenigstens einen bildgebenden Sensors relativ zu dem Ursprung (U) eines dreidimensionalen Koordinatensystems einer Handhabungseinrichtung mittels einer Recheneinrichtung bestimmt wird, wobei bekannte dreidimensionale Koordinaten betreffend die Position wenigstens eines Gelenks der Handhabungseinrichtung durch die Recheneinrichtung berücksichtigt werden, und wobei zweidimensionale Koordinaten betreffend die Position des wenigstens einen Gelenks anhand von Rohdaten des wenigstens einen bildgebenden Sensors ermittelt werden, und wobei die Recheneinrichtung die Pose des wenigstens einen bildgebenden Sensors anhand der Korrespondenz zwischen den zweidimensionalen Koordinaten und den dreidimensionalen Koordinaten bestimmt.
Als einer der ersten Wissenschaftler hat der Strategieprofessor Michael Porter die aus der Volkswirtschaftslehre stammenden Erkenntnisse der Industrieökonomik mit Konzepten der Unternehmensstrategie kombiniert, um ein genaueres Verständnis vom Einfluss des Branchenwettbewerbs auf den Unternehmenserfolg sowie von Wettbewerbsentscheidungen zu erlangen. In all seinen Arbeiten steckt der Kerngedanke, durch die Wahl einer geeigneten Strategie, Wert zu generieren und somit eine hohe Wettbewerbsfähigkeit und Profitabilität zu erzielen. Porters Themen weisen dabei eine große inhaltliche Vielfalt auf: von der Digitalisierung, über Wettbewerb in der Politik bis hin zum gesellschaftlichen Fortschritt. Typisch für Porter ist ein ganzheitlicher Forschungsansatz, der sich anstelle einzelner Bestandteile eines Systems der umfassenden Betrachtung komplexer Systeme widmet. Hieraus leitet er anhand zahlreicher Fallstudien und Praxisbeispiele Modelle ab, die Managern als Spielregeln für den Wettbewerb dienen. Mit seinen Werken liefert er nicht nur Impulse für die Wissenschaft, sondern er versucht vor allem, das Denken und Handeln von Unternehmenspraxis, Politik und Gesellschaft nachhaltig zu beeinflussen. Seine Modelle, wie beispielsweise das Fünf-Kräfte-Modell, sind im Hinblick auf die Entwicklung von Organisationen dafür bekannt, dass Manager die marktseitigen Einflüsse auf die Wettbewerbssituation ihres Unternehmens besser verstehen und entsprechend ihre strategischen Entscheidungen treffen können.
This study describes a non-contact measuring and system identification procedure for evaluating inhomogeneous stiffness and damping characteristics of the annular ligament in the physiological amplitude and frequency range without the application of large static external forces that can cause unnatural displacements of the stapes. To verify the procedure, measurements were first conducted on a steel beam. Then, measurements on an individual human cadaveric temporal bone sample were performed. The estimated results support the inhomogeneous stiffness and damping distribution of the annular ligament and are in a good agreement with the multiphoton microscopy results which show that the posterior-inferior corner of the stapes footplate is the stiffest region of the annular ligament.
Dieser Bericht fasst die wesentlichen Arbeiten und Ergebnisse zusammen, die in dem Verbundvorhaben „GalvanoFlex_BW“ im Kalenderjahr 2018 durchgeführt und erzielt wurden. Dazu lässt sich zunächst sagen, dass die Messwertaufnahme und –auswertung abgeschlossen ist. Es wurden verschiedene Messkampagnen bei der Fa. NovoPlan durchgeführt. Bei C&C Bark konnte man teilweise auf bestehende Daten zurückgreifen, die punktuell durch weitere Messungen ergänzt wurden. Bei der Fa. Hartchrom konnten aufgrund von Personalmangel keine Messungen durchgeführt werden. Die aufgenommenen Daten wurden in eine Effizienzbewertung überführt, aus der im Folgenden allgemeine Aussagen abgeleitet werden sollen. Dazu ist ein Simulationsprogramm aufgesetzt worden, das in der Lage ist, Prozessketten energetisch abzubilden und zu optimieren. Zudem sollen aus den Messdaten verbesserte Profile für den Wärmebedarf in den Unternehmen entwickelt werden, die daraufhin der KWK-Optimierung zur Verfügung gestellt werden. Im Zuge der Entwicklung und Bewertung stromoptimierter KWK- Strategien ist ein bestehendes Simulationsmodell entsprechend weiterentwickelt worden. Konkret wurde das Modell um eine verbesserte Lastprognose für Strom und Wärme für Industriebetriebe ergänzt, und das Optimierungsverfahren wurde um eine zweite Dimension erweitert. Während bislang allein die Optimierung der Eigenstromdeckung mit einer Begrenzung der BHKW-Starts als Nebenbedingung möglich war, ist jetzt die Kappung der elektrischen Lastspitze zusätzlich in der Zielfunktion integriert. Gerade bei Industrieunternehmen lässt sich auf diese Weise eine weitere, zum Teil nicht unerhebliche Energiekosteneinsparung erreichen, was durch die ersten Berechnungen anhand der drei im Reallabor vertretenden Betriebe bestätigt wird. Die Ergebnisse werden unter AP 8 (Umsetzung) diskutiert. Der Dialog mit weiteren Unternehmen und Institutionen außerhalb des Vorhabens konnte über die Branchenplattfom weitergeführt werden. In 2018 wurden zwei Veranstaltungen dieser Art durchgeführt, und im Frühjahr 2019 wird ein weiterer Workshop zu diesem Thema durchgeführt. Die sozialwissenschaftliche Begleitforschung wurde mit der zweiten Phase der Firmenbefragungen ebenfalls planmäßig weitergeführt. Mit Blick auf die Umsetzung eines BHKW-Konzeptes haben sich dabei zwei wichtige Punkte wie folgt gezeigt: Zum einen muss die umsetzende Firma eine gewisse „Energieeffizienz-Reife“ besitzen, die sich u.a. in der Erfahrung bei der Durchführung von Energieeffizienzmaßnahmen zeigt, da die Installation eines BHKWs eine äußerst komplexe Maßnahme darstellt. Zum anderen müssen andere unternehmensspezifische Kontextfaktoren hinzukommen, wie z.B. aus anderen Gründen durchzuführende bauliche Maßnahmen, so dass gewisse zeitliche Entscheidungsfenster entstehen, in denen die Umsetzung von KWK-Maßnahmen sinnvoll sind.
IC layout automation with self-organized wiring and arrangement of responsive modules (SWARM)
(2019)
Focused on automating analog IC layout, the multi-agent-system Self-organized Wir ing and Arrangement of Responsive Modules (SWARM) combines the powers of pro-cedural generators and algorithmic optimization into a novel bottom-up meets top-down flow of supervised layout module interaction. Provoking self-organization via the effect of emergence, examples show SWARM finding even optimal placement solutions and producing constraint-compliant layout blocks which fit into a specified zone.
Das Pariser Klimaschutzabkommen von 2015 fordert die Begrenzung der globalen Erwärmung auf "deutlich unter" 2 Grad Celsius gegenüber der vorindustriellen Zeit. Zwar wurde es von der internationalen Staatengemeinschaft anerkannt, jedoch reichen die national festgelegten Beiträge (NDCs) bisher nicht aus, um das Ziel zu erreichen. Neben der "Emissionslücke" besteht eine große Kluft zwischen naturwissenschaftlichem und öffentlichem Verständnis über den Klimawandel. Während die Besorgnis über den Klimawandel steigt, sehen die meisten Menschen den Klimawandel nicht als ernsthafte Bedrohung für sich selbst und Ansichten über den Klimawandel sind politisch polarisiert. Konventionelle Kommunikationsansätze haben die Lücke zwischen dem wissenschaftlichen und öffentlichen Verständnis über die durch den Klimawandel entstehenden Bedrohungen nicht geschlossen. Hier wird mit dem simulationsbasierten Rollenspiel World Climate ein innovativer Ansatz für die Klimakommunikation vorgestellt: ein soziales, einnehmendes Rollenspiel bei der Entscheidungsfindung im Klimaschutz ist mit einem interaktiven Computermodell kombiniert, das eine sofortige Rückmeldung über die erwarteten Ergebnisse von Entscheidungen liefert. Die Teilnehmenden erfahren mehr über den Klimawandel und erleben sogleich die soziale Dynamik der Verhandlungen. In diesem Beitrag werden die Ergebnisse einer Studie über Auswirkungen von World Climate präsentiert.
The paper analyses the importance of List's views on growth and integration from the perspective of modern approaches to economic growth and international economics. Furthermore, some ideas will be presented on how List's ideas could help to explain and understand current economic developments, such as the crisis of the European Union or the new form of isolationism of the United States of America.
The economic thought of Friedrich List. - (Routledge studies in the history of economics ; 16)
(2019)
Friedrich List is, besides Karl Marx, one of the most important economists of the 19th century in Germany. Probably most modern economists know List for his idea of educational tariffs that protect infant industries from international competition an help them to become competitive before their country opens the domestic market for foreign rivals. Furthermore, List is still popular because of his contribution to establishing a railway system in the USA and Germany. However, a closer look at his work reveals that his ideas about the economic system could enrich the current theoretical and political debate on international trade and integration as well as economic growth.
In Folge der gegenwärtigen Digitalisierung in der produzierenden Industrie werden Anwendungen oder Services mit potentiell positiven Auswirkungen auf Faktoren wie Effektivität und Arbeitsqualität entwickelt. Ein geeigneter Ansatz zur Stärkung motivierender Aspekte im Arbeitskontext kann Gamification darstellen. In dieser Arbeit ist die initiale Konzeption und Evaluation eines Gamification-Ansatzes für Anwender eines KI-Service zur Maschinenoptimierung dargestellt und möglichen Anforderungen an ein Konzept zur Motivationssteigerung extrahiert.
In dieser Ausarbeitung wird eine zeitliche Vorhersage von Erdbeben getroffen. Hierfür werden mit einem Datensatz aus Labor-Erdbeben Convolutional Neural Networks (CNN) trainiert. Die trainierten Netzwerke geben Vorhersagen, indem sie einen Input an seismischen Daten klassifizieren. Durch das Klassifizieren kann das CNN die zeitliche Entfernung zum nächsten Erdbeben vorhersagen. Es werden hierfür zwei Ansätze miteinander verglichen. Beim ersten Ansatz werden die Originaldaten in ein CNN gegeben. Beim zweiten Ansatz wird vor dem CNN eine Vorverarbeitung der Daten mit den Mel Frequency Cepstral Coefficients (MFCC) durchgeführt. Es zeigt sich, dass mit beiden Ansätzen eine gute Klassifikation möglich ist. Die Kombination aus MFCC und CNN liefert die besseren quantitativen Ergebnisse. Hierbei konnte eine Genauigkeit von 65 % erreicht werden.
Semi-automated image data labelling using AprilTags as a pre-processing step for machine learning
(2019)
Data labelling is a pre-processing step to prepare data for machine learning. There are many ways to collect and prepare this data, but these are usually associated with a greater effort. This paper presents an approach to semi-automated image data labelling using AprilTags. The AprilTags attached to the object, which contain a unique ID, make it possible to link the object surfaces to a particular class. This approach will be implemented and used to label data of a stackable box.
The data is evaluated by training a You Only Look Once (YOLO) net, with a subsequent evaluation of the detection results. These results show that the semi-automatically collected and labelled data can certainly be used for machine learning. However, if concise features of an object surface are covered by the AprilTag, there is a risk that the concerned class will not be recognized. It can be assumed that the labelled data can not only be used for YOLO, but also for other machine learning approaches.
Bereits zum elften Mal findet nun die Studierendenkonferenz Informatics Inside statt. Als Teil des Masterstudiengangs Human-Centered Computing organisieren Masterstudierende selbständig eine vollumfängliche wissenschaftliche Konferenz. Die Informatik ist nach wie vor ständigem Wandel unterworfen. Unsere Studierenden tragen diesem Wandel bei, indem sie in ihrer wissenschaftllichen Vertiefung aktuelle Problemstellungen durch innovative Konzepte lösen. Inzwischen ist die Informatik aber auch nicht immer sofort sichtbar. Das merken wir immer dann, wenn etwas nicht wie vorgesehen funktioniert. Das diesjährige Motto der Informatics Inside ist experience (IT);, verdeckt als Funktionsaufruf:).
Aimed at the problem that the accuracy of face image classification in complex environment is not high, a network model F-Net suitable for aesthetic classification of face images is proposed. Based on LeNet-5, the model uses convolutional layers to extract facial image features in complex backgrounds, optimized parameters in the network model, and changes the number of convolutional layers and fully connected layer feature elements in the model. The experimental results show that the F-Net network model proposed in this paper has a face image classifation accuracy of 73% in complex environment background, which is better than other classical convolutional neural network classification models.
In this paper, we address the novel EDP (Expert Design Plan) principle for procedural design automation of analog integrated circuits, which captures the knowledge-based design strategy of human circuit designers in an executable script, making it reusable. We present the EDP Player, which enables the creation and execution of EDPs for arbitrary circuits in the Cadence® Virtuoso® Design Environment. The tool provides a generic version of an instruction set, called EDPL (EDPLanguage), enabling emulation of a typical manual analog sizing flow. To automate the design of a Miller Operational Amplifier and to create variants of a Smart Power IC, several EDPs were implemented using this tool. Employing these EDPs leads to a strong reduction of design time without compromising design quality or reliability.
Serverless computing is an emerging cloud computing paradigm with the goal of freeing developers from resource management issues. As of today, serverless computing platforms are mainly used to process computations triggered by events or user requests that can be executed independently of each other. These workloads benefit from on-demand and elastic compute resources as well as per-function billing. However, it is still an open research question to which extent parallel applications, which comprise most often complex coordination and communication patterns, can benefit from serverless computing.
In this paper, we introduce serverless skeletons for parallel cloud programming to free developers from both parallelism and resource management issues. In particular, we investigate on the well known and widely used farm skeleton, which supports the implementation of a wide range of applications. To evaluate our concepts, we present a prototypical development and runtime framework and implement two applications based on our framework: Numerical integration and hyperparameter optimization - a commonly applied technique in machine learning. We report on performance measurements for both applications and discuss
the usefulness of our approach.
The Virtual Power Plant Neckar-Alb is a demonstration platform for operation, optimization and control of distributed energy resources, which are able to produce, store or consume electric energy. A heterogeneous set of distributed energy devices has been installed at the Campus of Reutlingen University by the Reutlingen Energy Centre (REZ) of the School of Engineering. The distributed energy devices have been combined to local microgrids and connected to an operative central power plant with additional participants. The demonstration platform serves students, researchers and industry experts for education and investigation of new technologies, devices and software.
A digital twin - a replica of energy devices - was established in the computing environment of MATLAB and Simulink. It simulates continuously their operation and is time synchronized and connected to the cenral energy management and control system of a virtual power plant. The model can be used as a platform for testing device performance in various conditions, working schedules and new optimization options.
Companies are continuously changing their strategy, processes, and information systems to benefit from the digital transformation. Controlling the digital architecture and governance is the fundamental goal. Enterprise Governance, Risk and Compliance (GRC) systems are vital for managing digital risks threatening in modern enterprises from many different angles. The most significant constituent to GRC systems is the definition of controls that is implemented on different layers of a digital Enterprise Architecture (EA). As part of the compliant aspect of GRC, the effectiveness of these controls is assessed and reported to relevant management bodies within the enterprise. In this paper, we present a metamodel which links controls to the affected elements of a digital EA and supplies a way of expressing associated assessment techniques and results. We complement a metamodel with an expository instantiation of a control compliance cockpit in an international insurance enterprise.
Business process models provide a considerable number of benefits for enterprises and organizations, but the creation of such models is costly and time-consuming, which slows down the organizational adoption of business process modeling. Social paradigms pave new ways for business process modeling by integrating stakeholders and leveraging knowledge sources. However, empirical research about the impact of social paradigms on costs of business process modeling is sparse. A better understanding of their impact could help to reduce the cost of business process modeling and improve decision-making on BPM activities. The paper constributes to this field by reporting about an empirical investigation via survey research on the perceived influence of different cost factors among experts. Our results indicate that different cost components, as well as the use of social paradigms, influence cost.
Due to the consequential impact of technological breakdowns, companies have to be prepared to deal with breakdowns or even better prevent them. In today's information technology, several methods and tools exist to downscale this concern. Therefore, this paper deals with the initial determination of a resilient enterprise architecture supporting predictive maintenance in the information technology domain and furthermore, concerns several mechanisms on how to reactively and proactively secure the state of resiliency on several abstraction levels. The objective of this paper is to give an overview on existing mechanisms for resiliency and to describe the foundation of an optimized approach, combining infrastructure and process mining techniques.
This book contains the proceedings of the KES International conferences on Innovation in Medicine and Healthcare (KES-InMed-19) and Intelligent Interactive Multimedia Systems and Services (KES-IIMSS-19), held on 17–19 June 2019 and co-located in St. Julians, on the island of Malta, as part of the KES Smart Digital Futures 2019 multi theme conference.
The major areas covered by KES-InMed-19 include: Digital IT Architecture in Healthcare; Advanced ICT for Medical and Healthcare; Biomedical Engineering, Trends, Research and Technologies and Healthcare Support System. The major areas covered by KES-IIMSS-19 were: Interactive Technologies; Artificial Intelligence and Data Analytics; Intelligent Services and Architectures and Applications.
This book is of use to researchers in these vibrant areas, managers, industrialists and anyone wishing to gain an overview of the latest research in these fields.
Size and function of bioartificial tissue models are still limited due to the lack of blood vessels and dynamic perfusion for nutrient supply. In this study, we evaluated the use of cytocompatible methacryl-modified gelatin for the fabrication of a hydrogel-based tube by dip-coating and subsequent photo-initiated cross-linking. The wall thickness of the tubes and the diameter were tuned by the degree of gelatin methacryl-modification and the number of dipping cycles. The dipping temperature of the gelatin solution was adjusted to achieve low viscous fluids of approximately 0.1 Pa s and was different for gelatin derivatives with different modification degrees. A versatile perfusion bioreactor for the supply of surrounding tissue models was developed, which can be adaped to several geometries and sizes of blood-vessel mimicking tubes. The manufactured bendable gelatin tubes were permeable for water and dissolved substances, like Nile Blue and serum albumin. As a proof of concept, human fibroblasts in a three-dimensional collagen tissue model were sucessfully supplied with nutrients via the central gelatin tube under dynamic conditions for 2 days. Moreover, the tubes could be used as scaffolds to build-up a functional and viable endothelial layer. Hence, the presented tools can contribute to solving current challenges in tissue engineering.
The rise of digital technologies has become an important driver for change in multiple industries. Therefore, firms need to develop digital capabilities to manage the transformation process successfully. Prior research assumes that the development of a specific set of digital capabilities leads to higher digital maturity. However, a measurement framework for digital maturity does not exist in scholarly work. Therefore, this paper develops a conceptualization and measuremnent model for digital maturity.
In 2017, Philips' goal was to use innovation to improve the lives of three billion people a year by 2025. To achieve that, the company was shifting from selling medical products in a transactional manner to providing integrated healthcare solutions based on digital health technology. Based on our interviews with 23 executives at Philips, the case examines the two directions of the transformation required by this shift: externally, Philips worked on transforming how healthcare was conducted. Healthcare professionals would have to change the way they worked and reimbursement schemes needed to change to incentivize payers, providers, and patients in vastly different ways. Internally, Philips needed to redesign how its employees worked. The company componentized its business, introduced digital platforms, and co-created integrated solutions with the various stakeholders of the healthcare industry. In other words: Philips was transforming itself in order the reinvent healthcare in the digital age.
Autism spectrum disorders (ASD) affect a large number of children both in the Russian Federation and in Germany. Early diagnosis is key for these children, because the sooner parents notice such disorders in a child and the rehabilitation and treatment program starts, the higher the likelihood of his social adaptation. The difficulties in raising such a child lie in the complexity of his learning outside of children's groups and the complexity of his medical care. In this regard, the development of digital applications that facilitate medical care and education of such children at home is important and relevant. The purpose of the project is to improve the availability and quality of healthcare and social adaptation at home of children with ASD through the use of digital technologies.
Anders als Digital-ICs, die hochautomatisiert entworfen werden können, ist der Entwurf analoger ICs bis heute Handarbeit. Übliche auf Optimierung basierende Automatisierungsverfahren scheitern. Die Ursachen wurden jetzt in einem Forschungsprojekt untersucht, um neue Ansätze zur Entwurfsautomatisierung analoger ICs abzuleiten.
Die Landessprache in der Lehre - welche Bedeutung kommt ihr bei der Internationalisierung zu?
(2019)
Seit der Jahrhundertwende wird erfolgreich die Intensivierung des Austauschs zwischen wissenschaftlichen Einrichtungen betrieben, auch national, aber vor allem international. Anfänglich schien klar, dass gute Indikatoren für die "Internationalisierung" genannte Entwicklung die Anteile ausländischer Wissenschaftler und Studierender sind. Konsens über sinnvolle Zielgrößen für die Indikatoren gibt es jedoch bisher nicht. Nach einiger Zeit flachte sich der anfängliche Anstieg dieser Quoten etwas ab. Mit der Folge einer weiteren Steigerung dieses Indikators ist neuerdings international der Trend zur Anglophonisierung der Lehre zu beobachten.
Additive manufacturing is a key technology which applies the ideas of Industry 4.0 in order to enable the production of personalized and highly customized products economically. Especially small and medium sized companies often lack the competence and experience to evaluate objectively and profoundly the potential of additive manufacturing technologies in small and medium sized companies. Furthermore, the method has been validated in a small medical technology company evaluating the additive manufacturing potential of an existing surgery tool.
Continuous refactoring is necessary to maintain source code quality and to cope with technical debt. Since manual refactoring is inefficient and error prone, various solutions for automated refactoring have been proposed in the past. However, empirical studies have shown that these solutions are not widely accepted by software developers and most refactorings are still performed manually. For example, developers reported that refactoring tools should support functionality for reviewing changes. They also criticized that introducing such tools would require substantial effort for configuration and integration into the current development environment.
In this paper, we present our work towards the Refactoring-Bot, an autonomous bot that integrates into the team like a human developer via the existing version control platform. The bot automatically performs refactorings to resolve code smells and presents the changes to a developer for asynchronous review via pull requests. This way, developers are not interrupted in their workflow and can review the changes at any time with familiar tools. Proposed refactorings can then be integrated into the code base via the push of a button. We elaborate on our vision, discuss design decisions, describe the current state of development, and give an outlook on planned development and research activities.