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In-vivo and in-vitro comparison of implant-based CRT optimization - What provide new algorithms?
(2011)
Introduction: In cardiac resynchronization therapy (CRT), individual AV delay (AVD) optimization can effectively increase hemodynamics and reduce non-responder rate. Accurate, automatic and easily comprehensible algorithms for the follow-up are desirable. QuickOpt is the first attempt of a semi-automatic intracardiac electrogram (IEGM) based AVD algorithm. We aimed to compare its accuracy and usefulness by in-vitro and in-vivo studies.
Methods: Using the programmable ARSI-4 four-chamber heart rhythm and IEGM simulator (HKP, Germany), the QuickOpt feature of an Epic HF system (St. Jude, USA) was tested in-vitro by simulated atrial IEGM amplitudes between 0.3 and 3.5mV during both, manual and automatic atrial sensing between 0.2 and 1.0mV. Subsequently, in 21 heart failure patients with implanted biventricular defibrillators, QuickOpt was performed in-vivo. Results of the algorithm for VDD and DDD stimulation were compared with echo AV delay optimization.
Results: In-vitro simulations demonstrated a QuickOpt measuring accuracy of ± 8ms. Depending on atrial IEGM amplitude, the algorithm proposed optimal AVD between 90 and 150ms for VDD and between 140 and 200ms for DDD operation, respectively. In-vivo, QuickOpt difference between individual AVD in DDD and VDD mode was either 50ms (20pts) or 40ms (1pt). QuickOpt and echo AVD differed by 41 ± 25ms (7 – 90ms) in VDD and by 18 ± 24ms (17-50ms) in DDD operation. Individual echo AVD difference between both modes was 73 ± 20ms (30-100ms).
Conclusion: The study demonstrates the value of in-vitro studies. It predicted QuickOpt deficiencies regarding IEGM amplitude dependent AVD proposals constrained to fixed individual differences between DDD and VDD mode. Consequently, in-vivo, the algorithm provided AVD of predominantly longer duration than echo in both modes. Accepting echo individualization as gold standard, QuickOpt should not be used alone to optimize AVD in CRT patients.
Introduction: To simplify AV delay (AVD) optimization in cardiac resynchronization therapy (CRT), we reported that the hemodynamically optimal AVD for VDD and DDD mode CRT pacing can be approximated by individually measuring implant-related interatrial conduction intervals (IACT) in oesophageal electrogram (LAE) and adding about 50ms. The programmer-based St Jude QuickOpt algorithm is utilizing this finding. By automatically measuring IACT in VDD operation, it predicts the sensed AVD by adding either 30ms or 60ms. Paced AVD is strictly 50ms longer than sensed AVD. As consequence of those variations, several studies identified distinct inaccuracies of QuickOpt. Therefore, we aimed to seek for better approaches to automate AVD optimization.
Methods: In a study of 35 heart failure patients (27m, 8f, age: 67±8y) with Insync III Marquis CRT-D systems we recorded telemetric electrograms between left ventricular electrode and superior vena cava shock coil (LVtip/SVC = LVCE) simultaneously with LAE. By LVCE we measured intervals As-Pe in VDD and Ap-Pe in DDD operation between right atrial sense-event (As) or atrial stimulus (Ap), resp., and end of the atrial activity (Pe). As-Pe and Ap-Pe were compared with As-LA an Ap-LA in LAE, respectively.
Results: End of the left atrial activity in LVCE could clearly be recognized in 35/35 patients in VDD and 29/35 patients in DDD operation. We found mean intervals As-LA of 40.2±24.5ms and Ap-LA of 124.3±20.6ms. As-Pe was 94.8±24.1ms and Ap-Pe was 181.1±17.8ms. Analyzing the sums of As-LA + 50ms with duration of As-Pe and Ap-LA + 50ms with duration of Ap-Pe, the differences were 4.7±9.2ms and 4.2±8.6ms, resp., only. Thus, hemodynamically optimal timing of the ventricular stimulus can be triggered by automatically detecting Pe in LVCE.
Conclusion: Based on minimal deviations between LAE and LVCE approach, we proposed companies to utilize the LVCE in order to automate individual AVD optimization in CRT pacing.
Vorgestellt wird ein Konzept zur biologischen Methanisierung von Wasserstoff direkt in Biogasreaktoren, mit dem durch Membranbegasung der Methangehalt des Biogases auf > 96 % erhöht werden kann. Essentiell zum Erreichen solch hoher Methanwerte sind die Einhaltung eines optimalen pH-Bereichs und die Vermeidung von H2-Akkumulation. Im Falle einer Limitierung der Methanbildungsrate durch den eigentlichen anaeroben Abbauprozess der Biomasse ist auch eine externe Zufuhr von CO2 zur weiteren Methanbildung denkbar. Das Verfahren soll weiter optimiert und in einem von der Deutschen Bundesstiftung Umwelt geförderten Projekt in der Biogasanlage einer regionalen Käserei in der Praxis getestet werden. Die hier angestrebte Kombination aus dezentraler Abfallverwertung und Eigenenergieerzeugung eines lebensmittelverarbeitenden Betriebs unter Einbindung in ein intelligentes Erneuerbare Energien - Konzept soll einen zusätzlichen Mehrwert liefern.
This work discusses several use cases of post-mortem mobile device tracking in which privacy is required e.g. due to client-confidentiality agreements and sensibility of data from government agencies as well as mobile telecommunication providers. We argue that our proposed Bloomfilter based privacy approach is a valuable technical building block for the arising General Data Protection Regulation (GDPR) requirements in this area. In short, we apply a solution based on the Bloom filters data structure that allows a 3rd party to performsome privacy saving setrelations on a mobiletelco’s access logfile or other mobile access logfile from harvesting parties without revealing any other mobile users in the proximity of a mobile base station but still allowing to track perpetrators.
Printed electronics (PE) is a fast growing technology with promising applications in wearables, smart sensors and smart cards since it provides mechanical flexibility, low-cost, on-demand and customizable fabrication. To secure the operation of these applications, True Random Number Generators (TRNGs) are required to generate unpredictable bits for cryptographic functions and padding. However, since the additive fabrication process of PE circuits results in high intrinsic variation due to the random dispersion of the printed inks on the substrate, constructing a printed TRNG is challenging. In this paper, we exploit the additive customizable fabrication feature of inkjet printing to design a TRNG based on electrolyte-gated field effect transistors (EGFETs). The proposed memory-based TRNG circuit can operate at low voltages (≤ 1 V ), it is hence suitable for low-power applications. We also propose a flow which tunes the printed resistors of the TRNG circuit to mitigate the overall process variation of the TRNG so that the generated bits are mostly based on the random noise in the circuit, providing a true random behaviour. The results show that the overall process variation of the TRNGs is mitigated by 110 times, and the simulated TRNGs pass the National Institute of Standards and Technology Statistical Test Suite.
Printed Electronics is perceived to have a major impact in the fields of smart sensors, Internet of Things and wearables. Especially low power printed technologies such as electrolyte gated field effect transistors (EGFETs) using solution-processed inorganic materials and inkjet printing are very promising in such application domains. In this paper, we discuss a modeling approach to describe the variations of printed devices. Incorporating these models and design flows into our previously developed printed design system allows for robust circuit design. Additionally, we propose a reliability-aware routing solution for printed electronics technology based on the technology constraints in printing crossovers. The proposed methodology was validated on multiple benchmark circuits and can be easily integrated with the design automation tools-set.
Radio frequency identification (RFID) antennas are popular for high frequency (HF) RFID, energy transfer and near field communication (NFC) applications. Particularly for wireless measurement systems the RFID/NFC technology is a good option to implement a wireless communication interface. In this context, the design of corresponding reader and transmitter antennas plays a major role for achieving suitable transmission quality. This work proves the feasibility of the rapid prototyping of a RFID/NFC antenna, which is used for the wireless communication and energy harvesting at the required frequency of 13.56 MHz. A novel and low-cost direct ink writing (DIW) technology utilizing highly viscous silver nanoparticle ink is used for this process. This paper describes the development and analysis of low-cost printed flexible RFID/NFC antennas on cost-effective substrates for a microelectronic vital parameter measurement system. Furthermore, we compare the measured technical parameters with existing copper-based counterparts on a FR4 substrate.
Smart Home or Smart Building applications are a growing market. An increasing challenge is to design energy efficient Smart Home applications to achieve sustainable and green homes. Using the example of the development of an Indoor Smart Gardening system with wireless monitoring and automated watering this paper is discussing in particular the design issue of energy autonomous working sensors and actuators for home automation. Most important part of the presented Smart Gardening system is a 3D printed smart flower pot for single plants. The smart flower pot has integrated a water reservoir for automated plant irrigation and an electronic for monitoring important plant parameters and the water level of the water reservoir. Energy harvesting with solar cells enables energy autonomous working of the flower pot. A low-power wireless interface also integrated in the flowerpot and an external gateway based on a Raspberry Pi 3 enables wireless networking of multiple of those flower pots. The gateway is used for evaluating the plant parameters and as a user interface. Particularly the architecture of the energy autonomous wireless flower pot will be considered, because fully energy autonomous sensors and actuators for home automation could not be implemented without special concepts for the energy supply and the overall electronic.
Process engineering industries are now facing growing economic pressure and societies' demands to improve their production technologies and equipment, making them more efficient and environmentally friendly. However unexpected additional technical and ecological drawbacks may appear as negative side effects of the new environmentally-friendly technologies. Thus, in their efforts to intensify upstream and downstream processes, industrial companies require a systematic aid to avoid compromising of ecological impact. The paper conceptualises a comprehensive approach for eco-innovation and eco- design in process engineering. The approach combines the advantages of Process Intensification as Knowledge-Based Engineering (KBE), inventive tools of Knowledge-Based Innovation (KBI), and main principles and best-practices of Eco-Design and Sustainable Manufacturing. It includes a correlation matrix for identification of eco-engineering contradictions and a process mapping technique for problem definition, database of Process Intensification methods and equipment, as well as a set of strongest inventive operators for eco-ideation.
As engineering graduates and specialists frequently lack the advanced skills and knowledge required to run eco-innovation systematically, the paper proposes a new teaching method and appropriate learning materials in the field of eco-innovation and evaluates the learning experience and outcomes. This programme is aimed at strengthening student’s skills and motivation to identify and creatively overcome secondary eco-contradictions in case if additional environmental problems appears as negative side effects of eco-friendly solutions.
Based on a literature analysis and own investigations, authors propose to introduce a manageable number of eco-innovation tools into a standard one-semester design course in process engineering with particular focus on the identification of eco-problems in existing technologies, selection of the appropriate new process intensification technologies (knowledge-based engineering), and systematic ideation and problem solving (knowledge-based innovation and invention).
The proposed educational approach equips students with the advanced knowledge, skills and competences in the field of eco-innovation. Analysis of the student’s work allows one to recommend simple-to-use tools for a fast application in process engineering, such as process mapping, database of eco-friendly process intensification technologies, and up to 20 strongest inventive operators for solving of environmental problems. For the majority of students in the survey, even the small workload has strengthened their self-confidence and skills in eco-innovation
Growing demands for cleaner production and higher eco-efficiency in process engineering require a comprehensive analysis of technical and environmental outcomes of customers and society. Moreover, unexpected additional technical or ecological drawbacks may appear as negative side effects of new environ-mentally friendly technologies. The paper conceptualizes a comprehensive ap-proach for analysis and ranking of engineering and ecological requirements in process engineering in order to anticipate secondary problems in eco-design and to avoid compromising the environmental or technological goals. For this purpose, the paper presents a method based on integration of the Quality Func-tion Deployment approach with the Importance-Satisfaction Analysis for the requirements ranking. The proposed method identifies and classifies compre-hensively the potential engineering and eco-engineering contradictions through analysis of correlations within requirements groups such as stakehold-er requirements (SRs) and technical requirements (TRs), and additionally through cross-relationship between SRs and TRs.
The 40 Altshuller Inventive Principles with numerous sub-principles remain over decades the most frequently applied tool of the Theory of Inventive Problem Solving TRIZ for systematic idea generation. However, their application often requires a concentrated, creative and abstract way of thinking that can be fairly challenging for the newcomers to TRIZ. This paper describes an approach to reduce the abstraction level of inventive sub-principles and presents the results of the idea generation experiment conducted with three groups of undergraduate and graduate students from different years of study in mechanical and process engineering. The students were asked to generate and to record their individual ideas for three design problems using a pre-defined set of classical and modified sub-principles within 10 minutes. The overall outcomes of the experiment support the assumption that the less abstract wording of the modified sub-principles leads to higher number of ideas. The distribution of ideas between the fields of MATCHEM-IBD (Mechanical, Acoustic, Thermal, Chemical, Electrical, Magnetic, Intermolecular, Biological and Data processing) differs significantly between groups using modified and abstract sub-principles.
Recent deep learning based approaches have shown remarkable success on object segmentation tasks. However, there is still room for further improvement. Inspired by generative adversarial networks, we present a generic end-to-end adversarial approach, which can be combined with a wide range of existing semantic segmentation networks to improve their segmentation performance. The key element of our method is to replace the commonly used binary adversarial loss with a high resolution pixel-wise loss. In addition, we train our generator employing stochastic weight averaging fashion, which further enhances the predicted output label maps leading to state-of-the-art results. We show, that this combination of pixel-wise adversarial training and weight averaging leads to significant and consistent gains in segmentation performance, compared to the baseline models.
Current training methods for deep neural networks boil down to very high dimensional and non-convex optimization problems which are usually solved by a wide range of stochastic gradient descent methods. While these approaches tend to work in practice, there are still many gaps in the theoretical understanding of key aspects like convergence and generalization guarantees, which are induced by the properties of the optimization surface (loss landscape). In order to gain deeper insights, a number of recent publications proposed methods to visualize and analyze the otimization surfaces. However, the computational cost of these methods are very high, making it hardly possible to use them on larger networks. In this paper, we present the GradVis Toolbox, an open source library for efficient and scalable visualization and analysis of deep neural network loss landscapes in Tesorflow and PyTorch. Introducing more efficient mathematical formulations and a novel parallelization scheme, GradVis allows to plot 2d and 3d projections of optimization surfaces and trajectories, as well as high resolution second order gradient information for large networks.
Most machine learning methods require careful selection of hyper-parameters in order to train a high performing model with good generalization abilities. Hence, several automatic selection algorithms have been introduced to overcome tedious manual (try and error) tuning of these parameters. Due to its very high sample efficiency, Bayesian Optimization over a Gaussian Processes modeling of the parameter space has become the method of choice. Unfortunately, this approach suffers from a cubic compute complexity due to underlying Cholesky factorization, which makes it very hard to be scaled beyond a small number of sampling steps. In this paper, we present a novel, highly accurate approximation of the underlying Gaussian Process. Reducing its computational complexity from cubic to quadratic allows an efficient strong scaling of Bayesian Optimization while outperforming the previous approach regarding optimization accuracy. First experiments show speedups of a factor of 162 in single node and further speed up by a factor of 5 in a parallel environment.
One of the challenges for autonomous driving in general is to detect objects in the car's camera images. In the Audi Autonomous Driving Cup (AADC), among those objects are other cars, adult and child pedestrians and emergency vehicle lighting. We show that with recent deep learning networks we are able to detect these objects reliably on the limited Hardware of the model cars. Also, the same deep network is used to detect road features like mid lines, stop lines and even complete crossings. Best results are achieved using Faster R-CNN with Inception v2 showing an overall accuracy of 0.84 at 7 Hz.
This paper describes the concept and some results of the project "Menschen Lernen Maschinelles Lernen" (Humans Learn Machine Learning, ML2) of the University of Applied Sciences Offenburg. It brings together students of different courses of study and practitioners from companies on the subject of Machine Learning. A mixture of blended learning and practical projects ensures a tight coupling of machine learning theory and application. The paper details the phases of ML2 and mentions two successful example projects.
The high peak power in comparison to the average transmit power is one of the major long-standing problems in multicarrier modulation and is known as the PAPR (peak to average power ratio) problem. Many PAPR reduction methods have been devised and their comparison is usually based on the complementary cumulative distribution function (CCDF) of the PAPR. While this comparison is straightforward and easy to compute, its relationship with system performance metrics like the (uncoded) BER or the word error rate (WER) for coded systems is considerably more involved. We evaluate the impact of the PAPR on performance metrics like uncoded BER, EVM (error vector magnitude), mutual information and the WER for soft decoding. In this context, we find that system performance is not necessarily degraded by an increasing PAPR. We show that a high number of subcarriers, despite the corresponding high PAPR, is actually not a problem for the system performance and provide a simple explanation for this seemingly counter-intuitive fact.
Classification of TRIZ Inventive Principles and Sub-Principles for Process Engineering Problems
(2019)
The paper proposes a classification approach of 40 Inventive Principles with an extended set of 160 sub-principles for process engineering, based on a thorough analysis of 155 process intensification technologies, 200 patent documents, 6 industrial case studies applying TRIZ, and other sources. The authors define problem-specific sub-principles groups as a more precise and productive ideation technique, adaptable for a large diversity of problem situations, and finally, examine the anticipated variety of ideation using 160 sub-principles with the help of MATCEM-IBD fields.
Kleinstlebewesen vorgestellt, das Vitalparameter erfasst und diese in einem FRAM-Speicher bis zum Auslesen abspeichert. Durch eine drahtlose RFID-/NFC-Ausleseschnittstelle kann die erfasste Körpertemperatur und der Puls der letzten Wochen ausgelesen werden. Alle Einstellungen des Messsystems können durch einen geeigneten RFID-Reader für Laptops oder durch Smartphones über die NFC-Schnittstelle geändert werden. Das vollständige Aufladen des nur 3 g leichten und 15 mm x 25 mm großen Messsystems erfolgt durch eine selbstgedruckte RFID-Reader-Antenne in Verbindung mit einem RFID-Reader und benötigt hierzu weniger als 21 Stunden. Bei vollständig aufgeladenem Energiespeicher ist ein Betrieb von 47 Tagen möglich. Dies wird durch ein speziell für das Messsystem konzipiertes Lade- und Powermanagement erreicht. Neben der Auswahl von energiesparenden Komponenten für die Hardware und deren bestmöglichen Nutzung, wurde die Software so optimiert, dass das Programm schnell und stromsparend abgearbeitet wird. Die Erweiterbarkeit und Anpassung wird durch das modulare Konzept auch in anderen Bereichen gewährleistet.
Smart Home-/Smart-Building-Anwendungen sind ein stetig wachsender Markt. Smart Gardening ist ein Beispiel dafür, Nutzern mehr Komfort und eine bessere Lebensqualität zu Hause oder in Bürogebäuden zu ermöglichen. Im Rahmen dieses Beitrags wird die Entwicklung eines Indoor-Smart-Gardening-Systems mit dem Fokus auf energieautarkes Arbeiten vorgestellt. Herzstück des Systems ist ein 3D-gedruckter Blumentopf für einzelne Pflanzen mit integrierter Elektronik zum Monitoring der wichtigsten Pflanzenparameter und einem integrierten Wasserreservoir mit Tauchpumpe für das automatisierte Bewässern der Pflanze. Energy Harvesting per Solarzellen ermöglicht ein energieautarkes Arbeiten des Blumentopfes. Eine selbstentwickelte Low-Power-Funkschnittstelle im Blumentopf und ein externes Gateway ermöglichen die drahtlose Vernetzung mehrerer Pflanzen. Das Gateway dient zur Auswertung der Pflanzenparameter, der Ansteuerung der im Netzwerk vorhandenen Blumentöpfe und als Benutzerinterface.
Industrie 4.0 bedeutet nicht nur einen Wandel der technischen Möglichkeiten und Arbeitsbedingungen, sondern auch einen Bedarf an neuen, sich kontinuierlich weiterentwickelnden Kompetenzen und die Bereitschaft der Beschäftigten, Veränderungen mitzugestalten. Spielerische Ansätze der Kompetenzentwicklung können v.a. bei weiterbildungsfernen Mitarbeitern hilfreich sein, um das komplexe Thema verständlich zu vermitteln. Der Beitrag beschreibt ein Seminarkonzept mit integriertem Brettspiel, mit dem Teilnehmer anhand eines fiktiven Unternehmens (Müller GmbH) die Transformation eines Unternehmens in die Industrie 4.0 spielerisch nachvollziehen. Dieses Konzept erweist sich in einer ersten Evaluation als durchaus vielversprechend.
Medical devices accompany our everyday life and come across in situations of worse condition, in significant moments concerning the health or during routine checkups. To ensure flawless operations and error-free results it is essential to test applications and devices. High risks for patient’s health come with operating errors [33] so that the presented research project, called Professional UX, identifies signals and irritations caused by the interaction with a certain device by analyzing mimic, voice and eye tracking data during user experience tests. Besides, this paper will provide information on typical errors of interactive applications which are based on an empirical lab-based survey and the evaluated results achieved. The pictured proceeding of user experience tests and the following analysis can also be applied to other fields and serves as a support for the optimization of products and systems.
Apache Hadoop is a well-known open-source framework for storing and processing huge amounts of data. This paper shows the usage of the framework within a project of the university in cooperation with a semiconductor company. The goal of this project was to supplement the existing data landscape by the facilities of storing and analyzing the data on a new Apache Hadoop based platform.
A novel Bluetooth Low Energy advertising scan algorithm is presented for hybrid radios that are additionally capable to measure energy on Bluetooth channels, e.g. as they would need to be compliant with IEEE 802.15.4. Scanners applying this algorithm can achieve a low latency whilst consuming only a fraction of the power that existing mechanisms can achieve at a similar latency. Furthermore, the power consumption can scale with the incoming network traffic and in contrast to the existing mechanisms, scanners can operate without any frame loss given ideal network conditions. The algorithm does not require any changes to advertisers, hence, stays compatible with existing devices. Performance evaluated via simulation and experiments on real hardware shows a 37 percent lower power consumption compared to the best existing scan setting while even achieving a slightly lower latency which proves that this algorithm can be used to improve the quality of service of connection-less Bluetooth communication or reduce the connection establishment time of connection-oriented communication.
The TriRhenaTech alliance universities and their partners presented their competences in the field of artificial intelligence and their cross-border cooperations with the industry at the tri-national conference 'Artificial Intelligence : from Research to Application' on March 13th, 2019 in Offenburg. The TriRhenaTech alliance is a network of universities in the Upper Rhine Trinational Metropolitan Region comprising of the German universities of applied sciences in Furtwangen, Kaiserslautern, Karlsruhe, and Offenburg, the Baden-Wuerttemberg Cooperative State University Loerrach, the French university network Alsace Tech (comprised of 14 'grandes écoles' in the fields of engineering, architecture and management) and the University of Applied Sciences and Arts Northwestern Switzerland. The alliance's common goal is to reinforce the transfer of knowledge, research, and technology, as well as the cross-border mobility of students.
With the surge in global data consumption with proliferation of Internet of Things (IoT), remote monitoring and control is increasingly becoming popular with a wide range of applications from emergency response in remote regions to monitoring of environmental parameters. Mesh networks are being employed to alleviate a number of issues associated with single-hop communication such as low area coverage, reliability, range and high energy consumption. Low-power Wireless Personal Area Networks (LoWPANs) are being used to help realize and permeate the applicability of IoT. In this paper, we present the design and test of IEEE 802.15.4-compliant smart IoT nodes with multi-hop routing. We first discuss the features of the software stack and design choices in hardware that resulted in high RF output power and then present field test results of different baseline network topologies in both rural and urban settings to demonstrate the deployability and scalability of our solution.
Enabling ultra-low latency is one of the major drivers for the development of future cellular networks to support delay sensitive applications including factory automation, autonomous vehicles and tactile internet. Narrowband Internet of Things (NB-IoT) is a 3 rd Generation Partnership Project (3GPP) Release 13 standardized cellular network currently optimized for massive Machine Type Communication (mMTC). To reduce the latency in cellular networks, 3GPP has proposed some latency reduction techniques that include Semi Persistent Scheduling (SPS) and short Transmission Time Interval (sTTI). In this paper, we investigate the potential of adopting both techniques in NB-IoT networks and provide a comprehensive performance evaluation. We firstly analyze these techniques and then implement them in an open-source network simulator (NS3). Simulations are performed with a focus on Cat-NB1 User Equipment (UE) category to evaluate the uplink user-plane latency. Our results show that SPS and sTTI have the potential to greatly reduce the latency in NB-IoT systems. We believe that both techniques can be integrated into NB-IoT systems to position NB-IoT as a preferred technology for low data rate Ultra-Reliable Low-Latency Communication (URLLC) applications before 5G has been fully rolled out.
The monitoring of industrial environments ensures that highly automated processes run without interruption. However, even if the industrial machines themselves are monitored, the communication lines are currently not continuously monitored in todays installations. They are checked usually only during maintenance intervals or in case of error. In addition, the cables or connected machines usually have to be removed from the system for the duration of the test. To overcome these drawbacks, we have developed and implemented a cost-efficient and continuous signal monitoring of Ethernet-based industrial bus systems. Several methods have been developed to assess the quality of the cable. These methods can be classified to either passive or active. Active methods are not suitable if interruption of the communication is undesired. Passive methods, on the other hand, require oversampling, which calls for expensive hardware. In this paper, a novel passive method combined with undersampling targeting cost-efficient hardware is proposed.
Narrowband IoT (NB-IoT) as a radio access technology for the cellular Internet of Things (cIoT) is getting more traction due to attractive system parameters, new proposals in the 3 rd Generation Partnership Project (3GPP) Release 14 for reduced power consumption and ongoing world-wide deployment. As per 3GPP, the low-power and wide-area use cases in 5G specification will be addressed by the early NB-IoT and Long-Term Evolution for Machines (LTE-M) based technologies. Since these cIoT networks will operate in a spatially distributed environment, there are various challenges to be addressed for tests and measurements of these networks. To meet these requirements, unified emulated and field testbeds for NB-IoT-networks were developed and used for extensive performance measurements. This paper analyses the results of these measurements with regard to RF coverage, signal quality, latency, and protocol consistency.
When designing and installing Indoor Positioning Systems, several interrelated tasks have to be solved to find an optimum placement of the Access Points. For this purpose, a mathematical model for a predefined number of access points indoors is presented. Two iterative algorithms for the minimization of localization error of a mobile object are described. Both algorithms use local search technique and signal level probabilities. Previously registered signal strengths maps were used in computer simulation.
Formal Description of Use Cases for Industry 4.0 Maintenance Processes Using Blockchain Technology
(2019)
Maintenance processes in Industry 4.0 applications try to achieve a high degree of quality to reduce the downtime of machinery. The monitoring of executed maintenance activities is challenging as in complex production setups, multiple stakeholders are involved. So, full transparency of the different activities and of the state of the machine can only be supported, if these stakeholders trust each other. Therefore, distributed ledger technologies, like Blockchain, can be promising candidates for supporting such applications. The goal of this paper is a formal description of business and technical interactions between non-trustful stakeholders in the context of Industry 4.0 maintenance processes using distributed ledger technologies. It also covers the integration of smart contracts for automated triggering of activities.
The Internet of Things (IoT) application has becoming progressively in-demand, most notably for the embedded devices (ED). However, each device has its own difference in computational capabilities, memory usage, and energy resources in connecting to the Internet by using Wireless Sensor Networks (WSNs). In order for this to be achievable, the WSNs that form the bulk of the IoT implementation requires a new set of technologies and protocol that would have a defined area, in which it addresses. Thus, IPv6 Low Power Area Network (6LoWPAN) was designed by the Internet Engineering Task Force (IETF) as a standard network for ED. Nevertheless, the communication between ED and 6LoWPAN requires appropriate routing protocols for it to achieve the efficient Quality of Service (QoS). Among the protocols of 6LoWPAN network, RPL is considered to be the best protocol, however its Energy Consumption (EC) and Routing Overhead (RO) is considerably high when it is implemented in a large network. Therefore, this paper would propose the HRPL to enchance the RPL protocol in reducing the EC and RO. In this study, the researchers would present the performance of RPL and HRPL in terms of EC, Control traffic Overhead (CTO) and latency based on the simulation of the 6LoWPAN network in fixed environment using COOJA simulator. The results show HRPL protocol achieves better performance in all the tested topology in terms of EC and CTO. However, the latency of HRPL only improves in chain topology compared with RPL. We found that further research is required to study the relationship between the latency and the load of packet transmission in order to optimize the EC usage.
Low latency communication is essential to enable mission-critical machine-type communication (mMTC) use cases in cellular networks. Factory and process automation are major areas that require such low latency communication. In this paper, we investigate the potential of adopting the semi-persistent scheduling (SPS) latency reduction technique in narrowband LTE (NB-LTE) networks and provide a comprehensive performance evaluation. First, we investigate and implement SPS in an open-source network simulator (NS3). We perform simulations with a focus on LTE-M and Narrowband IoT (NB-IoT) systems and evaluate the impact of the SPS technique on the uplink latency of these narrowband systems in real industrial automation scenarios. The performance gain of adopting SPS is analyzed and the results is compared with the legacy dynamic scheduling. Our results show that SPS has the potential to reduce the latency of cellular Internet of Things (cIoT) networks. We believe that SPS can be integrated into LTE-M and NB-IoT systems to support low-latency industrial applications.
The ability to change aerodynamic parameters of airfoils during flying can potentially save energy as well as reducing the noise made by the unmanned aerial vehicles (UAV) because of sharp edges of the airfoil and its rudders. In this paper, an approach for the design of an adaptive wing using a multi-material 3D printer is shown. In multi-material 3D printing, up to six different materials can be combined in one component. Thus, the user can determine the mixture and the spatial arrangement of this “digital material” in advance in the pre-processing software. First, the theoretical benefits of adaptive wings are shown, and already existing adaptive wings and concepts are explicated within a literature review. Then the additive manufacturing process using photopolymer jetting and its capabilities to print multiple materials in one part are demonstrated. Within the scope of a case study, an adaptive wing is developed and the necessary steps for the product development and their implementation in CAD are presented. This contribution covers the requirements for different components and sections of an adaptive wing designed for additive manufacturing using multiple materials as well as the single steps of development with its different approaches until the final design of the adaptive wing. The developed wing section is simulated, and qualitative tests in a wind tunnel are carried out with the wing segment. Finally, the additively manufactured wing segment is evaluated under technical and economic aspects.
The fast and cost-effective manufacturing of tools for thermoforming is an essential requirement to shorten the development time of products. Thus, additive processes are used increasingly in tooling for thermoforming of plastic sheets. However, a disadvantage of many additive methods is that they are highly cost-intensive, since complex systems based on laser technology and expensive metal powders are needed. Therefore, this paper examines how to work with favorable additive methods, e.g. Binder Jetting, to manufacture tools, which provide sufficient strength for thermoforming. The use of comparatively low-priced inkjet technology for the layer construction and a polymer plaster as material can be expected to result in significant cost reductions. Based on a case study using a cowling (engine bonnet) for an Unmanned Aerial Vehicle (UAV), the development of a complex tool for thermoforming is demonstrated. The object in this study is to produce a tool for a complex-shaped component in small numbers and high quality in a short time and at reasonable costs. Within the tooling process, integrated vacuum channels are implemented in additive tooling without the need for additional post-processing (for example, drilling). In addition, special technical challenges, such as the demolding of undercuts or the parting of the tool are explained. All process steps from tool design to the use of the additively manufactured tool are analyzed. Based on the manufacturing of a small series of cowlings for a UAV made of plastic sheets (ABS), it is shown, that the Binder Jetting offers sufficient mechanical and thermal strength for additive tooling. In addition, an economic evaluation of the tool manufacturing and a detailed consideration of the required manufacturing times for the different process steps are carried out. Finally, a comparison is made with conventional and alternative additive methods of tooling.
Direct Digital Manufacturing of Architectural Models using Binder Jetting and Polyjet Modeling
(2019)
Today, architectural models are an important tool for illustrating drawn-on plansor computer-generated virtual models and making them understandable. Inaddition to the conventional methods for the manufacturing of physical models, awide range of processes for Direct Digital Manufacturing (DDM) has spreadrapidly in recent years. In order to facilitate the application of these new methodsfor architects, this contribution examines which technical and economic resultsare possible using 3D printed architectural models. Within a case study, it will beshown on the basis of a multi-storey detached house, which kind of datapreparation is necessary. The DDM of architectural models will be demonstratedusing two widespread techniques and the resulting costs will be compared.
Art and Photonics
(2019)
In this paper we report on our continuous efforts to apply optics and photonics in art. This results in interdisciplinary projects which sometimes lead to concrete art installations.
We presented some of these projects at the UNESCO headquarters in Paris, at the opening ceremony of the International Year of Light and the inaugural ceremony of the International Day of Light.
Some newer projects, such as “A Maze: Ingenious Pipes” and “The Power of Your Eyes,” are also presented in this paper.
We present our twenty years of experience in the live broadcasting of astronomical events, with the main focus on total lunar eclipses. Our efforts were motivated by the great impact and high number of viewers of these events. Visitors from over a hundred countries watched our live broadcasts. Our viewer record was set on July 27, 2018, with the live transmission of the total lunar eclipse from the Feldberg, the highest mountain in the Black Forest, attracting nearly half a million viewers in five hours.
An especially challenging activity was the live observing of the Mercury transit on 9 May 2016, which we presented as ‘live astronomy’ with hands-on telescope. The main goal of this event was to awake our students enthusiasm for optics and astronomy.
Furthermore, we report on our experiences with the photography of optical phenomena such as polar lights and green flash.
After the successful International Year of Light 2015, the idea of sustainability became increasingly imminent. After a preparatory year on 16 May 2018, the International Day of Light was launched for the first time. This event was celebrated with a public celebration in Paris at the UNESCO headquarters. In this paper we will present our projects dedicated to the International Day of Light in Paris. Together with a group of students from our university, we had the special opportunity to be integrated in the program of the opening ceremony at UNESCO in Paris. With our interdisciplinary projects we have tried to build a bridge between optics, photonics, art and media installations.
The authors explain a developed concept for research-oriented education in optics and photonics. It is presented which goals are to be achieved, which strategies have been developed and how these can be implemented in a blended learning scenario. The goal of our education is the best possible qualification of the students on the basis of a strong scientific and research-oriented education, which also includes the acquisition of important interdisciplinary competences. All phases of a research process are to be mapped in the learning process and offer students an insight into current research topics in optics and photonics.
Increased knowledge transfer through the integration of research projects into university teaching
(2019)
This paper describes the integration of the research project "Characterization of Color Vision using Spectroscopy and Nanotechnology: Application to Media Photonics" into an engineering course in the field of media technology. The aim is to develop the existing learning concept towards a more research-oriented teaching. Involving students in research projects as part of the learning process provides a deeper insight into current research topics and the key elements of scientific work. This makes it easier for students to recognize the importance of the acquired theoretical knowledge for the practice, which enables them to derive new insights of their own.
Walking interfaces offer advantages in navigation of VE systems over other types of locomotion. However, VR helmets have the disadvantage that users cannot see their immediate surroundings. Our publication describes the prototypical implementation of a virtual environment (VE) system, capable of detecting possible obstacles using an RGB-D sensor. In order to warn users of potential collisions with real objects while they are moving throughout the VE tracking area, we designed 4 different visual warning metaphors: Placeholder, Rubber Band, Color Indicator and Arrow. A small pilot study was carried out in which the participants had to solve a simple task and avoid any arbitrarily placed physical obstacles when crossing the virtual scene. Our results show that the Placeholder metaphor (in this case: trees), compared to the other variants, seems to be best suited for the correct estimation of the position of obstacles and in terms of the ability to evade them.
This paper presents the use of model predictive control (MPC) based approach for peak shaving application of a battery in a Photovoltaic (PV) battery system connected to a rural low voltage gird. The goals of the MPC are to shave the peaks in the PV feed-in and the grid power consumption and at the same time maximize the use of the battery. The benefit to the prosumer is from the maximum use of the self-produced electricity. The benefit to the grid is from the reduced peaks in the PV feed-in and the grid power consumption. This would allow an increase in the PV hosting and the load hosting capacity of the grid.
The paper presents the mathematical formulation of the optimal control problem
along with the cost benefit analysis. The MPC implementation scheme in the
laboratory and experiment results have also been presented. The results show
that the MPC is able to track the deviation in the weather forecast and operate
the battery by solving the optimal control problem to handle this deviation.
Model-based analysis of Electrochemical Pressure Impedance Spectroscopy (EPIS) for PEM Fuel Cells
(2019)
Electrochemical impedance spectroscopy (EIS) is a widely-used diagnostic technique to characterize electrochemical processes. It is based on the dynamic analysis of two electrical observables, that is, current and voltage. Electrochemical cells with gaseous reactants or products, in particular fuel cells, offer an additional observable, that is, the gas pressure. The dynamic coupling of current or voltage with gas pressure gives rise to a number of additional impedance definitions, for which we have previously introduced the term electrochemical pressure impedance spectroscopy (EPIS) [1,2]. EPIS shows a particular sensitivity towards transport processes of gas-phase or dissolved species, in particular, diffusion coefficients and transport pathway lengths. It is as such complementary to standard EIS, which is mainly sensitive towards electrochemical processes. First EPIS experiments on PEM fuel cells have recently been shown [3].
We present a detailed modeling and simulation analysis of EPIS of a PEM fuel cell. We use a 1D+1D continuum model of a fuel/air channel pair with GDL and MEA. Backpressure is dynamically varied, and the resulting simulated oscillation in cell voltage is evaluated to yield the ▁Z_( V⁄p_ca ) EPIS signal. Results are obtained for different transport situations of the fuel cell, giving rise to very complex EPIS shapes in the Nyquist plot. This complexity shows the necessity of model-based interpretation of the complex EPIS shapes. Based on the simulation results, specific features in the EPIS spectra can be assigned to different transport domains (gas channel, GDL, membrane water transport).
Die Vorlesung Physik ist ein grundlegender Baustein der meisten Ingenieursstudiengänge und stellt für viele Studienanfänger eine Hürde zum Studienstart da. Die Vorkenntnisse der Studienanfänger sind zunehmend heterogen und der sichere Umgang mit physikalischen Konzepten erfordert mehr oder wenig Übung, um diese zu festigen oder auch erstmals einzuführen. Um dieses Üben zu ermöglichen, wurde für die Vorlesung "Physik 1" in den Studiengängen Maschinenbau, Werkstofftechnik, Mechatronik, Biomechanik, Biotechnologie und Umwelt- und Verfahrenstechnik der Hochschule Offenburg ein E-Tutorium erarbeitet, das die Übungsaufgaben in Form von 10 Online-Selbsttest mit jeweils vier Übungsaufgaben anbietet. Die Selbsttests beinhalten dabei typische Aufgabenstellungen, deren Zahlenwerte (Masse, Geschwindigkeit usw.) bei jedem Aufruf der Aufgabe variieren. Dadurch lassen sich die Selbsttests zum selbständigen Üben nutzen. Ein reines Abschreiben einer Musterlösung ist durch die veränderlichen Zahlenwerte darüber hinaus unmöglich. Wir beschreiben eine Methode zur effizienten Erzeugung der Moodle-basierten Selbsttests mit Hilfe der Software R/exams und berichten über die Erfahrungen beim ersten Einsatz.
Protecting software from illegal access, intentional modification or reverse engineering is an inherently difficult practical problem involving code obfuscation techniques and real-time cryptographic protection of code. In traditional systems a secure element (the "dongle") is used to protect software. However, this approach suffers from several technical and economical drawbacks such as the dongle being lost or broken.
We present a system that provides such dongles as a cloud service, and more importantly, provides the required cryptographic material to control access to software functionality in real-time.
This system is developed as part of an ongoing nationally funded research project and is now entering a first trial stage with stakeholders from different industrial sectors.