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Targeting complex fractionated atrial electrocardiograms by automated algorithms during ablation of persistent atrial fibrillation has produced conflicting outcomes in previous electrophysiological studies and catheter ablation of atrial fibrillation and ventricular tachycardia. The aim of the investigation was to evaluate atrial and ventricular high frequency fractionated electrical signals with signal averaging technique.
Methods: Signal averaging electrocardigraphy allows high resolution ECG technique to eliminate interference noise signals in the recorded ECG. The algorithm use automatic ECG trigger function for signal averaged transthoracic, transesophageal and intra-cardiac ECG signals with novel LabVIEW software.
Results: The analysis in the time domain evaluated fractionated atrial signals at the end of the signal averaged P-wave and fractionated ventricular signals at the end of the QRS complex. We evaluated atrial flutter in the time domain with two-to-one atrioventricular conduction, 212.0 ± 4.1 ms atrial cycle length, 426.0 ± 8.2 ms ventricular cycle length, 58.2 ± 1.8 ms P-wave duration, 119.6 ± 6.4 ms PQ duration, 103.0 ± 2.4 ms QRS duration and 296.4 ± 6.8 ms QT duration. The analysis in the frequency domain evaluated high frequency fractionated atrial signals during the P-wave and high frequency fractionated ventricular signals during QRS complex.
Conclusions: Spectral analysis of signal averaging electrocardiography with novel LabVIEW software can be utilized to evaluate atrial and ventricular conduction delays in patients with atrial fibrillation and ventricular tachycardia. Complex fractionated atrial and ventricular electrocardiograms may be useful parameters to evaluate electrical cardiac bradycardia and tachycardia signals in atrial fibrillation and ventricular tachycardia ablation.
Spectral analysis of signal averaging electrocardiography in atrial and ventricular tachyarrhythmias
(2017)
Background: Targeting complex fractionated atrial electrograms detected by automated algorithms during ablation of persistent atrial fibrillation has produced conflicting outcomes in previous electrophysiological studies. The aim of the investigation was to evaluate atrial and ventricular high frequency fractionated electrical signals with signal averaging technique.
Methods: Signal averaging electrocardiography (ECG) allows high resolution ECG technique to eliminate interference noise signals in the recorded ECG. The algorithm uses automatic ECG trigger function for signal averaged transthoracic, transesophageal and intracardiac ECG signals with novel LabVIEW software (National Instruments, Austin, Texas, USA). For spectral analysis we used fast fourier transformation in combination with spectro-temporal mapping and wavelet transformation for evaluation of detailed information about the frequency and intensity of high frequency atrial and ventricular signals.
Results: Spectral-temporal mapping and wavelet transformation of the signal averaged ECG allowed the evaluation of high frequency fractionated atrial signals in patients with atrial fibrillation and high frequency ventricular signals in patients with ventricular tachycardia. The analysis in the time domain evaluated fractionated atrial signals at the end of the signal averaged P-wave and fractionated ventricular signals at the end of the QRS complex. The analysis in the frequency domain evaluated high frequency fractionated atrial signals during the P-wave and high frequency fractionated ventricular signals during QRS complex. The combination of analysis in the time and frequency domain allowed the evaluation of fractionated signals during atrial and ventricular conduction.
Conclusions: Spectral analysis of signal averaging electrocardiography with novel LabVIEW software can utilized to evaluate atrial and ventricular conduction delays in patients with atrial fibrillation and ventricular tachycardia. Complex fractionated atrial electrograms may be useful parameters to evaluate electrical cardiac arrhythmogenic signals in atrial fibrillation ablation.
The industry of the agave-derived bacanora, in the northern Mexican state of Sonora, has been growing substantially in recent years. However, this higher demand still lies under the influences of a variety of social, legal, cultural, ecological and economic elements. The governmental institutions of the state have tried to encourage a sustainable development and certain levels of standardization in the production of bacanora by applying different economical and legal strategies. However, a large portion of this alcoholic beverage is still produced in a traditional and rudimentary fashion. Beyond the quality of the beverage, the lack of proper control, by using adequate instrumental methods, might represent a health risk, as in several cases traditional-distilled beverages can contain elevated levels of harmful materials. The present article describes the qualitative spectral analysis of samples of the traditional-produced distilled beverage bacanora in the range from 0 cm−1 to 3500 cm−1 by using a Fourier Transform Raman spectrometer. This particular technique has not been previously explored for the analysis of bacanora, as in the case of other beverages, including tequila. The proposed instrumental arrangement for the spectral analysis has been built by combining conventional hardware parts (Michelson interferometer, photo-diodes, visible laser, etc.) and a set of self-developed evaluation algorithms. The resulting spectral information has been compared to those of pure samples of ethanol and to the spectra from different samples of the alcoholic beverage tequila. The proposed instrumental arrangement can be used the analysis of bacanora.
The formation of secondary phases in the porous electrodes is a severe mechanism affecting the lifetime of solid oxide fuel cells (SOFC). It can occur via various chemical mechanisms and it has a significant influence on cell performance due to pore clogging and deactivation of active surfaces and triple-phase boundary (TPB). We present a modeling and simulation study of nickel oxide formation (reoxidation) and carbon formation (coking) within the SOFC anode. We use a 2D continuum model based on a multi-phase framework [Neidhardt et al., J. Electrochem. Soc., 159, 9 (2012)] that allows the introduction of arbitrary solid phases (here: Ni, YSZ, NiO, Carbon) plus gas phase. Reactions between the bulk phases are modeled via interface-adsorbed species and are described by an elementary kinetic approach. Published experimental data are used for parameterization and validation. Simulations allow the prediction of cell performance under critical operation conditions, like (i) a non-fuel operation test, where NiO formation is taking place (Figure 1a), or (ii) an open circuit voltage (OCV) stability test under hydrocarbon atmosphere, where solid carbon is formed (Figure 1b). Results are applied for enhanced interpretation of experimental data and for prediction of safe operation conditions.
ECG simulators, available on the market, imitate the electric activity of the heart in a simplified manner. Thus, they are suitable for education purposes but not really for testing algorithms to recognize complex arrhythmias needed for pacemakers and implantable defibrillators. Especially certain discrimination between various morphologies of atrial and ventricular fibrillation needs simulators providing native electrograms of different patients’ heart rhythm events. This explains the necessity to develop an ECG simulator providing high-resolution native intracardiac and surface electrograms of in-vivo rhythm events. In this paper we demonstrate an approach for an ECG simulator based on a consumer multichannel soundcard and a corresponding software application for a laptop computer. This Live-ECG Simulator is able to handle invasive electrogram recordings from electrophysiological studies and send the data to a modified external soundcard for subsequent digital to analog conversion. The hardware is completed with an electronic circuit providing level adjustment to adapt the output amplitude to the input conditions of several cardiac implants.
We propose in this work to solve privacy preserving set relations performed by a third party in an outsourced configuration. We argue that solving the disjointness relation based on Bloom filters is a new contribution in particular by having another layer of privacy on the sets cardinality. We propose to compose the set relations in a slightly different way by applying a keyed hash function. Besides discussing the correctness of the set relations, we analyze how this impacts the privacy of the sets content as well as providing privacy on the sets cardinality. We are in particular interested in how having bits overlapping in the Bloom filters impacts the privacy level of our approach. Finally, we present our results with real-world parameters in two concrete scenarios.
Nonlinear acoustic waves are considered that have displacements localized at the tip of an elastic wedge. The evolution equation governing their propagation is discussed and compared with its analogues pertaining to nonlinear acoustic surface and bulk waves. Solitary wave solutions of the evolution equation have been determined numerically for the cases of two rectangular edges which may be viewed as generated by splitting a half-space, consisting of crystalline silicon, into two quarter-spaces. For these two geometries, the kernel in the nonlinear terms of the evolution equation has been calculated from the second-order and third-order elastic constants of silicon, and weak dispersion due to tip truncation has been considered. Solitary pulse shapes have been computed and collisions of solitary pulses have been simulated for various relative speeds of the two collision partners. Collision scenarios for the two wedge geometries were found to differ considerably. Special attention is paid to the peculiar interaction of two initially identical solitary pulses.
Für die solarunterstützte CO2-neutrale Nahwärmeversorgung des Neubaugebiets Hülben in Holzgerlingen wurden Holzpelletskessel mit einer 249m²-großen Solaranlage kombiniert. Im ersten Intensivmessjahr vom 01.03.2007 bis 29.02.2008 wurde eine Gesamt-Wärmeabgabe ins Nahwärmenetz von 920.606 kWh gemessen, wobei der solare Anteil bei 84.033 kWh lag. Es wurden ein Systemnutzungsgrad von 23,8 % und ein solarer Deckungsanteil von 9,5% gemessen. Die vom Lieferanten abgegebene Energiegarantie wurde in der ersten Intensivmessphase nicht erreicht.
The improvements in the hardware and software of communication devices have allowed running Virtual Reality (VR) and Augmented Reality (AR) applications on those. Nowadays, it is possible to overlay synthetic information on real images, or even to play 3D on-line games on smart phones or some other mobile devices. Hence the use of 3D data for business and specially for education purposes is ubiquitous. Due to always available at hand and always ready to use properties of mobile phones, those are considered as most potential communication devices. The total numbers of mobile phone users are increasing all over the world every day and that makes mobile phones the most suitable device to reach a huge number of end clients either for education or for business purposes. There are different standards, protocols and specifications to establish the communication among different communication devices but there is no initiative taken so far to make it sure that the send data through this communication process will be understood and used by the destination device. Since all the devices are not able to deal with all kind of 3D data formats and it is also not realistic to have different version of the same data to make it compatible with the destination device, it is necessary to have a prevalent solution. The proposed architecture in this paper describes a device and purpose independent 3D data visibility any time anywhere to the right person in suitable format. There is no solution without limitation. The architecture is implemented in a prototype to make an experimental validation of the architecture which also shows the difference between theory and practice.
Smoothie: a solution for device and content independent applications including 3D imaging as content
(2014)
Network landscape of recent time contains many different network technologies, a wide range of end-devices with a large scale of capabilities and power, and an immense quantity of information represented in different data formats. Research on 3D imaging, virtual reality and holographic techniques will result in new user interfaces (UI) for mobile devices and will increase their diversity and variety. A lot of effort is being made in order to establish open, scalable and seamless integration of various technologies and content presentation for different devices including those that are mobile, considering the individual situation of the end user. Till today the research is going on in different parts of the world but the task is not completed yet. The goal of this research work is to find a way to solve the above stated problems by investigating system architectures to provide unconstrained, continuous and personalized access to the content and interactive applications everywhere and at anytime with different devices. As a Solution of the problem considered, a new architecture named “Smoothie” is proposed.
Due to the rapidly increasing storage consumption worldwide, as well as the expectation of continuous availability of information, the complexity of administration in today’s data centers is growing permanently. Integrated techniques for monitoring hard disks can increase the reliability of storage systems. However, these techniques often lack intelligent data analysis to perform predictive maintenance. To solve this problem, machine learning algorithms can be used to detect potential failures in advance and prevent them. In this paper, an unsupervised model for predicting hard disk failures based on Isolation Forest is proposed. Consequently, a method is presented that can deal with the highly imbalanced datasets, as the experiment on the Backblaze benchmark dataset demonstrates.
Innovative technologies and concepts will emerge as we move towards a more dynamic, service-based, market-driven infrastructure, where energy efficiency and savings can be facilitated by interactive distribution networks. A new generation of fully interactive Information and Communication Technologies (ICT) infrastructure has to be developed to support the optimal exploitation of the changing, complex business processes and to enable the efficient functioning of the deregulated energy market for the benefit of citizens and businesses. The architecture of such distributed system landscapes must be designed and validated, standards need to be created and widely supported, and comprehensive, reliable IT applications will need to be implemented. The collaboration between a smart house and a smart grid is a promising approach which, with the help of ICT can fully unleash the capabilities of the smart electricity network.
The twin concept is increasingly used for optimization tasks in the context of Industry 4.0 and digitization. The twin concept can also help small and medium-sized enterprises (SME) to exploit their energy flexibility potential and to achieve added value by appropriate energy marketing. At the same time, this use of flexibility helps to realize a climate-neutral energy supply with high shares of renewable energies. The digital twin reflects real production, power flows and market influences as a computer model, which makes it possible to simulate and optimize on-site interventions and interactions with the energy market without disturbing the real production processes. This paper describes the development of a generic model library that maps flexibility-relevant components and processes of SME, thus simplifying the creation of a digital twin. The paper also includes the development of an experimental twin consisting of SME hardware components and a PLC-based SCADA system. The experimental twin provides a laboratory environment in which the digital twin can be tested, further developed and demonstrated on a laboratory scale. Concrete implementations of such a digital twin and experimental twin are described as examples.
With major intellectual properties there is a long tradition of cross-media value chains -- usually starting with books and comics, then transgressing to film and TV and finally reaching interactive media like video games. In recent years the situation has changed: (1) smaller productions start to establish cross media value chains; (2) there is a trend from sequential towards parallel content production. In this work we describe how the production of a historic documentary takes a cross media approach right from the start. We analyze how this impacts the content creation pipelines with respect to story, audience and realization. The focus of the case study is the impact on the production of a documentary game. In a second step we reflect on the experiences gained so far and derive recommendations for future small-scale cross media productions.
Avoiding collisions between a robot arm and any obstacle in its path is essential to human-robot collaboration. Multiple systems are available that can detect obstacles in the robot's way prior and subsequent to a collision. The systems work well in different areas surrounding the robot. One area that is difficult to handle is the area that is hidden by the robot arm. This paper focuses on pick and place maneuvers, especially on obstacle detection in between the robot arm and the table that robot is located on. It introduces the use of single pixel time-of-flight sensors to detect obstacles directly from the robot arm. The proposed approach reduces the complexity of the problem by locking axes of the robot that are not needed for the pick and place movement. The comparison of simulated results and laboratory measurements show concordance.
Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
The insufficient lifetime of lithium-ion batteries is one of the major cost driver for mobile applications. The battery pack in vehicles is one of the most expensive single components that practically must be excluded from premature replacement (i.e., before the life span of the other components end). Battery degradation is a complex physicochemical process that strongly depends on operating condition and environment. We present a simulation-based analysis of lithium-ion battery degradation during operation with a standard PHEV test cycle. We use detailed multiphysics (extended Newman-type) cell models that allow the assessment of local electrochemical potential, species and temperature distributions as driving forces for degradation, including solid electrolyte interphase (SEI) formation [1]. Fig. 1 shows an exemplary test cycle and the predicted resulting spatially-averaged SEI formation rate. We apply a time-upscaling approach to extrapolate the degradation analysis over long time scales, keeping physical accuracy while allowing end-of-life assessment [2]. Results are presented for lithium-ion battery cells with graphite/LFP chemistry. The behavior of these cells in terms of degradation propensity, performance, state of charge and other internal states is predicted during long-term cycling. State of health (SOH) is quantified as capacity fade and internal resistance increase as function of operation time.
Simulation-based degradation assessment of lithium-ion batteries in a hybrid electric vehicle
(2017)
Hot forging dies are subjected to high cyclic thermo-mechanical loads. In critical areas, the occurring stresses can exceed the material’s yield limit. Additionally, loading at high temperatures leads to thermal softening of the used martensitic materials. These effects can result in an early crack initiation and unexpected failure of the dies, usually described as thermo-mechanical fatigue (TMF). In previous works, a temperature-dependent cyclic plasticity model for the martensitic hot forging tool steel 1.2367 (X38CrMoV5-3) was developed and implemented in the finite element (FE)-software Abaqus. However, in the forging industry, application-specific software is usually used to ensure cost-efficient numerical process design. Therefore, a new implementation for the FE-software Simufact Forming 16.0 is presented in this work. The results are compared and validated with the original implementation by means of a numerical compression test and a cyclic simulation is calculated with Simufact Forming.
The electrical field (E-field) of the biventricular (BV) stimulation is important for the success of cardiac resynchronization therapy (CRT) in patients with cardiac insufficiency and widened QRS complex.
The aim of the study was to model different pacing and ablation electrodes and to integrate them into a heart model for the static and dynamic simulation of BV stimulation and HF ablation in atrial fibrillation (AF).
The modeling and simulation was carried out using the electromagnetic simulation software CST. Five multipolar left ventricular (LV) electrodes, four bipolar right atrial (RA) electrodes, two right ventricular (RV) electrodes and one HF ablation catheter were modelled. A selection were integrated into the heart rhythm model (Schalk, Offenburg) for the electrical field simulation. The simulation of an AV node ablation at CRT was performed with RA, RV and LV electrodes and integrated ablation catheter with an 8 mm gold tip.
The BV stimulation were performed simultaneously at amplitude of 3 V at the LV electrode and 1 V at the RV electrode with a pulse width of 0.5 ms each. The far-field potential at the RA electrode tip was 32.86 mV and 185.97 mV at a distance of 1 mm from the RA electrode tip. AV node ablation was simulated with an applied power of 5 W at 420 kHz at the distal ablation electrode. The temperature at the catheter tip was 103.87 °C after 5 s ablation time and 37.61 °C at a distance of 2 mm inside the myocardium. After 15 s, the temperature was 118.42 °C and 42.13 °C.
Virtual heart and electrode models as well as the simulations of electrical fields and temperature profiles allow the static and dynamic simulation of atrial synchronous BV stimulation and HF ablation at AF and could be used to optimize the CRT and AF ablation.
Background: The electrical field (E-field) of the biventricular (BV) stimulation is essential for the success of cardiac resynchronization therapy (CRT) in patients with cardiac insufficiency and widened QRS complex. 3D modeling allows the simulation of CRT and high frequency (HF) ablation.
Purpose: The aim of the study was to model different pacing and ablation electrodes and to integrate them into a heart model for the static and dynamic simulation of BV stimulation and HF ablation in atrial fibrillation (AF).
Methods: The modeling and simulation was carried out using the electromagnetic simulation software. Five multipolar left ventricular (LV) electrodes, one epicardial LV electrode, four bipolar right atrial (RA) electrodes, two right ventricular (RV) electrodes and one HF ablation catheter were modeled. Different models of electrodes were integrated into a heart rhythm model for the electrical field simulation (fig.1). The simulation of an AV node ablation at CRT was performed with RA, RV and LV electrodes and integrated ablation catheter with an 8 mm gold tip.
Results: The RV and LV stimulation were performed simultaneously at amplitude of 3 V at the LV electrode and 1 V at the RV electrode, each with a pulse width of 0.5 ms. The far-field potentials generated by the BV stimulations were perceived by the RA electrode. The far-field potential at the RA electrode tip was 32.86 mV. A far-field potential of 185.97 mV resulted at a distance of 1 mm from the RA electrode tip. AV node ablation was simulated with an applied power of 5 W at 420 kHz at the distal 8 mm ablation electrode. The temperature at the catheter tip was 103.87 ° C after 5 s ablation time, 44.17 ° C from the catheter tip in the myocardium and 37.61 ° C at a distance of 2 mm. After 10 s, the temperature at the three measuring points described above was 107.33 ° C, 50.87 ° C, 40.05 ° C and after 15 seconds 118.42 ° C, 55.75 ° C and 42.13 ° C.
Conclusions: Virtual heart and electrode models as well as the simulations of electrical fields and temperature profiles allow the static and dynamic simulation of atrial synchronous BV stimulation and HF ablation at AF. The 3D simulation of the electrical field and temperature profile may be used to optimize the CRT and AF ablation.
In den Unternehmen der Automobilbranche herrscht ein beträchtlicher Rationalisierungsdruck mit einem daraus folgenden hohen Automatisierungsgrad. Den erheblichen Investitionen in modernste Fertigungstechnologien und Montageanlagen steht zunehmend die Forderung eines Return of Investment mit zweistelligen Prozentsätzen gegenüber. Betriebliche Abläufe und Fertigungsprozesse werden daher sehr detailliert geplant, wobei 'minutiöse' Planungen oftmals nur die Beherrschung komplexer Prozeßabläufe vortäuschen. Ungeplante Einflußfaktoren und Störungen lassen manche Planung schnell zu Makulatur verkommen.
Geschäftsprozeßmodellierung und dynamische Simulationen von Fertigungsprozessen mittels zeitbewerteter Petri-Netze, bieten ausgezeichnete Möglichkeiten, komplexe Zusammenhänge transparenter zu machen und neue Erkenntnisse über die Einflüsse von Störungen oder Qualitätsschwankungen auf die Produkt- und Prozeßqualität zu erhalten. In einem Teilbereich der Produktion der Daimler-Benz AG in Gaggenau wurden Qualitätsstörungen und ihre Wirkungen auf den Fertigungsprozeß von Drehmomentwandlern untersucht. Die im Fertigungsverlauf auftretenden qualitätsbeeinflussenden Störungen wurden in Petri-Netz-Modellen abgebildet und in diversen Szenerien simuliert. Die Auswirkungen auf die Anlagenverfügbarkeit, Durchlaufzeiten, Lagerstrategien und die Kostensituationen wurden verdeutlicht und erste Maßnahmen mit den zugehörigen Voraussetzungen aufgezeigt.
Patients with focal ventricular tachycardia are at risk of hemodynamic failure and if no treatment is provided the mortality rate can exceed 30%. Therefore, medical professionals must be adequately trained in the management of these conditions. To achieve the best treatment, the origin of the abnormality should be known, as well as the course of the disease. This study provides an opportunity to visualize various focal ventricular tachycardias using the Offenburg cardiac rhythm model.
3D printing offers customisation capabilities regarding suspensions for oscillators of vibration energy harvesters. Adjusting printing parameters or geometry allows to influence dynamic properties like resonance frequency or bandwidth of the oscillator. This paper presents simulation results and measurements for a spiral shaped suspension printed with polylactic acid (PLA) and different layer heights. Eigenfrequencies have been simulated and measured and damping ratios have been experimentally determined.
WirelessHART protocol was specifically designed for real-time communication in the wireless sensor networks domain for industrial process automation requirements. Whereas the major purpose of WirelessHART is the read-out of sensors with moderate real-time requirements, an increasing demand for integration of actuator applications can be observed. Therefore, it must be verified that the WirelessHART protocol gives sufficient support to real-time industry requirements. As a result, the delay of especially burst and command messages from actuator and sensor nodes to the gateway and vice versa must be analyzed. In this paper, we implemented a WirelessHART network scenario in WirelessHART simulator in NS-2 [8], simulated and analyzed its time characteristics under ideal and noisy conditions. We evaluated the performance of the implementation in order to verify whether the requirements of industrial process and control can be met. This implementation offers an early alternative to expensive test beds for WirelessHART in real-time actuator applications.
Significance of new electrocardiographic parameters to improve cardiac resynchronization therapy
(2011)
Introduction: Oesophageal left heart electrogram (LHE) is a valuable tool providing electrocardiographic parameters for cardiac resynchronization therapy (CRT). It can be utilized to measure left ventricular (LVCD) and intra-leftventricular conduction delays (ILVCD) in heart failure patients to justify implantation of CRT systems. In the follow-up, LHE enables measurement of implant-related interatrial conduction times (IACT) which are the key intervals defining the hemodynamically optimal AV delay (AVD).
Methods: By TOSlim oesophageal electrode and Rostockfilter (Osypka AG, Rheinfelden, Germany), LHE was recorded in 39 heart failure patients (10f, 29m, 65±8yrs., QRS=163±21ms) after implantation of CRT systems according to guidelines. In position of maximal left ventricular deflection, LVCD and ILVCD were measured and compared with QRS width. In position of maximal left atrial deflection (LA), IACT was determined in VDD and DDD operation as interval As-LA and Ap-LA between atrial sense event (As) or stimulus (Ap), resp., and onset of LA. AVD was individualized using SAV =As-LA + 50ms for VDD and PAV=Ap-LA + 50ms for DDD operation.
Results: The CRT patients were characterized by minimal transoesophageal LVCD of 40ms but 73±20ms, at mean, ILVCD of 90±24ms and QRS/LVCD ratio of 2.4±0.6. The measured As-LA of 39±24ms and Ap-LA of 124±26ms resulted into SAV of 89±24ms and PAV of 174±26ms. In case of empirical AVD programming using 120ms for SAV and 180ms for PAV, the LHE revealed inverse sequences of LA and Vp in 4 patients (10%) during VDD and 13 patients (33%) in DDD pacing. In these patients, Vp preceded LA as IACT exceeded the programmed AVD.
Conclusion: Guideline indication of CRT systems is associated with LVCD of 40ms or more. Therefore, individual LVCD offers the minimal target interval that should be reached during left ventricular electrode placement to increase responder rate. Postoperatively, AV delay optimization respecting implant-related IACTs excludes adverse hemodynamic effects.
Cardiac resynchronization therapy with biventricular pacing is an established therapy for heart failure patients with electrical left ventricular desynchronization. The aim of this study was to evaluate left atrial conduction delay, intra left atrial conduction delay, left ventricular conduction delay and intra left ventricular conduction delay in heart failure patients using novel signal averaging transesophageal left heart ECG software.
Methods: 8 heart failure patients with dilated cardiomyopathy (DCM), age 68 ± 9 years, New York Heart Association (NYHA) class 2.9 ± 0.2, 24.8 ± 6.7 % left ventricular ejection fraction, 188.8 ± 15.5 ms QRS duration and 8 heart failure patients with ischaemic cardiomyopathy (ICM), age 67 ± 8 years, NYHA class 2.9 ± 0.3, 32.5 ± 7.4 % left ventricular ejection fraction and 167.6 ± 19.4 ms QRS duration were analysed with transesophageal and transthoracic ECG by Bard LabDuo EP system and novel National Intruments LabView signal averaging ECG software.
Results: The electrical left atrial conduction delay was 71.3 ± 17.6 ms in ICM versus 72.3 ± 12.4 ms in DCM, intra left atrial conduction delay 66.8 ± 8.6 ms in ICM versus 63.4 ± 10.9 ms in DCM and left cardiac AV delay 180.5 ± 32.6 ms in ICM versus 152.4 ± 30.4 ms in DCM. The electrical left ventricular conduction delay was 40.9 ± 7.5 ms in ICM versus 42.6 ± 17 ms in DCM and intra left ventricular conduction delay 105.6 ± 19.3 ms in ICM versus 128.3 ± 24.1 ms in DCM.
Conclusions: Left heart signal averaging ECG can be utilized to analyse left atrial conduction delay, intra left atrial conduction delay, left ventricular conduction delay and intra left ventricular conduction delay to improve patient selection for cardiac resynchronization therapy.
Immer mehr Anwendungen der Heim- und der Gebäudeautomatisierung werden vernetzt, weil damit erweiterte Funktionen ermöglicht oder Kosten gespart werden können. Dabei führt eine Reihe von Aspekten zu einem erhöhten Risiko für diese vernetzten Systeme. Gegenwärtig arbeiten verschiedene Gruppen an Sicherheitslösungen für die vernetzte Heim- und Gebäudeautomatisierung. Der Beitrag gibt einen Überblick über diese Aktivitäten und zeigt die wesentlichen Entwicklungsrichtungen auf.
Sichere Detektion von Menschen in der Mensch-Roboter-Kollaboration mit Time-of-Flight Kameras
(2017)
We aim to debate and eventually be able to carefully judge how realistic the following statement of a young computer scientist is: “I would like to become an ethical correctly acting offensive cybersecurity expert”. The objective of this article is not to judge what is good and what is wrong behavior nor to present an overall solution to ethical dilemmas. Instead, the goal is to become aware of the various personal moral dilemmas a security expert may face during his work life. For this, a total of 14 cybersecurity students from HS Offenburg were asked to evaluate several case studies according to different ethical frameworks. The results and particularities are discussed, considering different ethical frameworks. We emphasize, that different ethical frameworks can lead to different preferred actions and that the moral understanding of the frameworks may differ even from student to student.
Erlang is a functional programming language with dynamic typing. The language offers great flexibility for destructing values through pattern matching and dynamic type tests. Erlang also comes with a type language supporting parametric polymorphism, equi-recursive types, as well as union and a limited form of intersection types. However, type signatures only serve as documentation; there is no check that a function body conforms to its signature.
Set-theoretic types and semantic subtyping fit Erlang’s feature set very well. They allow expressing nearly all constructs of its type language and provide means for statically checking type signatures. This article brings set-theoretic types to Erlang and demonstrates how existing Erlang code can be statically type checked without or with only minor modifications to the code. Further, the article formalizes the main ingredients of the type system in a small core calculus, reports on an implementation of the system, and compares it with other static type checkers for Erlang.
Separation Estimation with Thermal Cameras for Separation Monitoring in Human-Robot Collaboration
(2022)
Human-Robot Collaborative applications have the drawback of being less efficient than their non-collaborative counterparts. One of the main reasons is, that the robot has to slow down when a human being is within the operating space of the robot. There are different approaches on dynamic speed and separation monitoring in human-robot collaborative applications. One approach additionally differentiates between human and non-human objects to increase efficiency in speed and separation monitoring. This paper proposes to estimate the separation distance by measuring the temperature of the approaching object. Measurements show that the measured temperature of a human being decreases with 1 deg C per meter distance from the sensor. This allows an estimation of separation between a robotic system and a human being.
Die in dieser Arbeit vorgestellte Vorgehensweise erlaubt die Ortung von Schienenfahrzeugen in topologischen Karten allein mit Hilfe eines Wirbelstromsensorsystems (WSS). Zur Ortung primär erforderlich ist die Identifizierung des befahrenen Gleises selbst, wofür unterschiedliche in einer Karte gespeicherte Merkmale herangezogen werden sowie der zurückgelegte Weg, der durch Zählen der passierten Schwellen ermittelt wird. Diese Merkmale werden mittels eigens definierter, virtueller Sensoren aus dem Signal des WSS gewonnen und mittels einem Bayes’schen Formalismus mit den Referenzdaten aus der vorliegenden topologischen Karte abgeglichen. Diese auf virtuellen Sensoren basierende Vorgehensweise erlaubt eine Parallelisierung der Sensorsignalverarbeitung und eine flexible Einbindung von Sensoren in das Ortungssystem. Die Möglichkeit, Weichen mit einer Trefferquote von 99% zu detektieren, erlaubt die Verfolgung der Fahrzeugposition über die gesamte Fahrstrecke hinweg, unter alleiniger Verwendung der vom WSS gelieferten Messdaten.
Introduction: Cardiac resynchronization therapy (CRT) with left ventricular (LV) pacing is an established therapy for heart failure (HF) patients (P) with ventricular desynchronisation and reduced LV ejection fraction (EF). The aim of this study was to test the utilization of the transesophageal approach to measure arterial pulse pressure (PP) during LV pacing and electrical interventricular conduction delay (IVCD), to better select patients for CRT.
Methods: 32 HF patients (age 64 ± 10 years; 5 females, 27 males) with New York Heart Association (NYHA) class 2.8 ± 0.6, 27 ± 11 % LV EF and 155 ± 35 ms QRS duration were analysed with semi-invasive left cardiac pacing and electrocardiography. Esophageal TO8 Osypka catheter of 10.5 F diameter was perorally applied to the esophagus and placed in the position of maximum left atrial (LA) deflection and maximum LV deflection to measure PP with VAT or D00 pacing modes.
Results: Temporary transesophageal LV pacing was possible with VAT mode (n=16) and D00 mode (n=16) in all patients. In 15 Δ-PP-responders, PP was higher during LV pacing on than LV pacing off (78.3 ± 26.6 versus 65.9 ± 23.7 mmHg, P < 0.001) and NYHA class improved from 3.1 ± 0.35 to 2.1 ± 0.35 (P < 0.001) during 29 ± 26 month biventricular (BV) pacing follow-up (6 Medtronic and 9 Boston BV pacing devices). In 17 Δ-PP-non-responders, PP was not higher during LV pacing on than LV pacing off (61.5 ± 23.9 versus 60.9 ± 23.5 mmHg, P = 0.066). IVCD was significant longer in Δ-PP-responders than in Δ-PP-non-responders (87 ± 33 ms versus 37± 29 ms, P < 0.001).
Conclusion: Semi-invasive transesophageale LA and LV pacing with D00 and VAT mode and LV electrogram recording may be useful techniques to predict CRT improvement.
Semi-invasive electromechanical target interval to guide left ventricular electrode placement
(2011)
Using guideline parameters for indication of cardiac resynchronization therapy (CRT), only about two thirds of the patients improve clinically. Unfortunately both, surface ECG and echo are uncertain to predict CRT response. To better characterize cardiac desynchronization in heart failure, interventricular (IVCD) and intra-leftventricular conduction delays (ILVCD) were measured by esophageal left ventricular electrogram (LVE). Recordings in 43 CRT patients (34m, 9f, age: 64.7 ± 9.5yrs) evidenced only weak correlation between IVCD and QRS of 0.53 and between ILVCD and QRS of 0.33. This demonstrated that QRS duration is not a reliable indicator of desynchronization. Therefore, the study resulted into development of LVE feature for a programmer with implant support device. It can be used interoperatively to guide the left ventricular electrode location in order to increase responder rate in CRT.
Featherweight Go (FG) is a minimal core calculus that includes essential Go features such as overloaded methods and interface types. The most straightforward semantic description of the dynamic behavior of FG programs is to resolve method calls based on run-time type information. A more efficient approach is to apply a type-directed translation scheme where interface-values are replaced by dictionaries that contain concrete method definitions. Thus, method calls can be resolved by a simple lookup of the method definition in the dictionary. Establishing that the target program obtained via the type-directed translation scheme preserves the semantics of the original FG program is an important task.
To establish this property we employ logical relations that are indexed by types to relate source and target programs. We provide rigorous proofs and give a detailed discussion of the many subtle corners that we have encountered including the need for a step index due to recursive inter- faces and method definitions.
Seismic data processing relies on multiples attenuation to improve inversion and interpretation. Radon-based algorithms are often used for multiples and primaries discrimination. Deep learning, based on convolutional neural networks (CNNs), has shown encouraging applications for demultiple that could mitigate Radon-based challenges. In this work, we investigate new strategies to train a CNN for multiples removal based on different loss functions. We propose combined primaries and multiples labels in the loss for training a CNN to predict primaries, multiples, or both simultaneously. Moreover, we investigate two distinctive training methods for all the strategies: UNet based on minimum absolute error (L1) training, and adversarial training (GAN-UNet). We test the trained models with the different strategies and methods on 400 synthetic data. We found that training to predict multiples, including the primaries …
The provisioning of security for highly dynamic wireless networks, as for Car2X applications is still a major topic, as very specific requirements have to be solved. Those include a perfect privacy level and advanced real-time behavior, and the necessity to work with a public infrastructure (PKI) to support secure authentication.
This contribution analyzes these requirements, discusses the existing approaches, performs a gap analysis and elaborates on proposals to fill these gaps. It describes work in progress within the KoFAS-initiative for the development of a cooperative pedestrian protection system (CPPS).
Printed electronics can add value to existing products by providing new smart functionalities, such as sensing elements over large-areas on flexible or non-conformal surfaces. Here we present a hardware concept and prototype for a thinned ASIC integrated with an inkjet-printed temperature sensor alongside in-built additional security and unique identification features. The hybrid system exploits the advantages of inkjet-printable platinum-based sensors, physically unclonable function circuits and a fluorescent particle-based coating as a tamper protection layer.
The number of use cases for autonomous vehicles is increasing day by day especially in commercial applications. One important application of autonomous vehicles can be found within the parcel delivery section. Here, autonomous cars can massively help to reduce delivery efforts and time by supporting the courier actively. One important component of course is the autonomous vehicle itself. Nevertheless, beside the autonomous vehicle, a flexible and secure communication architecture also is a crucial key component impacting the overall performance of such system since it is required to allow continuous interactions between the vehicle and the other components of the system. The communication system must provide a reliable and secure architecture that is still flexible enough to remain practical and to address several use cases. In this paper, a robust communication architecture for such autonomous fleet-based systems is proposed. The architecture provides a reliable communication between different system entities while keeping those communications secure. The architecture uses different technologies such as Bluetooth Low Energy (BLE), cellular networks and Low Power Wide Area Network (LPWAN) to achieve its goals.
Qualitative Wissenschaft, künstlerisches Forschen und forschendes Lernen verbinden Erkenntnis aus Praxis und Erfahrung. In der Autoethnographie der eigenen Werkstatt des Hörens wie der Kultur in Studios anderer, wird die noch neue Interdisziplin Sound (Studies) erprobt und vertieft, mit Impulsen für die Praxis und Theorie, von der noch wenig bekannten A/r/t ographie heute, hin zu einer künftig A/R/Tophonie, dem künstlerischen Forschen in der Musik, ebenso wie durch Klang Komposition, Radio Kunst und visuelle Musik.
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.
Engineering, construction and operation of complex machines involves a wide range of complicated, simultaneous tasks, which potentially could be automated. In this work, we focus on perception tasks in such systems, investigating deep learning approaches for multi-task transfer learning with limited training data. We show an approach that takes advantage of a technical systems’ focus on selected objects and their properties. We create focused representations and simultaneously solve joint objectives in a system through multi-task learning with convolutional autoencoders. The focused representations are used as a starting point for the data-saving solution of the additional tasks. The efficiency of this approach is demonstrated using images and tasks of an autonomous circular crane with a grapple.
The contribution of the RoofKIT student team to the SDE 21/22 competition is the extension of an existing café in Wuppertal, Germany, to create new functions and living space for the building with simultaneous energetic upgrading. A demonstration unit is built representing a small cut-out of this extension. The developed energy concept was thoroughly simulated by the student team in seminars using Modelica. The system uses mainly solar energy via PVT collectors as the heat source for a brine-water heat pump (space heating and hot water). Energy storage (thermal and electrical) is installed to decouple generation and consumption. Simulation results confirm that carbon neutrality is achieved for the building operation, consuming and generating around 60 kWh/m2a.
The growing complexity in RF front-ends, which support carrier aggregation and a growing number of frequency bands, leads to tightened nonlinearity requirements in all sub-components. The generation of third order intermodulation products (IMD3) are typical problems caused by the non-linearity of SAW devices. In the present work, we investigate temperature compensating (TC) SAW devices on Lithium Niobate-rot128YX. An accurate FEM simulation model [1] is employed, which allows to better understand the origin of nonlinearities in such acoustic devices.
In the present work, nonlinearities in temperature compensating (TC) SAW devices are investigated. The materials used are LiNbO₃-rot128YX as the substrate and Copper electrodes covered with a SiO₂-layer as the compensating layer. In order to understand the role of these materials for the nonlinearities in such acoustic devices, a FEM simulation model in combination with a perturbation approach is applied. The nonlinear tensor data of the different materials involved in TC-SAW devices have been taken from literature, but were partially modified to fit experimental data by introducing scaling factors. An effective nonlinearity constant is determined by comparison of nonlinear P-matrix simulations to IMD3 measurements of test filters. By employing these constants in nonlinear periodic P-matrix simulations a direct comparison to nonlinear periodic FEM-simulations yields the scaling factors for the material used. Thus, the contribution of different materials to the nonlinear behavior of TC-SAW devices is obtained and the role of metal electrodes is discussed in detail.
Despite the success of convolutional neural networks (CNNs) in many academic benchmarks for computer vision tasks, their application in the real-world is still facing fundamental challenges. One of these open problems is the inherent lack of robustness, unveiled by the striking effectiveness of adversarial attacks. Current attack methods are able to manipulate the network's prediction by adding specific but small amounts of noise to the input. In turn, adversarial training (AT) aims to achieve robustness against such attacks and ideally a better model generalization ability by including adversarial samples in the trainingset. However, an in-depth analysis of the resulting robust models beyond adversarial robustness is still pending. In this paper, we empirically analyze a variety of adversarially trained models that achieve high robust accuracies when facing state-of-the-art attacks and we show that AT has an interesting side-effect: it leads to models that are significantly less overconfident with their decisions, even on clean data than non-robust models. Further, our analysis of robust models shows that not only AT but also the model's building blocks (like activation functions and pooling) have a strong influence on the models' prediction confidences. Data & Project website: https://github.com/GeJulia/robustness_confidences_evaluation
Despite the success of convolutional neural networks (CNNs) in many academic benchmarks for computer vision tasks, their application in the real-world is still facing fundamental challenges. One of these open problems is the inherent lack of robustness, unveiled by the striking effectiveness of adversarial attacks. Adversarial training (AT) is often considered as a remedy to train more robust networks. In this paper, we empirically analyze a variety of adversarially trained models that achieve high robust accuracies when facing state-of-the-art attacks and we show that AT has an interesting side-effect: it leads to models that are significantly less overconfident with their decisions even on clean data than non-robust models. Further, our analysis of robust models shows that not only AT but also the model's building blocks (like activation functions and pooling) have a strong influence on the models' prediction confidences.
Ripple: Overview and Outlook
(2015)
Ripple is a payment system and a digital currency which evolved completely independently of Bitcoin. Although Ripple holds the second highest market cap after Bitcoin, there are surprisingly no studies which analyze the provisions of Ripple.
In this paper, we study the current deployment of the Ripple payment system. For that purpose, we overview the Ripple protocol and outline its security and privacy provisions in relation to the Bitcoin system. We also discuss the consensus protocol of Ripple. Contrary to the statement of the Ripple designers, we show that the current choice of parameters does not prevent the occurrence of forks in the system. To remedy this problem, we give a necessary and sufficient condition to prevent any fork in the system. Finally, we analyze the current usage patterns and trade dynamics in Ripple by extracting information from the Ripple global ledger. As far as we are aware, this is the first contribution which sheds light on the current deployment of the Ripple system.
In this work a set of nonlinear coupled COM equations at interacting frequencies is derived on the basis of nonlinear electro-elasticity. The formalism is presented with the aim of describing intermodulation distortion of third-order (IMD3) and triple beat. The resulting COM equations are translated to the P-matrix formalism, where care is taken to obtain the correct frequency dependence. The scheme depends on two frequency-independent constants for an effective third-order nonlinearity. One of these two constants is negligibly small in the systems considered here. The P-matrix approach is applied to single filters and duplexers on LiTaO 3 (YXl)/42° operating in different frequency ranges. Both IMD3 and triple beat show good agreement with measurement.
RFID- Frontend ISO 15693
(2008)
Introduction: Radiofrequency ablation allows successful treatment of most supraventricular reentrant and focal tachycardias and an increasing number of ventricular tachycardias. Different catheter tips are used. While AV nodal reentrant tachycardias require catheters with a tip of 4mm length, an 8 mm tip electrodes will be used for atrial flutter. A pulmonary vein isolation will be performed using 4 mm irrigated tip electrodes to achieve larger and deeper lesions. The need of a tubing set and pump for saline transfusion is a disadvantage of this technique. Gold tip electrodes can alternatively be used to produce increases in lesion size. Aim of this study was to compare RF ablation catheters of exactly the same geometry with either platin-iridum or gold tip.
Methods: Gold provides an almost four-fold thermal conductivity compared with platinum-iridium. The Cerablate G flutter (Osypka AG, Rheinfelden-Herten) is a newly designed radiofrequency ablation catheter with an 8 mm gold tip. Its power delivery was compared with the Cerablate flutter of same geometry but platin-iridium tip. Therefore, in-vitro RF ablations were performed using pork meat in a 0.9% saline solution at 37°C temperature. A pulsed volume flow was generated using a pump to simulate the blood flow. Temperature controlled ablations of 60 seconds using 45, 55 and 65°C and a maximum of 70W RF power were performed.
Results: Using the Osypka HAT300smart ablator, cumulative power of 167, 474 and 672W was delivered with gold tip against 121, 227 and 310 W with platin-iridium tip. By the Stockert SmartAblate G4 ablator, 202, 546 and 1075W was delivered with gold tip against 117, 246 and 394W with platin-iridium using 45, 55 and 65°C temperature.
Conclusion: During in-vitro investigations, the gold tip electrodes allowed a in power delivery increase of 117 up to 173%. Thus, gold tips can be used to increase lesion depth and diameter without cooling equipment.
The uncertain and time-variant nature of renewable energy results in the need to deal with peaks in the production of energy. One approach is to achieve a load shift and thereby help balancing the grid by using thermally Activated Building Systems (TABS). Control systems currently in place do not exploit the full potential of TABS. This paper reviews how Model Predictive Control can possibly reduce the fluctuations of the demand and supply of (renewable) energy as it enables the TABS to react to the dynamics of weather and its impact on the grid at any time.
Due to globalization and the resulting increase in competition on the market, products must be produced more and more cheaply, especially in series production, because buyers expect new variants or even completely new products in ever shorter cycles. Injection molding is the most important production process for manufacturing plastic components in large quantities. However, the conventional production of a mold is extremely time-consuming and costly, which creates a contradiction to the fast pace of the market. Additive tooling is an area of application of additive manufacturing, which in the field of injection molding is preferably used for the prototype production of mold inserts. This allows injection molding tools to be produced faster and more cheaply than through the subtractive manufacturing of metal tools. Material Jetting processes using polymers (MJT-UV/P), also called Polyjet Modeling (PJM), have a great potential for use in additive tooling. Due to the poorer mechanical and thermal properties compared to conventional mold insert materials, e.g. steel or aluminum, the previously used design principles cannot be applied. Accordingly, new design guidelines are necessary, which are developed in this paper. The necessary information is obtained with the help of a systematic literature research. The design guidelines are mapped in a uniform design guide, which is structured according to the design process of injection molds. The guidelines do not only refer to the constructive design of the injection mold or the polymer mold insert, but to the entire design process and describe the four phases of planning, conception, development and realization. Particular attention is paid to the special geometric designs of a polymer mold insert and the thermomechanical properties of the mold insert materials. As a result, design guidelines are available that are adapted to the special requirements of additive tooling of molds inserts made of plastics for injection molding.
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.
RETIS – Real-Time Sensitive Wireless Communication Solution for Industrial Control Applications
(2020)
Ultra-Reliable Low Latency Communications (URLLC) has been always a vital component of many industrial applications. The paper proposes a new wireless URLLC solution called RETIS, which is suitable for factory automation and fast process control applications, where low latency, low jitter, and high data exchange rates are mandatory. In the paper, we describe the communication protocol as well as the hardware structure of the network nodes for implementing the required functionality. Many techniques enabling fast, reliable wireless transmissions are used – short Transmission Time Interval (TTI), Time-Division Multiple Access (TDMA), MIMO, optional duplicated data transfer, Forward Error Correction (FEC), ACK mechanism. Preliminary tests show that reliable end-to-end latency down to 350 μs and packet exchange rate up to 4 kHz can be reached (using quadruple MIMO and standard IEEE 802.15.4 PHY at 250 kbit/s).
While most ultrafast time-resolved optical pump-probe experiments in magnetic materials reveal the spatially homogeneous magnetization dynamics of ferromagnetic resonance (FMR), here we explore the magneto-elastic generation of GHz-to-THz frequency spin waves (exchange magnons). Using analytical magnon oscillator equations, we apply time-domain and frequency-domain approaches to quantify the results of ultrafast time-resolved optical pump-probe experiments in free-standing ferromagnetic thin films. Simulations show excellent agreement with the experiment, provide acoustic and magnetic (Gilbert) damping constants and highlight the role of symmetry-based selection rules in phonon-magnon interactions. The analysis is extended to hybrid multilayer structures to explore the limits of resonant phonon-magnon interactions up to THz frequencies.
Today's network landscape consists of quite different network technologies, wide range of end-devices with large scale of capabilities and power, and immense quantity of information and data represented in different formats. Research on 3D imaging, virtual reality and holographic techniques will result in new user interfaces (UI) for mobile devices and will increase their diversity and variety. A lot of efforts are being done in order to establish open, scalable and seamless integration of various technologies and content presentation for different devices including mobile considering individual situation of the end user. This is very difficult because various kinds of devices used by different users or in different times/parallel by the same user which are not predictable and have to be recognized by the system in order to identify device capabilities. Not only the devices but also Content and User Interfaces are big issues because they could include different kinds of data format like text, image, audio, video, 3D Virtual Reality data and other upcoming formats. A very suitable and useful example of the use of such a system is mobile learning because of the large amount of varying devices with significantly different features and functionalities. This is true not only to support different learners, e.g. all learners within one learning community, but also to support the same learner using different equipment parallel and/or at different times. Those applications may be significantly enhanced by including virtual reality content presentation. Whatever the purposes are, it is impossible to develop and adapt content for all kind of devices including mobiles individually due to different capabilities of the devices, cost issues and author‘s requirement. A solution should be found to enable the automation of the content adaptation process.
With the increasing degree of interconnectivity in industrial factories, security becomes more and more the most important stepping-stone towards wide adoption of the Industrial Internet of Things (IIoT). This paper summarizes the most important aspects of one keynote of DESSERT2020 conference. It highlights the ongoing and open research activities on the different levels, from novel cryptographic algorithms over security protocol integration and testing to security architectures for the full lifetime of devices and systems. It includes an overview of the research activities at the authors' institute.
Sustainable design of equipment for process intensification requires a comprehensive and correct identification of relevant stakeholder requirements, design problems and tasks crucial for innovation success. Combining the principles of the Quality Function Deployment with the Importance-Satisfaction Analysis and Contradiction Analysis of requirements gives an opportunity to define a proper process innovation strategy more reliably and to develop an optimal process intensification technology with less secondary engineering and ecological problems.
In dieser Arbeit wurde eine USB-Schnittstelle für ein bestehendes Mikrocontroller System FHOP realisiert. Im aktuellen Stand funktioniert das Design zuverlässig in Low Speed Konfiguration. Im Full Speed gibt es noch einige Schwierigkeiten, denn die Kommunikation bricht nach einigen Paket-Transfers zusammen. Durch das Emulieren des Designs auf FPGA wurde die Funktion nachgewiesen. Die nächste Aufgabe wird sein, die Hardware zu optimieren, damit das USB-Modul auch im Full Speed zuverlässig funktioniert. Zusätzlich wird die Software auf der PC Seite optimiert, um höhere Übertragungsraten zu erzielen.
This paper explains the realization of a concept for research-oriented photonics education. Using the example of the integration of an actual PhD project, it is shown how students are familiarized with the topic of research and scientific work in the first semesters. Typical research activities are included as essential parts of the learning process. Research should be made visible and tangible for the students. The authors will present all aspects of the learning environment, their impressions and experiences with the implemented scenario, as well as first evaluation results of the students.
Environmental Monitoring is an attractive application field for Wireless Sensor Network (WSN). Water Level Monitoring helps to increase the efficiency of water distribution and management. In Pakistan, the world’s largest irrigation system covers 90.000 km of channels which needs to be monitored and managed on different levels. Especially the sensor systems for the small distribution channels need to be low energy and low cost. The distribution presents a technical solution for a communication system which is developed in a research project being co-funded by German Academic Exchange Service (DAAD). The communication module is based on IEEE-802.15.4 transceivers which are enhanced through Wake-On-Radio (WOR) to combine low-energy and real-time behavior. On higher layers, IPv6 (6LoWPAN) and corresponding routing protocols like Routing Protocol for Low power and Lossy Networks (RPL) can extend range of the network. The data are stored in a database and can be viewed online via a web interface. Of course, also automatic data analysis can be performed.
Our university carries out various research projects. Among others, the project Schluckspecht is an interdisciplinary work on different ultra-efficient car concepts for international contests. Besides the engineering work, one part of the project deals with real-time data visualization. In order to increase the efficiency of the vehicle, an online monitoring of the runtime parameters is necessary. The driving parameters of the vehicle are transmitted to a processing station via a wireless network connection. We plan to use an augmented reality (AR) application to visualize different data on top of the view of the real car. By utilizing a mobile Android or iOS device a user can interactively view various real-time and statistical data. The car and its components are meant to be augmented by various additional information, whereby that information should appear at the correct position of the components. An engine e.g. could show the current rpm and consumption values. A battery on the other hand could show the current charge level. The goal of this paper is to evaluate different possible approaches, their suitability and to expand our application to other projects at our university.
Short-term load forecasting (STLF) has been playing a key role in the electricity sector for several decades, due to the need for aligning energy generation with the demand and the financial risk connected with forecasting errors. Following the top-down approach, forecasts are calculated for aggregated load profiles, meaning the sum of singular loads from consumers belonging to a balancing group. Due to the emerging flexible loads, there is an increasing relevance for STLF of individual factories. These load profiles are typically more stochastic compared to aggregated ones, which imposes new requirements to forecasting methods and tools with a bottom-up approach. The increasing digitalization in industry with enhanced data availability as well as smart metering are enablers for improved load forecasts. There is a need for STLF tools processing live data with a high temporal resolution in the minute range. Furthermore, behin-the-meter (BTM) data from various sources like submetering and production planning data should be integrated in the models. In this case, STLF is becoming a big data problem so that machine learning (ML) methods are required. The research project “GaIN” investigates the improvement of the STLF quality of an energy utility using BTM data and innovative ML models. This paper describes the project scope, proposes a detailed definition for a benchmark and evaluates the readiness of existing STLF methods to fulfil the described requirements as a reviewing paper.
The review highlights that recent STLF investigations focus on ML methods. Especially hybrid models gain more and more importance. ML can outperform classical methods in terms of automation degree and forecasting accuracy. Nevertheless, the potential for improving forecasting accuracy by the use of ML models depends on the underlying data and the types of input variables. The described methods in the analyzed publications only partially fulfil the tool requirements for STLF on company level. There is still a need to develop suitable ML methods to integrate the expanded data base in order to improve load forecasts on company level.
Remote code attestation protocols are an essential building block to offer a reasonable system security for wireless embedded devices. In the work at hand we investigate in detail the trustability of a purely software-based remote code attestation based inference mechanism over the wireless when e.g. running the prominent protocol derivate SoftWare-based ATTestation for Embedded Devices (SWATT). Besides the disclosure of pitfalls of such a protocol class we also point out good parameter choices which allow at least a meaningful plausibility check with a balanced false positive and false negative ratio.
The paper focuses on a numerical model which describes the radial temperature evolution in an optical fiber during the heating and cooling process according to the SP1 approximation. Based on this model, experimental methods for temperature measurement with optical fibers and for splice process optimization can be developed.
With the need for automatic control based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear behaviour of the components but also certain unknown process dynamics like their internal control logic. At the Institute of Energy Systems Technology in Offenburg we have built a real-life microscale trigeneration plant and present in this paper a rational modelling procedure that satisfies the necessary characteristics for models to be applied in model predictive control for grid-reactive optimal scheduling of this complex energy system. These models are validated against experimental data and the efficacy of the methodology is discussed. Their application in the future for the optimal scheduling problem is also briefly motivated.
We will present the first example of a two-dimensional scanned TLC-plate, measured by use of a diode-array scanner. A spatial resolution of 250 µm was achieved on plate. The system provides real 2D fluorescence and absorption spectra in the wavelength-range from 190 to 1000 nm with a spectral resolution of greater than 1 nm. A mixture of 12 sulphonamides was separated by using a cyanopropyl-coated silica gel plate (Merck, 1.16464) with the solvent mix of methyl tert-butyl ether-methanol-dichloromethane-cyclohexane-NH3 (25%) (48:2:2:1:1, v/v) in the first and with a mixture of water-acetonitrile-dioxane-ethanol (8:2:1:1, v/v) in the second direction. Both developments were carried out over a distance of 70 mm. A separation number (spot capacity) of 259 was calculated. We discussed a new formula for its calculation in 2D-TLC separations. The drawback of this method is that measuring a 2D-TLC plate needs more than 3 h measurement time.
Quantitative Bestimmung von Clozapin im Serum mittels Dioden-Array Dünnschichtchromatographie
(2003)
The recent successes and wide spread application of compute intensive machine learning and data analytics methods have been boosting the usage of the Python programming language on HPC systems. While Python provides many advantages for the users, it has not been designed with a focus on multiuser environments or parallel programming - making it quite challenging to maintain stable and secure Python workflows on a HPC system. In this paper, we analyze the key problems induced by the usage of Python on HPC clusters and sketch appropriate workarounds for efficiently maintaining multi-user Python software environments, securing and restricting resources of Python jobs and containing Python processes, while focusing on Deep Learning applications running on GPU clusters.
This paper describes the authors' first experiments in creating an artificial dancer whose movements are generated through a combination of algorithmic and interactive techniques with machine learning. This approach is inspired by the time honoured practice of puppeteering. In puppeteering, an articulated but inanimate object seemingly comes to live through the combined effects of a human controlling select limbs of a puppet while the rest of the puppet's body moves according to gravity and mechanics. In the approach described here, the puppet is a machine-learning-based artificial character that has been trained on motion capture recordings of a human dancer. A single limb of this character is controlled either manually or algorithmically while the machine-learning system takes over the role of physics in controlling the remainder of the character's body. But rather than imitating physics, the machine-learning system generates body movements that are reminiscent of the particular style and technique of the dancer who was originally recorded for acquiring training data. More specifically, the machine-learning system operates by searching for body movements that are not only similar to the training material but that it also considers compatible with the externally controlled limb. As a result, the character playing the role of a puppet is no longer passively responding to the puppeteer but makes movement decisions on its own. This form of puppeteering establishes a form of dialogue between puppeteer and puppet in which both improvise together, and in which the puppet exhibits some of the creative idiosyncrasies of the original human dancer.
Generative machine learning models for creative purposes play an increasingly prominent role in the field of dance and technology. A particularly popular approach is the use of such models for generating synthetic motions. Such motions can either serve as source of ideation for choreographers or control an artificial dancer that acts as improvisation partner for human dancers. Several examples employ autoencoder-based deep-learning architectures that have been trained on motion capture recordings of human dancers. Synthetic motions are then generated by navigating the autoencoder's latent space. This paper proposes an alternative approach of using an autoencoder for creating synthetic motions. This approach controls the generation of synthetic motions on the level of the motion itself rather than its encoding. Two different methods are presented that follow this principle. Both methods are based on the interactive control of a single joint of an artificial dancer while the other joints remain under the control of the autoencoder. The first method combines the control of the orientation of a joint with iterative autoencoding. The second method combines the control of the target position of a joint with forward kinematics and the application of latent difference vectors. As illustrative example of an artistic application, this latter method is used for an artificial dancer that plays a digital instrument. The paper presents the implementation of these two methods and provides some preliminary results.