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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.
In the domain of printed electronics (PE), field-effect transistors (FETs) with an oxide semiconductor channel are very promising. In particular, the use of high gate-capacitance of the composite solid polymer electrolytes (CSPEs) as a gate-insulator ensures extremely low voltage requirements. Besides high gate capacitance, such CSPEs are proven to be easily printable, stable in air over wide temperature ranges, and possess high ion conductivity. These CSPEs can be sensitive to moisture, especially for high surface-to-volume ratio printed thin films. In this paper, we provide a comprehensive experimental study on the effect of humidity on CSPE-gated single transistors. At the circuit level, the performance of ring oscillators (ROs) has been compared for various humidity conditions. The experimental results of the electrolyte-gated FETs (EGFETs) demonstrate rather comparable currents between 30%-90% humidity levels. However, the shifted transistor parameters lead to a significant performance change of the RO frequency behavior. The study in this paper shows the need of an impermeable encapsulation for the CSPE-gated FETs to ensure identical performance at all humidity conditions.
Printed electrolyte-gated oxide electronics is an emerging electronic technology in the low voltage regime (≤1 V). Whereas in the past mainly dielectrics have been used for gating the transistors, many recent approaches employ the advantages of solution processable, solid polymer electrolytes, or ion gels that provide high gate capacitances produced by a Helmholtz double layer, allowing for low-voltage operation. Herein, with special focus on work performed at KIT recent advances in building electronic circuits based on indium oxide, n-type electrolyte-gated field-effect transistors (EGFETs) are reviewed. When integrated into ring oscillator circuits a digital performance ranging from 250 Hz at 1 V up to 1 kHz is achieved. Sequential circuits such as memory cells are also demonstrated. More complex circuits are feasible but remain challenging also because of the high variability of the printed devices. However, the device inherent variability can be even exploited in security circuits such as physically unclonable functions (PUFs), which output a reliable and unique, device specific, digital response signal. As an overall advantage of the technology all the presented circuits can operate at very low supply voltages (0.6 V), which is crucial for low-power printed electronics applications.
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.
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.
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.
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.
As part of the design education at Offenburg University, the teaching in technical documentation is continuously optimised. In this study, numerous mechanical engineering students, ages 19 to 29, are observed using the eye tracking technology and a video camera while performing various design exercises. The aim of the study is to enhance the students’ ability to read, understand and analyse complex engineering drawings. In one experiment, the students are asked to perform the “cube perspective test” after Stumpf and Fay to assess their ability for mental rotation as part of spatial visualization ability. Furthermore, the students are asked to prepare and give micro presentations on a topic related to their studies. Students have a maximum of 100 s time for these presentations. Thus, they can practise presenting important information in a short amount of time, show their rhetorical skills and demonstrate their acquisition of basic knowledge. During the presentation, the eye movement of a few selected students is recorded to analyse their information acquisition. In a further test, the students’ eye movements are analysed while reading an engineering drawing that consists of multiple views. All the spatial connections have to be included based on the different component views. Including these and their acquired knowledge, the students are asked to identify the correct representation of a component view. Furthermore the subjects are describing the function of an assembly, a parallel gripper and then they are to mentally disassemble the assembly to replace a damaged cylindrical pin. Simultaneously, they are filmed using a video camera to see which terms the students use for the individual technical terms. The evaluation of the eye movements shows that the increasing digitalisation of society and the use of electronic devices in everyday life lead to fast and only selective perceptual behaviour and that students feel insecure when dealing with technical drawings. The analysis of the videos shows a mostly non-technical and inaccurate manner of expression and a poor use of technical terms. The transferability of the achieved results to other technical tasks is part of further investigations.
A Novel Approach of High Dynamic Current Control of Interior Permanent Magnet Synchronous Machines
(2019)
Harmonic-afflicted effects of permanent magnet synchronous machines with high power density are hardly faced by traditional current PI controllers, due to limited controller bandwidth. As a consequence, currents and lastly torque ripples appear. In this paper, a new deadbeat current controller architecture has been presented, which is capable to encounter the effects of these harmonics. This new control algorithm, here named “Hybrid-Deadbeat-Controller”, combines the stability and the low steady-state errors offered by common PI regulators with the high dynamic offered by the deadbeat control. Therefore, a novel control algorithm is proposed, capable of either compensating the current harmonics in order to get smoother currents or to control a varying reference value to achieve a smoother torque. The information needed to calculate the optimal reference currents is based on an online parameter estimation feeding an optimization algorithm to achieve an optimal torque output and will be investigated in future research. In order to ensure the stability of the controller over the whole area of operation even under the influence of effects changing the system’s parameter, this work as well focusses on the robustness of the “hybrid” dead beat controller.
More than 200 years ago, the scientist Alexander von Humboldt noted in his travel diaries that "everything is interconnectedness", when he was fascinated by nature and the phenomena observed. The view of nature has become much more detailed through the knowledge of phenomena and natural processes, which led to a more precise view of nature shaped by Humboldt. Technological progress and the artificial intelligence of highly developed computer systems are upsetting this view and changing the established world view through a new, unprecedented interaction between man and machinery. Thus we need digital axioms and comprehensive rules and laws for such autonomous acting systems that determine human interaction between cybernetic systems and biological individuals. This digital humanism should encompass our relationship to nature, our handling of the complexity and diversity of nature and the technological influences on society in order to avoid technical colonialism through supercomputers.
Dissertation D. Dongol
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.
Sweaty has already participated four times in RoboCup soccer competitions (Adult Size) and came second three times. While 2016 Sweaty needed a lot of luck to be finalist, 2017 Sweaty was a serious adversary in the preliminary rounds. In 2018 Sweaty showed up in the final with some lack of experience and room for improvements, but not without any chance. This paper describes the intended improvements of the humanoid adult size robot Sweaty in order to qualify for the RoboCup 2019 adult size competition.
Deep generative models have recently achieved impressive results for many real-world applications, successfully generating high-resolution and diverse samples from complex datasets. Due to this improvement, fake digital contents have proliferated growing concern and spreading distrust in image content, leading to an urgent need for automated ways to detect these AI-generated fake images.
Despite the fact that many face editing algorithms seem to produce realistic human faces, upon closer examination, they do exhibit artifacts in certain domains which are often hidden to the naked eye. In this work, we present a simple way to detect such fake face images - so-called DeepFakes. Our method is based on a classical frequency domain analysis followed by basic classifier. Compared to previous systems, which need to be fed with large amounts of labeled data, our approach showed very good results using only a few annotated training samples and even achieved good accuracies in fully unsupervised scenarios. For the evaluation on high resolution face images, we combined several public datasets of real and fake faces into a new benchmark: Faces-HQ. Given such high-resolution images, our approach reaches a perfect classification accuracy of 100% when it is trained on as little as 20 annotated samples. In a second experiment, in the evaluation of the medium-resolution images of the CelebA dataset, our method achieves 100% accuracy supervised and 96% in an unsupervised setting. Finally, evaluating a low-resolution video sequences of the FaceForensics++ dataset, our method achieves 91% accuracy detecting manipulated videos.
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.
Recent studies have shown remarkable success in image-to-image translation for attribute transfer applications. However, most of existing approaches are based on deep learning and require an abundant amount of labeled data to produce good results, therefore limiting their applicability. In the same vein, recent advances in meta-learning have led to successful implementations with limited available data, allowing so-called few-shot learning.
In this paper, we address this limitation of supervised methods, by proposing a novel approach based on GANs. These are trained in a meta-training manner, which allows them to perform image-to-image translations using just a few labeled samples from a new target class. This work empirically demonstrates the potential of training a GAN for few shot image-to-image translation on hair color attribute synthesis tasks, opening the door to further research on generative transfer learning.
In this preliminary report, we present a simple but very effective technique to stabilize the training of CNN based GANs. Motivated by recently published methods using frequency decomposition of convolutions (e.g. Octave Convolutions), we propose a novel convolution scheme to stabilize the training and reduce the likelihood of a mode collapse. The basic idea of our approach is to split convolutional filters into additive high and low frequency parts, while shifting weight updates from low to high during the training. Intuitively, this method forces GANs to learn low frequency coarse image structures before descending into fine (high frequency) details. Our approach is orthogonal and complementary to existing stabilization methods and can simply plugged into any CNN based GAN architecture. First experiments on the CelebA dataset show the effectiveness of the proposed method.
Background: The application of high-frequency ablation is used for the treatment of tachycardia arrhythmias and is a respected method. Ablation with high frequency current leads to the targeted heat destruction of myocardial tissue at specific sites and thus prevents the pathological propagation of excitation through these structures.
Purpose: The aim of this study was to simulate heat propagation during RF ablation with modeled electrodes in different sizes and materials. The simulation was performed on atrioventricular node re-entry tachycardia (AVNRT), atrioventricular re-entry tachycardia (AVRT) and atrial flutter (AFL).
Methods: Using the modeling and simulation software CST, ablation catheters with 4 mm and 8 mm tip electrodes were modeled from gold and platinum for each. The designed catheters correspond to the manufacturer"s specifications of Medtronic, Biotronik and Osypka. The catheters were integrated into the Offenburg heart rhythm model to simulate and compare the heat propagation during an ablation application, which also takes into account the blood flow in the four heart chambers. A power of 5 W - 40 W was simulated for the 4 mm electrodes and a power of 50 W - 80 W for the 8 mm electrodes.
Results: During the simulated HF ablation application, the temperature at the ablation electrode was measured at different powers. This is 40.67°C at 5 W, 44.34°C at 10 W, 51.76°C at 20 W, 59.0°C at 30 W, and 66.33°C at 40 W. The measured temperature during 40 W application is 39.5°C at 0,5 mm depth in the myocardium and 37.5°C at 2 mm depth.
In the simulation, the 8 mm platinum electrode reached an ablation temperature of 72.85°C at its tip during an applied power of 60 W. In contrast, the 8 mm platinum electrode reached a depth of 5 mm at 39.5 C° and at a depth of 2 mm at 37.5 °C. In contrast, the 8 mm gold electrode reached a temperature of 64.66°C with the same performance. This is due to the thermal properties of gold, which has a better thermal conductivity than platinum.
Conclusions: CST offers the possibility to carry out a static and dynamic simulation of a heart model and the ablation electrodes integrated in it during an HF ablation. In variation with different electrode sizes and materials, therapy methods for the treatment of AVNRT, AVRT and AFL can be optimized
We present a planar chromatographic separation method for the compounds caffeine, artemisinin, and equol, separated on high-performance thin-layer chromatography (HPTLC) silica gel plates. As solvents for separation, methyl t-butyl ether and cyclohexane (1:1, V/V) have been used for equol, cyclohexane and ethyl acetate (7:3, V/V) for artemisinin, and ethyl acetate and acetone (7:3, V/V) for caffeine. After separation, the plate was scanned with a very specific time of flight-direct analysis in real time-mass spectrometry (TOF-DART-MS) system using the (M + 1)+ signals of equol, artemisinin, and caffeine. The (M + 1) peak of artemisinin at 283.13 m/z is clearly detectable, which is the proof that DART-MS is applicable for the quantitative determination of rather instable molecules. The planar set-up of DART source, HPTLC plate and detector inlet in a line showed higher sensitivities compared to desorption at an angle. The optimal detector voltage increases with the molar mass of the analyte, thus an individual determination of optimal detector voltage setting for the different analyte is recommended to achieve the best possible measurement conditions. In conclusion, DART-MS detection in combination with an HPTLC separation allows very specific quantification of all three compounds.
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.
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 (PE) circuits have several advantages over silicon counterparts for the applications where mechanical flexibility, extremely low-cost, large area, and custom fabrication are required. The custom (personalized) fabrication is a key feature of this technology, enabling customization per application, even in small quantities due to low-cost printing compared with lithography. However, the personalized and on-demand fabrication, the non-standard circuit design, and the limited number of printing layers with larger geometries compared with traditional silicon chip manufacturing open doors for new and unique reverse engineering (RE) schemes for this technology. In this paper, we present a robust RE methodology based on supervised machine learning, starting from image acquisition all the way to netlist extraction. The results show that the proposed RE methodology can reverse engineer the PE circuits with very limited manual effort and is robust against non-standard circuit design, customized layouts, and high variations resulting from the inherent properties of PE manufacturing processes.
Printed electronics can benefit from the deployment of electrolytesas gate insulators,which enables a high gate capacitance per unit area (1–10 μFcm−2) due to the formation of electrical double layers (EDLs). Consequently, electrolyte-gated field-effect transistors (EGFETs) attain high-charge carrier densities already in the subvoltage regime, allowing for low-voltage operation of circuits and systems. This article presents a systematic study of lumped terminal capacitances of printed electrolyte-gated transistors under various dc bias conditions. We perform voltage-dependent impedancemeasurements and separate extrinsic components from the lumped terminal capacitance.
The proposed Meyer-like capacitance model, which also accounts for the nonquasi-static (NQS) effect, agrees well with experimental data. Finally, to verify the model, we implement it in Verilog-A and simulate the transient response of an inverter and a ring oscillator circuit. Simulation results are in good agreement with the measurement data of fabricated devices.
Electrolyte-gated, printed field-effect transistors exhibit high charge carrier densities in the channel and thus high on-currents at low operating voltages, allowing for the low-power operation of such devices. This behavior is due to the high area-specific capacitance of the device, in which the electrolyte takes the role of the dielectric layer of classical architectures. In this paper, we investigate intrinsic double-layer capacitances of ink-jet printed electrolyte-gated inorganic field-effect transistors in both in-plane and top-gate architectures by means of voltage-dependent impedance spectroscopy. By comparison with deembedding structures, we separate the intrinsic properties of the double-layer capacitance at the transistor channel from parasitic effects and deduce accurate estimates for the double-layer capacitance based on an equivalent circuit fitting. Based on these results, we have performed simulations of the electrolyte cutoff frequency as a function of electrolyte and gate resistances, showing that the top-gate architecture has the potential to reach the kilohertz regime with proper optimization of materials and printing process. Our findings additionally enable accurate modeling of the frequency-dependent capacitance of electrolyte/ion gel-gated devices as required in the small-signal analysis in the circuit simulation.
Robots and automata are key elements of every vision and forecast of life in the near and distant future. However, robots and automata also have a long history, which reaches back into antiquity. Today most historians think that one of the key roles of robots and automata was to amaze or even terrify the audience: They were designed to express something mythical, magical, and not explainable. Moreover, the visions of robots and their envisioned fields of application reflect the different societies. Therefore, this short history of robotics and (especially) anthropomorphic automata aims to give an overview of several historical periods and their perspective on the topic. In a second step, this work aims to encourage readers to reflect on the recent discussion about fields of application as well as the role of robotics today and in the future.
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.
We present a novel approach that utilizes BLE packets sent from generic BLE capable radios to synthesize an FSK-(like) addressable wake-up packet. A wake-up receiver system was developed from off-the-shelf components to detect these packets. It makes use of two differential signal paths separated by passive band-pass filters. After the rectification of each channel a differential amplifier compares the signals and the resulting wake-up signal is evaluated by an AS3933 wake-up receiver IC. Overall, the combination of these techniques contributes to a BLE compatible wake-up system which is more robust than traditional OOK wake-up systems. Thus, increasing wake-up range, while still maintaining a low energy budget. The proof-of-concept setup achieved a sensitivity of -47.8 dBm at a power consumption of 18.5 uW during passive listening. The system has a latency of 31.8 ms with a symbol rate of 1437 Baud.
Tryptamines can occur naturally in plants, mushrooms, microbes, and amphibians. Synthetic tryptamines are sold as new psychoactive substances (NPS) because of their hallucinogenic effects. When it comes to NPS, metabolism studies are of crucial importance, due to the lack of pharmacological and toxicological data. Different approaches can be taken to study in vitro and in vivo metabolism of xenobiotica. The zygomycete fungus Cunninghamella elegans (C. elegans) can be used as a microbial model for the study of drug metabolism. The current study investigated the biotransformation of four naturally occurring and synthetic tryptamines [N,N‐Dimethyltryptamine (DMT), 4‐hydroxy‐N‐methyl‐N‐ethyltryptamine (4‐HO‐MET), N,N‐di allyl‐5‐methoxy tryptamine (5‐MeO‐DALT) and 5‐methoxy‐N‐methyl‐N‐isoporpoyltryptamine (5‐MeO‐MiPT)] in C. elegans after incubation for 72 hours. Metabolites were identified using liquid chromatography–high resolution–tandem mass spectrometry (LC–HR–MS/MS) with a quadrupole time‐of‐flight (QqTOF) instrument. Results were compared to already published data on these substances. C. elegans was capable of producing all major biotransformation steps: hydroxylation, N‐oxide formation, carboxylation, deamination, and demethylation. On average 63% of phase I metabolites found in the literature could also be detected in C. elegans. Additionally, metabolites specific for C. elegans were identified. Therefore, C. elegans is a suitable complementary model to other in vitro or in vivo methods to study the metabolism of naturally occurring or synthetic tryptamines.
Background: Transesophageal left atrial (LA) pacing and transesophageal LA ECG recording are semi-invasive techniques for diagnostic and therapy of supraventricular rhythm disturbance. Cardiac resynchronization therapy (CRT) with right atrial (RA) sensed biventricular pacing is an established therapy for heart failure patients with reduced left ventricular (LV) ejection fraction, sinus rhythm and interventricular electrical desynchronization.
Purpose: The aim of the study was to evaluate electromagnetic and voltage pacing fields of the combination of RA pacing, LA pacing and biventricular pacing in patients with long interatrial and interventricular electrical desynchronization.
Methods: The modelling and electromagnetic simulations of transesophageal LA pacing in combination with RA pacing and biventricular pacing would be staged and analyzed with the CST (Computer Simulation Technology) software. Different electrodes were modelled in order to simulate different types of bipolar pacing in the 3D-CAD Offenburg heart rhythm model: The bipolar Solid S (Biotronik) electrode where modelled for RA pacing and right ventricular (RV) pacing, Attain 4194 (Medtronic) for LV pacing and TO8 (Osypka) multipolar esophageal electrode with hemispheric electrodes for LA pacing.
Results: The pacemaker amplitudes for the electromagnetic pacing simulations were performed with 3 V for RA pacing, 1.5 V for RV pacing, 50 V for LA pacing and 3V for LV pacing with pacing impulse duration of 0.5 ms for RA, RV and LV pacing and 10 ms for LA pacing. The atrioventricular pacing delay after RA pacing was 140 ms. The different pacing modes AAI, VVI, DDD, DDD0V and DDD0D were evaluated for the analysis of the electric pacing field propagation of pacemaker, CRT and LA pacing. The pacing results were compared at minimum (LOW) and maximum (HIGH) parameter settings. While the LOW setting produced fewer tetrahedral and more inaccurate results, the HIGH setting produced many tetrahedral and therefore more accurate results.
Conclusions: The simulation of the combination of transesophageal LA pacing with RA sensed biventricular pacing is possible with the Offenburg heart rhythm model. The new temporary 4-chamber pacing method may be additional useful method in CRT non-responders with long interatrial electrical delay.
In recent times, the energy consumed by buildings facilities became considerable. Efficient local energy management is vital to deal with building power demand penalties. This operation becomes complex when a hybrid energy system is included in the power system. This study proposes new energy management between photovoltaic (PV) system, Battery Energy Storage System (BESS) and the power network in a building by controlling the PV/BESS inverter. The strategy is based on explicit model predictive control (MPC) to find an optimal power flow in the building for one-day ahead. The control algorithm is based on a simple power flow equation and weather forecast. Then, a cost function is formulated and optimised using genetic algorithms-based solver. The objective is reducing the imported energy from the grid preventing the saturation and emptiness of BESS. Including other targets to the control policy as energy price dynamic and BESS degradation, MPC can optimise dramatically the efficacy of the global building power system. The strategy is implemented and tested successfully using MATLAB/SimPowerSystems software, compared to classical hysteresis management, MPC has given 10% in energy cost economy and 25% improvement in BESS lifetime.
High temperature components in internal combustion engines and exhaust systems must withstand severe mechanical and thermal cyclic loads throughout their lifetime. The combination of thermal transients and mechanical load cycling results in a complex evolution of damage, leading to thermomechanical fatigue (TMF) of the material. Analytical tools are increasingly employed by designers and engineers for component durability assessment well before any hardware testing. The DTMF model for TMF life prediction, which assumes that micro-crack growth is the dominant damage mechanism, is capable of providing reliable predictions for a wide range of high-temperature components and materials in internal combustion engines. Thus far, the DTMF model has employed a local approach where surface stresses, strains, and temperatures are used to compute damage for estimating the number of cycles for a small initial defect or micro-crack to reach a critical length. In the presence of significant gradients of stresses, strains, and temperatures, the use of surface field values could lead to very conservative estimates of TMF life when compared with reported lives from hardware testing. As an approximation of gradient effects, a non-local approach of the DTMF model is applied. This approach considers through-thickness fields where the micro-crack growth law is integrated through the thickness considering these variable fields. With the help of software tools, this method is automated and applied to components with complex geometries and fields. It is shown, for the TMF life prediction of a turbocharger housing, that the gradient correction using the non-local approach leads to more realistic life predictions and can distinguish between surface cracks that may arrest or propagate through the thickness and lead to component failure.
Neuroprosthetics 2.0
(2019)
New employees are supposed to quickly understand their tasks, internal processes and familiarize with colleagues. This process is called “onboarding” and is still mainly realized by organizational methods from human resource management, such as introductory events or special employee sessions. Software tools and especially mobile applications are an innovative means to support provide onboarding processes in a modern, even remote, way. In this paper we analyze how the use of gamification can enhance onboarding processes. Firstly, we describe a mobile onboarding application specifically developed for the young, technically literate generations Y and Z, who are just about to start their career. Secondly, we report on a study with 98 students and young employees. We found that participants enjoyed the gamified application. They especially appreciated the feature “Team Bingo” which facilitates social integration and teambuilding. Based on the OCEAN personality model (“Big Five”), the personality traits agreeableness and openness revealed significant correlations with a preference for the gamified onboarding application.
The paper describes a systematic approach for a precise short-time cloud coverage prediction based on an optical system. We present a distinct pre-processing stage that uses a model based clear sky simulation to enhance the cloud segmentation in the images. The images are based on a sky imager system with fish-eye lens optic to cover a maximum area. After a calibration step, the image is rectified to enable linear prediction of cloud movement. In a subsequent step, the clear sky model is estimated on actual high dynamic range images and combined with a threshold based approach to segment clouds from sky. In the final stage, a multi hypothesis linear tracking framework estimates cloud movement, velocity and possible coverage of a given photovoltaic power station. We employ a Kalman filter framework that efficiently operates on the rectified images. The evaluation on real world data suggests high coverage prediction accuracy above 75%.
This paper presents an approach for implementing an automated hit detection and score calculation system for a steel dartboard using a standard webcam. First, the rectilinear field separations of the dartboard are described mathematically by means of line slopes and are than stored. These slopes serve as a basis for later score calculation. In addition, thrown darts have to be detected and the pixel at which the dart cuts the dartboard has to be determined. When this information is known, a comparison is made using the line slopes, allowing the field number of the hit to be detected. The decision for single, double or triple hit is made by evaluating the defined colors on the dartboard. All these functions are then packaged in a Matlab GUI.
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.
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.
Virtual reality in the hotel industry: assessing the acceptance of immersive hotel presentation
(2019)
In the hotel industry, it is crucial to reduce the inherent information asymmetry with regard to the goods offered. This asymmetry can be minimised through the use of smartphone-based virtual reality applications (SBVRs), which allow virtual simulation of real experiences and thus enable more efficient information retrieval. The aim of the study is to determine for the first time the user acceptance of these immersive hotel presentations for assessing the performance of a travel accommodation. For this purpose, the Technology Acceptance Model (TAM) was used to explain the acceptance behaviour for this new technology. A virtual reality application was specially developed, in which the participants could explore a hotel virtually. A total of 569 participants took part in the study. The structural equation model and the hypotheses were tested using a Partial Least Squares (PLS) analysis. The results illustrate that the immersive product experience leads to more efficient information gathering. The perceived usefulness significantly affects the attitude towards using the technology as well as the intention to use it. In contrast to the traditional TAM, the perceived ease of use of SBVRs has no effect on the perceived usefulness or attitude towards using the technology.
Purpose
The purpose of this study is to investigate the effects of telepresence while using a smartphone-based virtual reality system (SBVR) to explore a hotel virtually and to determine the influence of this immersive experience on the booking intention of the potential customer.
Design/methodology/approach
Within the scope of this study, a conceptual research model was developed which covered utilitarian and hedonic aspects of the user experience of SBVRs and showed their relevance for the booking intention. A virtual reality application was programmed especially for the study, in which the test persons were able to virtually explore a hotel complex. A total of 569 people participated in the study. A questionnaire was used for the data collection. The structural equation modelling and hypothesis verification were carried out using the partial least squares method.
Findings
The immersive feeling of telepresence increases the perceived enjoyment and usefulness of the potential customer. In addition, the user's curiosity is aroused by the telepresence, which also significantly increases the perceived enjoyment as well as the perceived usefulness. The hedonic and utilitarian value of the virtual hotel experience increases the probability that the customer will book the travel accommodation.
Research limitations/implications
The virtual reality application developed for the study is based on static panoramic images and does not contain audio-visual elements (e.g. sound, video, animation). Audio-visual elements might increase the degree of immersion and could therefore be investigated in future research.
Practical implications
The results of the study show that the SBVR is a suitable marketing tool to present hotels in an informative and entertaining way, and can thereby increase sales and profits.
Originality/value
For the first time, this study investigates the potential of SBVRs for the virtual product presentation of hotels and provides empirical evidence that the availability of this innovative form of presentation leads to a higher booking intention.
For e-commerce retailers it is crucial to present their products both informatively and attractively. Virtual reality (VR) systems represent a new marketing tool that supports customers in their decision-making process and offers an extraordinary product experience. Despite these advantages, the use of this technology for e-commerce retailers is also associated with risks, namely cybersickness. The aim of the study is to investigate the occurrence of cybersickness in the context of the customer’s perceived enjoyment and the perceived challenge of a VR product presentation. Based on a conceptual research framework, a laboratory study with 533 participants was conducted to determine the influence of these factors on the occurrence of cybersickness. The results demonstrate that the perceived challenge has a substantially stronger impact on the occurrence of cybersickness, which can only be partially reduced by perceived enjoyment. When realizing VR applications in general and VR product presentations in particular, e-commerce retailers should therefore first minimize possible challenges instead of focusing primarily on entertainment aspects of such applications.
Hot working tools are subjected to complex thermal and mechanical loads during service. Locally, the stresses can exceed the material’s yield strength in highly loaded areas. During production, this causes cyclic plastic deformation and thus thermomechanical fatigue, which can significantly shorten the lifetime of hot working tools. To sustain this high loads, the hot working tools are typically made of tempered martensitic hot work tool steels. While the annealing temperatures of the tool steels usually lie in the range of 400 to 600 °C, the steels may experience even higher temperatures during hot working, resulting in softening of the material due to changes in microstructure. Therefore, the temperature-dependent cyclic mechanical properties of the frequently used hot work tool steel 1.2367 (X38CrMoV5-3) after tempering are investigated in this work. To this end, hardness measurements are performed. Furthermore, the Institute of Forming Technology and Machines (IFUM) provides test results from cyclic tests at temperatures ranging from 20 °C (room temperature) to 650 °C. To describe the observed time- and temperature-dependent softening during tempering, a kinetic model for the evolution of the mean size of secondary carbides based on Ostwald ripening is developed. In addition, both mechanism-based and phenomenological relationships for the cyclic mechanical properties of the Ramberg- Osgood model depending on carbide size and temperature are proposed. The stress-strain hysteresis loops measured at different temperatures and after different heat treatments can be well described with the proposed kinetic and mechanical model. Furthermore, the model is suitable for integration in advanced mechanism-based lifetime models. However, since the Ramberg-Osgood model is not suitable for finite element implementation, a temperature-dependent incremental cyclic plasticity model is presented as well. Thus, softening due to particle coarsening can be applied in the finite element method (FEM). Therefore, a kinetic model is coupled with a cyclic plasticity model including kinematic hardening. The plasticity model is implemented via subroutines in the finite element program ABAQUS for implicit integration (subroutine called UMAT) and explicit integration (subroutine called VUMAT). The implemented model is used for the simulation of an exemplary hot working process to assess the effects of softening due to particle coarsening. It shows that the thermal softening at high temperatures, which occur over a long time at a mechanically highly loaded area, has a great influence. If this influence is not considered in tool design, an unexpected tool failure might occur bringing the production to a standstill.
Besides of conventional CAD systems, new, cloud-based CAD systems have also been available for some years. These CAD systems designed according to the principle of software as a service (SaaS) differ in some important features from the conventional CAD systems. Thus, these CAD systems are operated via a browser and it is not necessary to install the software on a computer. The CAD-data is stored in the cloud and not on a local computer or central server. This new approach should also facilitate the sharing and management of data. Finally, many of these new CAD systems are available as freeware for education purposes, so the universities can save license costs. This contribution examines newly developed, cloud-based CAD systems. In the context of a case study, the application of these new CAD systems are investigated in the training of engineers in design education. Thus, the students compare a conventional and a cloud-based CAD system as part of an exercise of designing and 3D modelling of a pinion shaft. Subsequently, the students manufacture a drawing with different views of the pinion shaft. This assessment evaluates different criteria such as user-friendliness, tutorial support and installation effort.
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 additive manufacturing processes have developed significantly in recent years. Currently, new generative processes are coming onto the market. Likewise, the number of available materials that can be processed using additive processes is steadily increasing. Therefore, an important task is to integrate these new processes and materials into the university education of engineers. Due to the rapid change and the constant development in the field of additive manufacturing, a pure transfer of knowledge is not expedient, because this obsolete very quickly. Rather, the students should be enabled to use their skills in such a way that they can always handle new technologies and materials independently and meaningfully.
In this paper, therefore, a new course is developed in which the students largely independently work with additive manufacturing processes. For this purpose, teams of four to five students from different technical programs are formed. The teams have the task of developing and manufacturing a product using additive processes. The goal is to create a powerful product by taking into account the optimization of costs and use of resources.
As an example, the development and additive manufacturing of an ornithopter (aircraft that flies by flapping its wings) will be presented in this contribution. The students have to analyze and optimize the mechanics and aerodynamics of the aircraft. In addition, the rules for production-oriented design must be determined and applied. Further more, they should assess the costs and material consumption during development and production.
This contribution shows how the students have achieved the different learning outcomes. In addition, it becomes clear how the students independently acquired and applied their knowledge in development, design and additive manufacturing. Also, it will be demonstrated how much time the students spent on learning the different technologies.
The development of new processes and materials for additive manufacturing is currently progressing rapidly. In order to use the advantages of additive manufacturing, however, product development and design must also be adapted to these new processes. Therefore it is suitable to use structural optimization. To achieve the best results in lightweight design, it is important to have an approach that reduces the volume in the unloaded regions and considers the restrictions and characteristics of the additive manufacturing process. In this contribution, a case study using a humanoid robot is presented. Thus, the pelvis module of a humanoid robot is optimized regarding its weight and stiffness. Furthermore, an integrated design is implemented in order to reduce the number of parts and the screw connections. The manufacturing uses a new aluminum-based material that has been specially developed for use in additive manufacturing and lightweight construction. For the additive manufacturing by means of the Selective Laser Melting (SLM) process, different restrictions and the assembly concepts of the humanoid robot have to be taken into account. These restrictions have to be considered in the setting of the individual parameters and target functions of the structural optimization. As a result, a framework is presented that shows the steps of the redesign and the optimization of the pelvis module. In order to achieve high accuracy with the product, the redesign of the pelvis module is demonstrated with regard to mechanical and thermal postprocessing. Finally, the redesigned part and the different assembly concepts are compared to analyze the economic and technical effects of the optimization.
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.
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.