Refine
Year of publication
- 2022 (106) (remove)
Document Type
- Conference Proceeding (106) (remove)
Conference Type
- Konferenzartikel (87)
- Konferenz-Abstract (13)
- Konferenz-Poster (3)
- Sonstiges (3)
Is part of the Bibliography
- yes (106)
Keywords
- injury (10)
- Machine Learning (5)
- biomechanics (5)
- running (5)
- ACL (4)
- Robustness (4)
- Radar (3)
- RoboCup (3)
- sport (3)
- 3D printing (2)
- Geophysik (2)
- Lightweight design (2)
- NB-IoT (2)
- Roboter (2)
- Robotics (2)
- Sustainabilty (2)
- TRIZ (2)
- UWB radars (2)
- catheter ablation (2)
- cryptography (2)
- cybersecurity (2)
- deep learning (2)
- gamification (2)
- imaging algorithms (2)
- loneliness (2)
- machine learning (2)
- medical imaging (2)
- microwave (2)
- overuse (2)
- scattering measurements (2)
- 3D Printed Force Sensor (1)
- 5G (1)
- 5G private networks (1)
- AIN Cantilever (1)
- Additive Manufacturing (1)
- Additive Tooling (1)
- Additive manufacturing (1)
- Adversarial Attacks (1)
- Adversarial Robustness (1)
- Agent based sensor (1)
- Aliasing (1)
- Angle of Arrival (1)
- Approximation (1)
- Artificial Intelligence (1)
- Augmented reality (1)
- Automotive Radar (1)
- Bauteilfestigkeit (1)
- Biologische Methanisierung (1)
- Blockchain (1)
- Business Intelligence (1)
- CNN (1)
- CNNs (1)
- COVID (1)
- Capacitive Liquid Level Sensor (1)
- Challenges in Action Recognition (1)
- Chemical engineering (1)
- Circular polarizing filter (1)
- Climate change (1)
- Clustering (1)
- Coal phase-out (1)
- Cobotik (1)
- Collaboration of Academia and Industry (1)
- Computer Vision (1)
- Conversational user experience (1)
- Data Mining (1)
- Deepfake (1)
- Demand side flexibility (1)
- Design Based Research (1)
- Design education (1)
- Design for fibre reinforced AM (1)
- Digitaler Zwilling (1)
- Digitalisierung (1)
- Digitalization (1)
- Dimensional Modelling (1)
- ETAP Simulations (1)
- Eco-Design (1)
- Eco-Innovation (1)
- Eco-inventive principles (1)
- Economics (1)
- Edge AI (1)
- Education (1)
- Effectiveness of fraud detection (1)
- Einkapselung (1)
- Einsamkeit (1)
- Elderly (1)
- Elderly care (1)
- Embedded AI (1)
- Embedded Constantan Wire (1)
- Embedded Systems (1)
- Emotion analysis (1)
- Encapsulation (1)
- Energiewirtschaft (1)
- Energy Management (1)
- Energy System Analysis (1)
- Energy policy (1)
- Energy systems modeling (1)
- European structural and investment funds (1)
- Eye Tracking (1)
- Feasibility study (1)
- Featherweight Go (1)
- Federal Republic of Germany (1)
- Fraud detection rates (1)
- Fused Layer Modeling (1)
- GPU Computing (1)
- Gamification (1)
- Gebäude (1)
- Gesundheit (1)
- HCI (1)
- Head-mounted displays (1)
- Health (1)
- Hemodynamic monitoring (1)
- Human-Robot Collaboration (1)
- Human-centered computing (1)
- Inertial (1)
- IoT Security (1)
- IoT security (1)
- Irregularities (1)
- Isolation (1)
- Jones calculus (1)
- KAM (1)
- Knowledge-based innovation (1)
- Künstliche Intelligenz (1)
- LPWAN (1)
- Large Grid-Connected PV Systems (1)
- Lernmanagementsystem (1)
- Load Flow Analysis (1)
- MEMS (1)
- MLOps (1)
- Machine learning (1)
- Makespan (1)
- Manufacturing industries (1)
- Maschinenbaustudium (1)
- Material Properties (1)
- Mean Square Error (1)
- Medizintechnik (1)
- Mensch-Maschine-Kommunikation (1)
- Model Calibration (1)
- Model Search (1)
- Module Manufacturing (1)
- Monte-Carlo method (1)
- Nachhaltigkeit (1)
- Nature-Inspired Innovation (1)
- Network Test (1)
- Netzintegration (1)
- Neural networks (1)
- Nonlinear waves (1)
- Nonlinearity (1)
- Nyquist-Shannon (1)
- Ontology (1)
- Optimization and control (1)
- PV Module (1)
- PV System (1)
- Parallelization (1)
- Peer to peer network (1)
- Pflanzenkohle (1)
- Photography (1)
- Photonics (1)
- Physical Unclonable Functions (1)
- Physikdidaktik (1)
- Polarization (1)
- Power Loss (1)
- Printing parameters (1)
- Process Design (1)
- Projektmanagement (1)
- Prothesen (1)
- Quarter-wave plate (1)
- Random call model (1)
- Reliability (1)
- Robotik (1)
- Russian Ukrainian war (1)
- SAP Analytics Cloud (1)
- SAP Data Warehouse Cloud (1)
- Sampling (1)
- Security (1)
- Selbsttest (1)
- Sensing Element (1)
- Separation Monitoring (1)
- Smart Energy Metering (1)
- Smart-UPS (1)
- Social Isolation (1)
- Social Media (1)
- Social Robots (1)
- Solar Radiation (1)
- Solitary waves (1)
- Soziale Roboter (1)
- Subspace Clustering (1)
- Surface acoustic wave (1)
- Sustainable (1)
- Sustainable product development (1)
- Thermomechanische Ermüdung (1)
- Time series data (1)
- Total Harmonic Distortion (1)
- Traceability (1)
- Training (1)
- University students (1)
- User-generated content (1)
- Verlassenheit (1)
- Vibrotactile Feedback (1)
- Virtual reality (1)
- Virtuelles Laboratorium (1)
- Visualization (1)
- Voice User Experience (1)
- Voice assistants (1)
- Voice user interfaces (1)
- Wedge waves (1)
- Weitsprung (1)
- Wärmepumpen (1)
- adversarial (1)
- algorithm-based data analysis (1)
- approximation (1)
- artificial dancer (1)
- asymmetry (1)
- atrial fibrillation (1)
- autoML (1)
- autoattack (1)
- benchmarking (1)
- biochar (1)
- biocompatibility test (1)
- biodegradable (1)
- biomaterials (1)
- biomechanical stimulation (1)
- curb (1)
- curricular concepts (1)
- dance and technology (1)
- data aggregation (1)
- dickkopf 3 (1)
- dictionary passing (1)
- digital games (1)
- digital twin (1)
- efficient training (1)
- energy harvesting (1)
- equivalent circuit model (1)
- ethical frameworks (1)
- eversion (1)
- flexible job shop (1)
- force (1)
- grey-box model (1)
- heat pump (1)
- height estimation (1)
- impedance cardiography (1)
- industrial IoT (1)
- industry (1)
- interactive media (1)
- learning scenarios (1)
- lid (1)
- lithium-ion battery (1)
- load profiles (1)
- local electricity markets (1)
- mahalanobis (1)
- maintenance scheduling (1)
- masked Stereolithography (1)
- media tyechnolog (1)
- mental health apps (1)
- message complexity (1)
- micronization (1)
- midsole (1)
- mobile app (1)
- model-predictive control (1)
- molybdenum (1)
- motion synthesis (1)
- multipath (1)
- mutual authentication (1)
- neural architecture search (1)
- neural ordinary differential equations (1)
- offensive security techniques (1)
- optics and photonics (1)
- optimization (1)
- parking (1)
- peer-to-peer energy trading (1)
- physical unclonable function (1)
- programming languages (1)
- pruning (1)
- pulmonary vein isolation (1)
- railway system (1)
- random call model (1)
- remanufacturing (1)
- remote model-based laboratory (1)
- research-oriented education (1)
- resource efficiency (1)
- risk factor (1)
- scheduling (1)
- semantics (1)
- sensor network (1)
- shoe (1)
- simulation (1)
- software defined radio (1)
- spectraldefense (1)
- synthetical profiles (1)
- transmit beamforming (1)
- vibration harvester (1)
- virtual lab (1)
- Ältere (1)
Institute
- Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) (42)
- Fakultät Maschinenbau und Verfahrenstechnik (M+V) (31)
- Fakultät Wirtschaft (W) (22)
- Fakultät Medien (M) (ab 22.04.2021) (13)
- INES - Institut für nachhaltige Energiesysteme (13)
- ivESK - Institut für verlässliche Embedded Systems und Kommunikationselektronik (11)
- IMLA - Institute for Machine Learning and Analytics (10)
- ACI - Affective and Cognitive Institute (3)
- IUAS - Institute for Unmanned Aerial Systems (3)
- POIM - Peter Osypka Institute of Medical Engineering (2)
Open Access
- Open Access (52)
- Closed (45)
- Bronze (29)
- Diamond (13)
- Closed Access (9)
- Grün (6)
- Hybrid (2)
- Gold (1)
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.
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.
The isolation measures adopted during the COVID-19 pandemic brought light to discussions related to the importance of meaningful social relationships as a basic need to human well-being. But even before the pandemic outbreak in the years 2020 and 2021, organizations and scholars were already drawing attention to the growing numbers related to lonely people in the world (World Economic Forum, 2019). Loneliness is an emotional distress caused by the lack of meaningful social connections, which affects people worldwide across all age groups, mainly young adults (Rook, 1984). The use of digital technologies has gained prominence as a means of alleviating the distress. As an example, studies have shown the benefits of using digital games both to stimulate social interactions (Steinfield, Ellison & Lampe, 2008) and to enhance the effects of digital interventions for mental health treatments, through gamification (Fleming et al., 2017). It is with these aspects in mind that the gamified app Noneliness was designed with the intention of reducing loneliness rates among young students at a German university. In addition to sharing the related works that supported the application development, this chapter also presents the aspects considered for the resource's design, its main functionalities, and the preliminary results related to the reduction of loneliness in the target audience.
Sweaty has already participated several times in RoboCup soccer competitions (Adult Size). Now the work is focused on stabilizing the gait. Moreover, we would like to overcome the constraints of a ZMP-algorithm that has a horizontal footplate as precondition for the simplification of the equations. In addition we would like to switch between impedance and position control with a fuzzy-like algorithm that might help to minimize jerks when Sweaty’s feet touch the ground.
Fallstudien sollen theoretische Lerninhalte zu Konzepten von Business Intelligence und Data Warehousing veranschaulichen und in einen praxisnahen Kontext bringen. Außerdem sollen Studierende umsetzungsorientierte Kompetenzen mit praxisrelevanten Systemen erwerben. Um diese Kompetenzen abzuprüfen und um die Auseinandersetzung mit Software und Konzepten zu vertiefen, haben sich Projekte als Ergänzung zu Fallstudien und Klausuren vielfach bewährt. Der Vortrag stellt dar, welche Möglichkeiten Dozierende im Rahmen der vom UCC zur Verfügung gestellten Plattform SAP Data Warehouse Cloud (SAP DWC) haben, um studentische Projekte zu Data Warehousing und Analytics durchzuführen. Der Autor berichtet über seine Erfahrung aus der Betreuung von über 30 Projekten mit SAP DWC aus verschiedenen Studiengängen seit 2020. Neben einer Übersicht über die von Studierenden gewählten Themen werden ausgewählte Projektergebnisse vorgestellt. Außerdem wird auf den Modus der Durchführung sowie existierende systemseitige Limitationen eingegangen. Für Dozierende, die mit ihren Studierenden eigene Projekte erfolgreich durchführen möchten, werden konkrete Hinweise und Maßnahmen dargestellt.
Significant improvements in module performance are possible via implementation of multi-wire electrodes. This is economically sound as long as the mechanical yield of the production is maintained. While flat ribbons have a relatively large contact area to exert forces onto the solar cell, wires with round cross section reduce this contact area considerably – in theory to an infinitively thin line. Therefore, the local stresses induced by the electrodes might increase to a point that mechanical production yields suffer unacceptably.
In this paper, we assess this issue by an analytical mechanical model as well as experiments with an encapsulant-free N.I.C.E. test setup. From these, we can derive estimations for the relationship between lay-up accuracy and expected breakage losses. This paves the way for cost-optimized choices of handling equipment in industrial N.I.C.E.-wire production lines.
Micronization of biochar (BC) may ease its application in agriculture. For example, fine biochar powders can be applied as suspensions via drip-irrigation systems or can be used to produce grnulated fertilizers. However, micronization may effect important physical biochar properties like the water holding capacity (WHC) or the porosity.
Weitsprung mit und ohne Unterschenkelprothese – gleiche Sportart, unterschiedliche Disziplinen
(2022)
The majority of anterior cruciate ligament (ACL) injuries in team sports are non-contact injuries, with cutting maneuvers identified as high-risk tasks. Young female handball players have been shown to be at greater risk for ACL injuries than males. One risk factor for ACL injuries is the magnitude of the knee abduction moment (KAM). Cutting technique variables on foot placement, overall approach and knee kinematics have been shown to influence the KAM. Since injury risk is believed to increase with increasing task complexity, the purpose of the study was to test the effect of task complexity on technique variables that influence the KAM in female handball players during fake-and-cut tasks.
Konstrukteure im Maschinenbau stehen häufig vor der Problemstellung, hochfest vorgespannte Schraubenverbindungen und einen durchgehenden Korrosionsschutz zu vereinen. Die einschlägigen Normen und Richtlinien bieten hierzu Stand heute keine ausreichende Hilfestellung. In diesem Beitrag werden an Versuchsblechen ermittelte Setzbeträge von maschinenbautypischen organischen Beschichtungssystemen unter Variation der Belastungshöhe und der Umgebungstemperatur präsentiert und mit in Bauteilversuchen gemessenen Vorspannkraftverlusten vergleichend bewertet.
To deal with frequent power outages in developing countries, people turn to solutions like uninterruptible power supply (UPS), which stores electric energy during normal operating hours and use it to meet energy needs during rolling blackout intervals. Locally produced UPSs of poorer power quality are widely accessible in the marketplaces, and they have a negative impact on power quality. The charging and discharging of the batteries in these UPSs generate significant amount of power losses in weak grid environments. The Smart-UPS is our proposed smart energy metering (SEM) solution for low voltage consumers that is provided by the distribution company. It does not require batteries, therefore there is no power loss or harmonic distortion due to corresponding charging and discharging. Through load flow and harmonic analysis of both traditional UPS and Smart-UPS systems on ETAP, this paper examines their impact on the harmonics and stability of the distribution grid. The simulation results demonstrate that Smart-UPS can assist fixing power quality issues in a developing country like Pakistan by providing cleaner energy than the battery-operated traditional UPSs.
VR-based implementation of interactive laboratory experiments in optics and photonics education
(2022)
Within the framework of a developed blended learning concept, a lot of experience has already been gained with a mixture of theoretical lectures and hands-on activities, combined with the advantages of modern digital media. Here, visualizations using videos, animations and augmented reality have proven to be effective tools to convey learning content in a sustainable way. In the next step, ideas and concepts were developed to implement hands-on laboratory experiments in a virtual environment. The main focus is on the realization of virtual experiments and environments that give the students a deep insight into selected subfields of optics and photonics.
DE\GLOBALIZE
(2022)
The artistic research cycle DE\GLOBALIZE is a media ecological search movement for the terrestrial. After examining matters of fact in India (2014-18), matters of concern in Egypt (2016-2019) and matters of care in the Upper Rhine (2018-22), the focus turns toward matters of violence in the Congo (2022). From matter to mater, mother-earth, the garden to exploitation. From science, water and climate to migration, oppression and extermination.
The long-term research is accessible through interactive web documentation. The platform serves as a continuous media-archaeological archive for a speculative ethnography. The relational structure of the videographic essay is enabling the forensic processing of single documents in the sense of the actor-network theory.
The subject of the presentation at IFM is a field trip to the Congo planned for March 2022, which will focus on the ambivalence of violence and care in collaboration with local artists. The field trip is based on the postcolonial reflection luderitzcargo by the author from 1996, in which a freight container was transformed into a translocal cinema in Namibia.
Through the journey to Congo, a group of media artists, a psychotherapist, a theater dramaturg, a filmmaker and a philosopher intend to explore the political, technological and psycho-geographic borders. By artistic interventions with locals, we want to interfere with relational string figures as part of the new Earth Politics. They are focusing on the displaced consumption of resources which are hard-fought and guarantee prosperity in the global north. The so-called ghost acreages are repressed and justified as part of a civilizational mission. With this trip, we want to confront our self-lies with the ones of our hosts. We want to confront ourselves with the foreign, the dark and the displaced ghosts within ourselves. In the presentation at the #IFM2022 Conference, the platform DE\GLOBALIZE will be problematized itself as an example of epistemic violence for the ethnographic memory of (Western) knowledge.
We are not the missionaries but the perplexed travellers. In our search movement, we are dealing with psychoanalysis, video, performance and trance. As disoriented white men we try the reversal of Black Skin and White Mask by Franz Fanon without blackfacing. We will not only care about the sensitivity of our skin but that of our g/hosts and the one of mother earth.
The sharp rise in electricity and oil prices due to the war in Ukraine has caused fluctuations in the results of the previous study about the economic analysis of electric buses. This paper shows how the increase in fuel prices affects the implementation of electric buses. This publication is constructing the Total Cost of Ownership (TCO) model in the small-mid-size city, Offenburg for the transition to electric buses. The future development of costs is estimated and a projection based on learning curves will be carried out. This study intends to introduce a new future prospect by presenting the latest data based on previous research. Through the new TCO result, the cost differences between the existing diesel bus and the electric bus are updated, and also the future prospects for the economic feasibility of the electric bus in a small and midsize city are presented.
The importance of machine learning has been increasing dramatically for years. From assistance systems to production optimisation to support the health sector, almost every area of daily life and industry comes into contact with machine learning. Besides all the benefits that ML brings, the lack of transparency and the difficulty in creating traceability pose major risks. While there are solutions that make the training of machine learning models more transparent, traceability is still a major challenge. Ensuring the identity of a model is another challenge. Unnoticed modification of a model is also a danger when using ML. One solution is to create an ML birth certificate and an ML family tree secured by blockchain technology. Important information about training and changes to the model through retraining can be stored in a blockchain and accessed by any user to create more security and traceability about an ML model.
Narrowband Internet-of-Things (NB-IoT) is a 3rd generation partnership project (3GPP) standardized cellular technology, adopted for 5G and optimized for massive Machine Type Communication (mMTC). Applications are anticipated around infrastructure monitoring, asset management, smart city and smart energy applications. In this paper, we evaluate the suitability of NB-IoT for private (campus) networks in industrial environments, including complex cloud-based applications around process automation. An end-to-end system has been developed, comprising of a sensor unit connected to a NB-IoT modem, a base station (gNodeB) equipped with a beamforming array and a local (private) network architecture comprising a sensor management system in the edge cloud. The experimental study includes field tests in realistic industrial environments with latency, reliability and coverage measurements. The results show a good suitability of NB-IoT for process automation with high scalability, low-power requirements and moderate latency requirements.
Due to the Covid-19 pandemic, the RoboCup WorldCup 2021 was held completely remotely. For this competition the Webots simulator (https://cyberbotics.com/) was used, so all teams needed to transfer their robot to the simulation. This paper describes our experiences during this process as well as a genetic learning approach to improve our walk engine to allow a more stable and faster movement in the simulation. Therefore we used a docker setup to scale easily. The resulting movement was one of the outstanding features that finally led to the championship title.
Synthesizing voice with the help of machine learning techniques has made rapid progress over the last years. Given the current increase in using conferencing tools for online teaching, we question just how easy (i.e. needed data, hardware, skill set) it would be to create a convincing voice fake. We analyse how much training data a participant (e.g. a student) would actually need to fake another participants voice (e.g. a professor). We provide an analysis of the existing state of the art in creating voice deep fakes and align the identified as well as our own optimization techniques in the context of two different voice data sets. A user study with more than 100 participants shows how difficult it is to identify real and fake voice (on avg. only 37% can recognize a professor’s fake voice). From a longer-term societal perspective such voice deep fakes may lead to a disbelief by default.
Additive manufacturing offers completely new production technologies thanks to the layered structure and the simultaneous processing of several materials. In order to exploit the potential of this new technology, it is already necessary in product development to consider the components no longer as monolithic blocks, but as a structure of many layers and individual elements (voxels). Therefore, this paper will examine the current state of voxel-based CAD systems and the subsequent 3D multi-material printing of the designed components. Different voxel-based CAD systems are used and analyzed for component design and a sample component is additively manufactured. The results show that simple components can be designed using voxel-based CAD systems. With the application of 3D multi-material printing, different materials and thus functions can be assigned to the designed voxel-based CAD-model.
This work focuses on the dependencies between typical design parameters of surface acoustic wave (SAW) resonators and the nonlinear emitted signals of second and third order. The parameters metalization ratio and pitch are used as examples, but the approach can be extended to other design parameters as well. It is shown, that the interaction between the nonlinear current generation and the linear admittance is defining the measured nonlinear power signals. It is also discussed, that changes in linear properties get more pronounced in nonlinear responses. Therefore, slight effects on linear parameters will have significant influence on the observed nonlinearity.
Im Projekt „BioMeth“ wurden zwei neuartige und bislang noch nicht für die biologische Methanisierung beschriebene Anlagenkonzepte entwickelt. Der neuentwickelte Invers-Membranreaktor (IMR) ermöglicht es, den Eintrag der erforderlichen Eduktgase Wasserstoff H2 und Kohlendioxid CO2 über kommerziell erhältliche Ultrafiltrationsmembranen und den Entgasungsbereich für den Methanaustrag räumlich zu trennen und zusätzlich einen hydraulischen Druck zur Steigerung des Wasserstoffeintrages zu nutzen. Ein Vorteil des Verfahrens ist, dass perspektivisch sowohl das CO2 aus klassischem Biogas als auch CO2-Quellen aus industriellen Abluftströmen, z. B. aus der Zementindustrie als Kohlenstoffquelle genutzt werden können.
Über die biologische Methanisierung hinaus eignet sich der Invers-Membranreaktor der Einschätzung der Autoren nach auch generell zur biotechnologischen Herstellung nicht-flüchtiger Wertstoffe ausgehend von gasförmigen Substraten. Im IMR kann z. B. ein Membranmodul zum Eintrag der Eduktgase verwendet werden, während ein weiteres Hohlmembranmodul zur zyklischen oder kontinuierlichen Abtrennung der wertstoffhaltigen Reaktionslösung unter Rückhaltung der Mikrobiologie im Sinne eines In-situ Product Recovery (ISPR)-Konzeptes genutzt werden kann.
Als herausragendes Ergebnis erwies sich während der Untersuchung des IMR, dass mit dem Konzept der Membranbegasung CH4-Konzentrationen von > 90 Vol.-% über eine einjährige Versuchsreihe kontinuierlich und mit flexiblem Gaseintrag erzielt werden konnten. Nach Inbetriebnahme war dabei außer der Zugabe von H2 und CO2 als Energie- bzw. C-Quelle lediglich eine zweimalige Ergänzung von Supplementen erforderlich. Die maximal erreichte membranflächen-spezifische Methanbildungsrate ohne Gaszirkulation lag bei 83 LN Methan pro m2 Membranfläche und Tag bei einer Produktgaszusammensetzung von 94 Vol.% Methan, 2 Vol.% H2, und 4 Vol.% CO2.
Das zweite noch in der frühen Testphase befindliche Verfahren nutzt Druckunterschiede in einer 10 m hohen gepackten Gegenstromblasensäule, die mit einem ebenfalls 10 m hohen separaten Entgasungs-Reaktor kombiniert wurde. Diese Verfahrenskonzept soll es ermöglichen, eine hohe Wasserstofflöslichkeit aufgrund des am Säulenfuß vorliegenden hydrostatischen Druckes zu erreichen und dabei gleichzeitig den Energiebedarf zu minimieren, die Investitionskosten zu reduzieren und optimale zeitliche und räumlichen Bedingungen für die mikrobiologische Umsetzung von H2 und CO2 zu schaffen. Erste Untersuchungen am Gegenstromblasensäulenreaktor zum Stoffübergang von Luft bestätigten eine gute Anreicherung der im Kreislauf geführten Flüssigkeit bereits bei verhältnismäßig niedrigen Gasleerrohrgeschwindigkeiten. In der zweiten Säule des Reaktoraufbaus sollte am Kopf aufgrund der Druckentspannung ein Ausgasen der im Vergleich zu Atmosphärendruck mit Gas übersättigten Flüssigkeit erfolgen. Das Ausgasen der Flüssigkeit konnte ebenfalls am Beispiel des Lufteintrages bestätigt werden.
Biodegradable metals have entered the implant market in recent years, but still do not show fully satisfactory degradation behaviour and mechanical properties. In contrast, it has been shown that pure molybdenum has an excellent combination of the required properties in this respect. We report on PM based screen printing of thin-walled molybdenum tubes as a processing step for medical stent manufacture. We also present data on the in vivo degradation and biocompatibility of molybdenum. The degradation of molybdenum wires implanted in the aorta of rats was evaluated by SEM and EDX. Biocompatibility was assessed by histological investigation of organs and analysis of molybdenum levels in tissue extracts and body fluids. Degradation rates of up to 13.5 μm/y were observed after 12 months. No histological changes or elevated molybdenum levels in organ tissues were observed. In summary, the results further underline that molybdenum is a highly promising biodegradable metallic material.
We consider large scale Peer-to-Peer Sensor Networks, which try to calculate and distribute the mean value of all sensor inputs. For this we design, simulate and evaluate distributed approximation algorithms which reduce the number of messages. The main difference of these algorithms is the underlying communication protocol which all use the random call model, where in discrete round model each node can call a random sensor node with uniform probability.The amount of data exchanged between sensor nodes and used in the calculation process affects the accuracy of the aggregation results leading to a trade-off situation. The key idea of our algorithms is to limit the sample size using the Finite Population Correction (FPC) method and collect the data using a distribution aggregation using Push-Pull Sampling, Pull Sampling, and Push Sampling communication protocols. It turns out that all methods show exponential improvement of Mean Squared Error (MSE) with the number of messages and rounds.
An import ban of Russian energy sources to Germany is currently being increasingly discussed. We want to support the discussion by showing a way how the electricity system in Germany can manage low energy imports in the short term and which measures are necessary to still meet the climate protection targets. In this paper, we examine the impact of a complete stop of Russian fossil fuel imports on the electricity sector in Germany, and how this will affect the climate coals of an earlier coal phase-out and climate neutrality by 2045.
Following a scenario-based analysis, the results gave a point of view on how much would be needed to completely rely on the scarce non-renewable energy resources in Germany. Huge amounts of investments would be needed in order to ensure a secure supply of electricity, in both generation energy sources (RES) and energy storage systems (ESS). The key findings are that a rapid expansion of renewables and storage technologies will significantly reduce the dependence of the German electricity system on energy imports. The huge integration of renewable energy does not entail any significant imports of the energy sources natural gas, hard coal, and mineral oil, even in the long term. The results showed that a ban on fossil fuel imports from Russia outlines huge opportunities to go beyond the German government's climate targets, where the 1.5-degree-target is achieved in the electricity system.
During the coronavirus crisis, labs had to be offered in digital form in mechanical engineering at short notice. For this purpose, digital twins of more complex test benches in the field of fluid energy machines were used in the mechanical engineering course, with which the students were able to interact remotely to obtain measurement data. The concept of the respective lab was revised with regard to its implementation as a remote laboratory. Fortunately, real-world labs were able to be fully replaced by remote labs. Student perceptions of remote labs were mostly positive. This paper explains the concept and design of the digital twins and the lab as well as the layout, procedure, and finally the results of the accompanying evaluation. However, the implementation of the digital twins to date does not yet include features that address the tactile experience of working in real-world labs.
The energy system is changing since some years in order to achieve the climate goals from the Paris Agreement which wants to prevent an increase of the global temperature above 2 °C [1]. Decarbonisation of the energy system has become for governments a big challenge and different strategies are being stablished. Germany has set greenhouse gas reduction limits for different years and keeps track of the improvement made yearly. The expansion of renewable energy systems (RES) together with decarbonisation technologies are a key factor to accomplish this objective.
This research is done to analyse the effect of introducing biochar, a decarbonisation technology, and study how it will affect the energy system. Pyrolysis is the process from which biochar is obtained and it is modelled in an open-source energy system model. A sensibility analysis is done in order to assess the effect of changing the biomass potential and the costs for pyrolysis.
The role of pyrolysis is analysed in the form of different future scenarios for the year 2045 to evaluate the impact when the CO2 emission limit is zero. All scenarios are compared to the reference scenario, where pyrolysis is not considered.
Results show that biochar can be used to compensate the emissions from other conventional power plant and achieve an energy transition with lower costs. Furthermore, it was also found that pyrolysis can also reduce the need of flexibility. This study also shows that the biomass potential and the pyrolysis costs can strongly affect the behaviour of pyrolysis in the energy system.
Eco-Feasibility Study and Application of Natural Inventive Principles in Chemical Engineering Design
(2022)
The early stages of the front-end process development are critical for the future success of projects involving new technologies. The application of eco-inventive principles identified in natural systems to the design of chemical processes and equipment allows one to find ways to mitigate or avoid secondary ecological problems such as, for example, higher consumption of raw materials or energy, generation of hazardous waste and pollution of the environment by toxic chemicals. However, before implementing a new technology in a real operational environment, it is necessary to completely investigate its undesirable ecological impact and to evaluate the future viability of this technology. Therefore, the research paper presents a study of ecological feasibility of an innovative process design utilising natural eco-inventive principles and analyses the correlations between applied inventive principles. Such eco-feasibility study can be considered as an important decision gate to determine whether the technology implementation should be moved forward. Furthermore, the study evaluates the practicability of natural inventive principles to the eco-friendly process design and is illustrated with an example of a sustainable technology for nickel extraction from pyrophyllite.
Rising societies’ demands require more sustainable products and technologies. Although numerous methods and tools have been developed in the last decades to support environmental-friendly product and process development, an interdisciplinary knowledge base of eco-innovative examples linked to the eco-innovative problems and solution principles is lacking. The paper proposes an ontology of examples for eco-friendly products and technologies assigned to the Inventive Principles (IPs) of the TRIZ methodology in accordance with the German TRIZ Standard VDI 4521. The examples of sustainable technologies and products build a database for sharing and reusing eco-innovation knowledge. The ontology acts as a tool for systematic solving of specific environmental problems in typical life cycle phases, for different environmental impact categories and engineering domains. Finally, the paper defines a future research agenda in the field of the TRIZ-based systematic eco-innovation.
Projektmanagement entwickelt sich kontinuierlich, auch in qualitativen Sprüngen und Zyklen. Planungsiterationen aus der Agilität und die coronabedingte Digitalisierung der Kommunikation sind nicht die einzigen aktuellen Entwicklungen. Nicht einmal die Wichtigsten. Es wird ein Überblick vermittelt, der nicht nur verstehen, sondern gestalten hilft.
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.
The aim of this study is to identify indicators at country level that could prove useful in improving the effectiveness of fraud detection in European Structural and Investment Funds. The chapter analyses EU funds, belonging to the period 2014–2020, from and the study suggests the convenience of tracking funds, especially in countries with higher GDP and higher transparency levels, and the lesser relevance of the number of irregularities for countries with higher GDP and those receiving larger funds. Fraud and fraud detection rates in individual funds vary significantly across states. Federal states, such as the Federal Republic of Germany, are comparatively successful in detecting fraud in EU funds.
Additive manufacturing with plastics enables the production of lightweight and resilient components with a high degree of design freedom. In the low-cost sector, Material Extrusion as Fused Layer Modeling (FLM) has so far been the leading method, as it offers simple 3D printers and a variety of inexpensive 3D materials. However, printing times for 6FLM are very long and dimensional accuracy and surface finish are rather poor. Recently, new processes from the field of Vat Polymerization have appeared on the market, such as masked Stereolithography (mSLA), which offer a significant improvement in component quality and build speed at equally favorable machine costs.
This paper therefore analyzes the technical and economic capabilities of the two competing additive processes. For this purpose, the achievable dimensional and surface qualities are determined using a test specimen which represents various important geometry elements. In addition, the machine and material costs are determined and compared with each other. Finally, the resulting environmental impact is determined in the form of the CO2 footprint. In order to optimize the strength of the printed components, material properties of the tensile specimens produced additively with mSLA are determined. The use of ABS-like resins will also be investigated to determine optimal processing settings.
Objective: Dickkopf 3 (DKK3) has been identified as a urinary biomarker. Values above 4000 pg/mg creatinine (Cr) were linked with a higher risk of short-term decline of kidney function (J Am Soc Nephrol 29: 2722–2733). However, as of today, there is little experience with DKK3 as a risk marker in everyday clinical practice. We used algorithm-based data analysis to evaluate the potential dependence of DKK3 in a cohort from a large single center in Germany.
Method: DKK3 was measured in all CKD patients in our center October 1 st 2018 till Dec. 31 2019, together with calculated GFR (eGFR) and urinary albumin/creatinine ratio (UACR). Kidney transplant patients were excluded. Until the end of follow-up Dec 31 st 2021, repeated measurements were performed for all parameters. Data analysis was performed using MD-Explorer (BioArtProducts, Rostock, Germany) and Python with multiple libraries. Linear regression models were applied in patients for DKK3, eGFR and UACR. Comparison of the models was performed with a twosided Kolmogorov-Smirnov test.
Results: 1206 DKK3 measurements were performed in 1103 patients (621 male, age 70yrs, eGFR 29,41 ml/min/1.73qm, UACR 800 mg/g). 134 patients died during follow-up. DKK3 mean was 2905 pg/mg Cr (max. 20000, 75 % percentile 3800). 121 pts had DKK3 > 4000. At the end of follow-up 7 % of patients with DKK3 < 4000 (initial eGFR 17.6) versus 39.6 % of patients with DDK3 > 4000 (initial eGFR 15.7) underwent dialysis. Compared to eGFR and UACR at baseline, DKK3 > 4000 performed best to predict eGFR loss over the next 12 months.
Conclusion: In this cohort of CKD patients, DKK3 > 4000 at baseline predicted the eGFR slope better than eGFR or UACR at baseline. DKK3 > 4000 reflected a higher risk of progression towards ESRD in patients with similar baseline eGFR levels.
The desire to connect more and more devices and to make them more intelligent and more reliable, is driving the needs for the Internet of Things more than ever. Such IoT edge systems require sound security measures against cyber-attacks, since they are interconnected, spatially distributed, and operational for an extended period of time. One of the most important requirements for the security in many industrial IoT applications is the authentication of the devices. In this paper, we present a mutual authentication protocol based on Physical Unclonable Functions, where challenge-response pairs are used for both device and server authentication. Moreover, a session key can be derived by the protocol in order to secure the communication channel. We show that our protocol is secure against machine learning, replay, man-in-the-middle, cloning, and physical attacks. Moreover, it is shown that the protocol benefits from a smaller computational, communication, storage, and hardware overhead, compared to similar works.
In recent years, Physical Unclonable Functions (PUFs) have gained significant attraction in the Internet of Things (IoT) for security applications such as cryptographic key generation and entity authentication. PUFs extract the uncontrollable production characteristics of physical devices to generate unique fingerprints for security applications. One common approach for designing PUFs is exploiting the intrinsic features of sensors and actuators such as MEMS elements, which typically exist in IoT devices. This work presents the Cantilever-PUF, a PUF based on a specific MEMS device – Aluminum Nitride (AlN) piezoelectric cantilever. We show the variations of electrical parameters of AlN cantilevers such as resonance frequency, electrical conductivity, and quality factor, as a result of uncontrollable manufacturing process variations. These variations, along with high thermal and chemical stability, and compatibility with silicon technology, makes AlN cantilever a decent candidate for PUF design. We present a cantilever design, which magnifies the effect of manufacturing process variations on electrical parameters. In order to verify our findings, the simulation results of the Monte Carlo method are provided. The results verify the eligibility of AlN cantilever to be used as a basic PUF device for security applications. We present an architecture, in which the designed Cantilever-PUF is used as a security anchor for PUF-enabled device authentication as well as communication encryption.
Spatially Distributed Wireless Networks (SDWN) are one of the basic technologies for the Internet of Things (IoT) and (Industrial) Internet of Things (IIoT) applications. These SDWN for many of these applications has strict requirements such as low cost, simple installation and operations, and high potential flexibility and mobility. Among the different Narrowband Wireless Wide Area Networking (NBWWAN) technologies, which are introduced to address these categories of wireless networking requirements, Narrowband Internet of Things (NB-IoT) is getting more traction due to attractive system parameters, energy-saving mode of operation with low data rates and bandwidth, and its applicability in 5G use cases. Since several technologies are available and because the underlying use cases come with various requirements, it is essential to perform a systematic comparative analysis of competing technologies to choose the right technology. It is also important to perform testing during different phases of the system development life cycle. This paper describes the systematic test environment for automated testing of radio communication and systematic measurements of the performance of NB-IoT.
The visual-inertial mapping and localization system maplab is analyzed by its implementation and subsequent evaluation. The mapping or localization is based on environmental feature detection. In addition to creating maps, there is also the option of fusion of several maps and thus mapping extensive areas and using them for further analysis of data. In this way, various software tools can be used to optimize the existing data sets.
Two sensor components are needed: an inertial measuring unit (IMU) and a monochrome camera, which are combined by a hardware rig and put into operation for the analysis of the visual-inertial system. System calibration is crucial for precision and system functioning and is based on nonlinear dynamic state estimation. This ensures the best possible estimate of the position of the environmental feature and the map. Maplab is particularly suitable for mapping rooms or small building complexes as the implementation and evaluation of the results in different application scenarios show. Special emphasis is laid on the evaluation of larger scenarios, in which is shown, that the system is struggling to keep up geometric consistencies and thus provide an accurate map.
In this paper, we study the runtime performance of symmetric cryptographic algorithms on an embedded ARM Cortex-M4 platform. Symmetric cryptographic algorithms can serve to protect the integrity and optionally, if supported by the algorithm, the confidentiality of data. A broad range of well-established algorithms exists, where the different algorithms typically have different properties and come with different computational complexity. On deeply embedded systems, the overhead imposed by cryptographic operations may be significant. We execute the algorithms AES-GCM, ChaCha20-Poly1305, HMAC-SHA256, KMAC, and SipHash on an STM32 embedded microcontroller and benchmark the execution times of the algorithms as a function of the input lengths.
In recent years, the topic of embedded machine learning has become very popular in AI research. With the help of various compression techniques such as pruning, quantization and others compression techniques, it became possible to run neural networks on embedded devices. These techniques have opened up a whole new application area for machine learning. They range from smart products such as voice assistants to smart sensors that are needed in robotics. Despite the achievements in embedded machine learning, efficient algorithms for training neural networks in constrained domains are still lacking. Training on embedded devices will open up further fields of applications. Efficient training algorithms would enable federated learning on embedded devices, in which the data remains where it was collected, or retraining of neural networks in different domains. In this paper, we summarize techniques that make training on embedded devices possible. We first describe the need and requirements for such algorithms. Then we examine existing techniques that address training in resource-constrained environments as well as techniques that are also suitable for training on embedded devices, such as incremental learning. At the end, we also discuss which problems and open questions still need to be solved in these areas.
The EREMI project is a 2-year project funded under the ERASMUS+ framework programme and its team has developed and will validate an advanced higher education program, including life-long learning, on the interdisciplinary topic of resource efficiency in manufacturing industries and the overall system optimization of low or not digitized physical infrastructure. All of these will be achieved by applying IoT technologies towards efficient industrial systems, and by utilizing a high-level educated human capital on these economically, politically, and technically crucial and highly relevant topics for the rapidly developing industries and economies of intensively economically and industrially transforming countries - Bulgaria, North Macedonia, and Romania. Efficiency will be attained by utilizing the experience and expertise of the involved German partner organisation.
The purpose of this study was to describe the effects of running speed and slope on metatarsophalangeal (MTP) joint kinematics. 22 male and female runners underwent 3D motion analysis on an instrumented treadmill at three different speeds (2.5 m/s, 3.0 m/s, 3.5 m/s). At each speed, participants ran at seven slope conditions (downhill: -15%, -10%, -5%, level, and uphill: +5%, +10%, +15%). We found a significant main effect (p < 0.001) of running speed and slope on peak MTP dorsiflexion and a running speed by slope interaction effect (p < 0.001) for peak MTP dorsiflexion velocity. These findings highlight the need to consider running intensity and environmental factors like running surface inclination when considering MTP joint mechanics and technological aids to support runners.
Effect of downhill running on biomechanical risk factors associated with iliotibial band syndrome
(2022)
The purpose of this study was to identify the influence of downhill running on biomechanical risk factors for iliotibial band syndrome. We conducted a 3D motion analysis of 22 females and males running on an instrumented treadmill at four different inclinations (0%, -5%, -10%, -15%) at a speed of 3.5 m/s. We found significant differences for biomechanical risk factors associated with iliotibial band syndrome. Peak knee flexion angle at initial ground contact (p < .001), peak knee adduction angle (p = .005), and iliotibial band strain (p < .001) systematically increased with increasing slope. Downhill running increases biomechanical risk factors for iliotibial band syndrome. Our results highlight the need to consider the individual running environment in assessing overuse injury risk in runners.