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Online grocery shopping (OGS) has significantly risen due to accelerated retail digitization and reshaped consumer shopping behaviors over the last years. Despite this trend, the German online grocery market lags behind its international counterparts. Notably, with almost half of the German population aged over 50 and the 55–64 age group emerging as the largest user segment in e-commerce, the over-50 demographic presents an attractive yet relatively overlooked audience for the expansion of the online grocery market. However, research on OGS behavior among German over-50s is scarce. This study addresses this gap, empirically investigating OGS adoption factors within this demographic through an online survey with 179 respondents. Our findings reveal that over a third of the over-50 demographic has embraced OGS, indicating a growing receptivity for OGS among the over-50s. Notably, home delivery, product variety, convenience, and curiosity emerged as primary drivers for OGS adoption among this demographic. Surprisingly, most adopters did not increase online grocery orders since 2020 and a not inconsiderable proportion have even stopped buying groceries online again. For potential OGS adopters, regional product availability turned out as a motivator, signaling substantial growth potential and providing online grocers with strategic opportunities to target this demographic. In light of our research, we offer practical suggestions to online grocery retailers, aiming to overcome barriers and capitalize on key drivers identified in our study for sustained growth in the over-50 market segment.
In a dynamic global landscape, the role of UK Export Finance (UKEF) and other export credit agencies (ECAs) has never been more important. Access to finance is critical for exporters as it enables them to invest in production, expand operations, manage cash flow and mitigate trade risks. However, businesses face challenges in securing export finance and trade credit insurance as geopolitical and trade megatrends lead to increased political, market and credit risks. Drawing on qualitative data from 35 semi-structured interviews and expert discussions and based on the Futures Triangle analytical framework, this white paper analyses the geopolitical and trade megatrends that UKEF and other ECAs will face in the coming years. It presents novel findings about the implications for ECA mandates, strategies, products and operations: The evolution of mandates towards a “growth promoter”, the need to further scale up operations, the use of big data and artificial intelligence for risk analysis and forecasting, and the need to balance multiple and conflicting priorities, including export growth, support for small and medium-sized exporters, inclusive trade, climate action, and positive impact in developing markets.
In a randomized controlled cross-over study ten male runners (26.7 ± 4.9 years; recent 5-km time: 18:37 ± 1:07 min:s) performed an incremental treadmill test (ITT) and a 3-km time trial (3-km TT) on a treadmill while wearing either carbon fiber insoles with downwards curvature or insoles made of butyl rubber (control condition) in light road racing shoes (Saucony Fastwitch 9). Oxygen uptake, respiratory exchange ratio, heart rate, blood lactate concentration, stride frequency, stride length and time to exhaustion were assessed during ITT. After ITT, all runners rated their perceived exertion, perceived shoe comfort and perceived shoe performance. Running time, heart rate, blood lactate levels, stride frequency and stride length were recorded during, and shoe comfort and shoe performance after, the 3-km TT. All parameters obtained during or after the ITT did not differ between the two conditions [range: p = 0.188 to 0.948 (alpha value: 0.05); Cohen's d = 0.021 to 0.479] despite the rating of shoe comfort showing better scores for the control insoles (p = 0.001; d = −1.646). All parameters during and after the 3-km TT showed no differences (p = 0.200 to 1.000; d = 0.000 to 0.501) between both conditions except for shoe comfort showing better scores for control insoles (p = 0.017; d = −0.919). Running with carbon fiber insoles with downwards curvature did not change running performance or any submaximal or maximal physiological or biomechanical parameter and perceived exertion compared to control condition. Shoe comfort is impaired while running with carbon fiber insoles. Wearing carbon fiber insoles with downwards curvature during treadmill running is not beneficial when compared to running with control insoles.
Garbage in, Garbage out: How does ambiguity in data affect state-of-the-art pedestrian detection?
(2024)
This thesis investigates the critical role of data quality in computer vision, particularly in the realm of pedestrian detection. The proliferation of deep learning methods has emphasised the importance of large datasets for model training, while the quality of these datasets is equally crucial. Ambiguity in annotations, arising from factors like mislabelling, inaccurate bounding box geometry and annotator disagreements, poses significant challenges to the reliability and robustness of the pedestrian detection models and their evaluation. This work aims to explore the effects of ambiguous data on model performance with a focus on identifying and separating ambiguous instances, employing an ambiguity measure utilizing annotator estimations of object visibility and identity. Through accurate experimentation and analysis, trade-offs between data cleanliness and representativeness, noise removal and retention of valuable data emerged, elucidating their impact on performance metrics like the log average miss-rate, recall and precision. Furthermore, a strong correlation between ambiguity and occlusion was discovered with higher ambiguity corresponding to greater occlusion prevalence. The EuroCity Persons dataset served as the primary dataset, revealing a significant proportion of ambiguous instances with approximately 8.6% ambiguity in the training dataset and 7.3% in the validation set. Results demonstrated that removing ambiguous data improves the log average miss-rate, particularly by reducing the false positive detections. Augmentation of the training data with samples from neighbouring classes enhanced the recall but diminished precision. Error correction of wrong false positives and false negatives significantly impacts model evaluation results, as evidenced by shifts in the ECP leaderboard rankings. By systematically addressing ambiguity, this thesis lays the foundation for enhancing the reliability of computer vision systems in real-world applications, motivating the prioritisation of developing robust strategies to identify, quantify and address ambiguity.
Die vorliegende Arbeit beschäftigt sich mit der Nutzung von Reinforcement Learning in der Informationsbeschaffungs-Phase eines Penetration Tests. Es werden Kernprobleme in den bisherigen Ansätzen anderer das Thema betreffender wissenschaftlicher Arbeiten analysiert und praktische Lösungsansätze für diese bisherigen Hindernisse vorgestellt und implementiert. Die Arbeit zeigt damit eine beispielhafte Implementierung eines Reinforcement Learning Agenten zur Automatisierung der Informationsbeschaffungs-Phase eines Penetration Tests und stellt Lösungen für existierende Probleme in diesem Bereich dar.
Eingebettet wird diese wissenschaftliche Arbeit in die Anforderungen der Herrenknecht AG hinsichtlich der Absicherung des Tunnelbohrmaschinen-Netzwerks. Dabei werden praktische Ergebnisse des eigen entwickelten Reinforcement Learning Modells im Tunnelbohrmaschinen-Test-Netzwerk der Herrenknecht AG vorgestellt.
The last decades have seen the evolution of industrial production into more sophisticated processes. The development of specialized, high-end machines has increased the importance of predictive maintenance of mechanical systems to produce high-quality goods and avoid machine breakdowns. Predictive maintenance has two main objectives: to classify the current status of a machine component and to predict the maintenance interval by estimating its remaining useful life (RUL). Nowadays, both objectives are covered by machine learning and deep learning approaches and require large training datasets that are often not available. One possible solution may be transfer learning, where the knowledge of a larger dataset is transferred to a smaller one. This thesis is primarily concerned with transfer learning for predictive maintenance for fault classification and RUL estimation. The first part presents the state-of-the-art machine learning techniques with a focus on techniques applicable to predictive maintenance tasks (Chapter 2). This is followed by a presentation of the machine tool background and current research that applies the previously explained machine learning techniques to predictive maintenance tasks (Chapter 3). One novelty of this thesis is that it introduces a new intermediate domain that represents data by focusing on the relevant information to allow the data to be used on different domains without losing relevant information (Chapter 4). The proposed solution is optimized for rotating elements. Therefore, the presented intermediate domain creates different layers by focusing on the fault frequencies of the rotating elements. Another novelty of this thesis is its semi and unsupervised transfer learning-based fault classification approach for different component types under different process conditions (Chapter 5). It is based on the intermediate domain utilized by a convolutional neural network (CNN). In addition, a novel unsupervised transfer learning loss function is presented based on the maximum mean discrepancy (MMD), one of the state-of-the-art algorithms. It extends the MMD by considering the intermediate domain layers; therefore, it is called layered maximum mean discrepancy (LMMD). Another novelty is an RUL estimation transfer learning approach for different component types based on the data of accelerometers with low sampling rates (Chapter 6). It applies the feature extraction concepts of the classification approach: the presented intermediate domain and the convolutional layers. The features are then used as input for a long short-term memory (LSTM) network. The transfer learning is based on fixed feature extraction, where the trained convolutional layers are taken over. Only the LSTM network has to be trained again. The intermediate domain supports this transfer learning type, as it should be similar for different component types. In addition, it enables the practical usage of accelerometers with low sampling rates during transfer learning, which is an absolute novelty. All presented novelties are validated in detailed case studies using the example of bearings (Chapter 7). In doing so, their superiority over state-of-the-art approaches is demonstrated.
With the expansion of IoT devices in many aspects of our life, the security of such systems has become an important challenge. Unlike conventional computer systems, any IoT security solution should consider the constraints of these systems such as computational capability, memory, connectivity, and power consumption limitations. Physical Unclonable Functions (PUFs) with their special characteristics were introduced to satisfy the security needs while respecting the mentioned constraints. They exploit the uncontrollable and reproducible variations of the underlying component for security applications such as identification, authentication, and communication security. Since IoT devices are typically low cost, it is important to reuse existing elements in their hardware (for instance sensors, ADCs, etc.) instead of adding extra costs for the PUF hardware. Micro-electromechanical system (MEMS) devices are widely used in IoT systems as sensors and actuators. In this thesis, a comprehensive study of the potential application of MEMS devices as PUF primitives is provided. MEMS PUF leverages the uncontrollable variations in the parameters of MEMS elements to derive secure keys for cryptographic applications. Experimental and simulation results show that our proposed MEMS PUFs are capable of generating enough entropy for a complex key generation, while their responses show low fluctuations in different environmental conditions.
Keeping in mind that the PUF responses are prone to change in the presence of noise and environmental variations, it is critical to derive reliable keys from the PUF and to use the maximum entropy at the same time. In the second part of this thesis, we elaborate on different key generation schemes and their advantages and drawbacks. We propose the PUF output positioning (POP) and integer linear programming (ILP) methods, which are novel methods for grouping the PUF outputs in order to maximize the extracted entropy. To implement these methods, the key enrollment and key generation algorithms are presented. The proposed methods are then evaluated by applying on the responses of the MEMS PUF, where it can be practically shown that the proposed method outperforms other existing PUF key generation methods.
The final part of this thesis is dedicated to the application of the MEMS PUF as a security solution for IoT systems. We select the mutual authentication of IoT devices and their backend system, and propose two lightweight authentication protocols based on MEMS PUFs. The presented protocols undergo a comprehensive security analysis to show their eligibility to be used in IoT systems. As the result, the output of this thesis is a lightweight security solution based on MEMS PUFs, which introduces a very low overhead on the cost of the hardware.
This paper provides a comprehensive overview of approaches to the determination of isocontours and isosurfaces from given data sets. Different algorithms are reported in the literature for this purpose, which originate from various application areas, such as computer graphics or medical imaging procedures. In all these applications, the challenge is to extract surfaces with a specific isovalue from a given characteristic, so called isosurfaces. These different application areas have given rise to solution approaches that all solve the problem of isocontouring in their own way. Based on the literature, the following four dominant methods can be identified: the marching cubes algorithms, the tessellation-based algorithms, the surface nets algorithms and the ray tracing algorithms. With regard to their application, it can be seen that the methods are mainly used in the fields of medical imaging, computer graphics and the visualization of simulation results. In our work, we provide a broad and compact overview of the common methods that are currently used in terms of isocontouring with respect to certain criteria and their individual limitations. In this context, we discuss the individual methods and identify possible future research directions in the field of isocontouring.
Background: Assistive Robotic Arms are designed to assist physically disabled people with daily activities. Existing joysticks and head controls are not applicable for severely disabled people such as people with Locked-in Syndrome. Therefore, eye tracking control is part of ongoing research. The related literature spans many disciplines, creating a heterogeneous field that makes it difficult to gain an overview.
Objectives: This work focuses on ARAs that are controlled by gaze and eye movements. By answering the research questions, this paper provides details on the design of the systems, a comparison of input modalities, methods for measuring the performance of these controls, and an outlook on research areas that gained interest in recent years.
Methods: This review was conducted as outlined in the PRISMA 2020 Statement. After identifying a wide range of approaches in use the authors decided to use the PRISMA-ScR extension for a scoping review to present the results. The identification process was carried out by screening three databases. After the screening process, a snowball search was conducted.
Results: 39 articles and 6 reviews were included in this article. Characteristics related to the system and study design were extracted and presented divided into three groups based on the use of eye tracking.
Conclusion: This paper aims to provide an overview for researchers new to the field by offering insight into eye tracking based robot controllers. We have identified open questions that need to be answered in order to provide people with severe motor function loss with systems that are highly useable and accessible.
Socially assistive robots (SARs) are becoming more prevalent in everyday life, emphasizing the need to make them socially acceptable and aligned with users' expectations. Robots' appearance impacts users' behaviors and attitudes towards them. Therefore, product designers choose visual qualities to give the robot a character and to imply its functionality and personality. In this work, we sought to investigate the effect of cultural differences on Israeli and German designers' perceptions of SARs' roles and appearance in four different contexts: a service robot for an assisted living/retirement residence facility, a medical assistant robot for a hospital environment, a COVID-19 officer robot, and a personal assistant robot for domestic use. The key insight is that although Israeli and German designers share similar perceptions of visual qualities for most of the robotics roles, we found differences in the perception of the COVID-19 officer robot's role and, by that, its most suitable visual design. This work indicates that context and culture play a role in users' perceptions and expectations; therefore, they should be taken into account when designing new SARs for diverse contexts.
Der Online-Handel verzeichnet seit Jahren ein stetiges Wachstum. Durch die COVID-19-Pandemie kaufen nun auch Nutzende, die zuvor physische Kanäle bevorzugten, vermehrt online ein. Der Anbietererfolg hängt dabei wesentlich von der Kenntnis über die Kund*innen ab. Allerdings dominieren einige große Anbieter den Markt, während kleinere Online-Shops Schwierigkeiten haben, ihre Angebote zu personalisieren. Eine Lösung bietet der Ansatz selbstbestimmter Identitäten. Dieser ermöglicht Kund*innen, ihre eigenen Shoppingdaten zu kontrollieren und sie selektiv mit Online-Shops zu teilen. Dadurch können individuelle Wünsche und Anforderungen der Kund*innen in Online-Shops berücksichtigt und ein personalisiertes Angebot sowie eine gute Nutzungserfahrung geboten werden. Trotz des großen Potenzials selbstbestimmter Identitäten ist der Ansatz in Deutschland kaum verbreitet. Dieser Beitrag beleuchtet den Einsatz selbstbestimmter Identitäten im Online-Handel. Mithilfe eines menschenzentrierten Gestaltungsprozesses wurden Personas und Ist-Szenarien erstellt, sowie daraus resultierend Anforderungen erhoben und Potenziale identifiziert. Auf Basis dessen konnte ein Daten- und Architekturmodell zur Integration von selbstbestimmten Identitäten im Online-Handel entwickelt werden.
This report examines exporters’ challenges and possible solutions for public intervention to promote foreign trade. Based on fieldwork conducted in Georgia, we explore which policy approaches can help to stimulate Georgian exports further. Our outcomes show that exporters face substantial barriers such as navigating complex trade regulations, lack of knowledge about target markets, trade finance gaps, as well as new export promotion programs (EPPs) in competitor countries. Other upper-middle-income countries can learn from our results that exporters can significantly benefit from a comprehensive export promotion strategy combined with an ecosystem-based “team” approach. EPPs related to awareness and capacity building in Georgia should be part of this strategy, focusing on challenges such as a lack of knowledge about trade practices and international business skills. Other EPPs must help to mitigate related market failures, as information gathering is costly, and firms have no incentive to share this information with competitors. Furthermore, targeted marketing support and customer matchmaking can answer Georgian exporters’ challenges, such as lack of market access and low sector visibility. Our results also show that public intervention through financial support and risk mitigation is essential for firms with an international orientation. The high-quality, rich outcomes provide significant value for other upper-middle-income countries by exploring the example of Georgia’s contemporary circumstances in an in-depth manner based on extensive interviews and document analysis. Limitations include that our work primarily relies on qualitative data and further research could involve a quantitative study with a diverse range of sectors.
"Ad fontes!"
Francesco Petrarca (1301–1374)
In the beginning, there was an idea: the reconstruction of the first "Iron Hand" of the Franconian imperial knight Götz von Berlichingen (1480–1562). We found that with this historical prosthesis, simple actions for daily use, such as holding a wine glass, a mobile phone, a bicycle handlebar grip, a horse’s reins, or some grapes, are possible without effort. Controlling this passive artificial hand, however, is based on the help of a healthy second hand.
In 2015, Google engineer Alexander Mordvintsev presented DeepDream as technique to visualise the feature analysis capabilities of deep neural networks that have been trained on image classification tasks. For a brief moment, this technique enjoyed some popularity among scientists, artists, and the general public because of its capability to create seemingly hallucinatory synthetic images. But soon after, research moved on to generative models capable of producing more diverse and more realistic synthetic images. At the same time, the means of interaction with these models have shifted away from a direct manipulation of algorithmic properties towards a predominance of high level controls that obscure the model's internal working. In this paper, we present research that returns to DeepDream to assess its suit-ability as method for sound synthesis. We consider this research to be necessary for two reasons: it tackles a perceived lack of research on musical applications of DeepDream, and it addresses DeepDream's potential to combine data driven and algorithmic approaches. Our research includes a study of how the model architecture, choice of audio data-sets, and method of audio processing influence the acoustic characteristics of the synthesised sounds. We also look into the potential application of DeepDream in a live-performance setting. For this reason, the study limits itself to models consisting of small neural networks that process time-domain representations of audio. These models are resource-friendly enough to operate in real time. We hope that the results obtained so far highlight the attractiveness of Deep-Dream for musical approaches that combine algorithmic investigation with curiosity driven and open ended exploration.
This paper describes the authors' first experiments in creating an artificial dancer whose movements are generated through a combination of algorithmic and interactive techniques with machine learning. This approach is inspired by the time honoured practice of puppeteering. In puppeteering, an articulated but inanimate object seemingly comes to live through the combined effects of a human controlling select limbs of a puppet while the rest of the puppet's body moves according to gravity and mechanics. In the approach described here, the puppet is a machine-learning-based artificial character that has been trained on motion capture recordings of a human dancer. A single limb of this character is controlled either manually or algorithmically while the machine-learning system takes over the role of physics in controlling the remainder of the character's body. But rather than imitating physics, the machine-learning system generates body movements that are reminiscent of the particular style and technique of the dancer who was originally recorded for acquiring training data. More specifically, the machine-learning system operates by searching for body movements that are not only similar to the training material but that it also considers compatible with the externally controlled limb. As a result, the character playing the role of a puppet is no longer passively responding to the puppeteer but makes movement decisions on its own. This form of puppeteering establishes a form of dialogue between puppeteer and puppet in which both improvise together, and in which the puppet exhibits some of the creative idiosyncrasies of the original human dancer.
Generative machine learning models for creative purposes play an increasingly prominent role in the field of dance and technology. A particularly popular approach is the use of such models for generating synthetic motions. Such motions can either serve as source of ideation for choreographers or control an artificial dancer that acts as improvisation partner for human dancers. Several examples employ autoencoder-based deep-learning architectures that have been trained on motion capture recordings of human dancers. Synthetic motions are then generated by navigating the autoencoder's latent space. This paper proposes an alternative approach of using an autoencoder for creating synthetic motions. This approach controls the generation of synthetic motions on the level of the motion itself rather than its encoding. Two different methods are presented that follow this principle. Both methods are based on the interactive control of a single joint of an artificial dancer while the other joints remain under the control of the autoencoder. The first method combines the control of the orientation of a joint with iterative autoencoding. The second method combines the control of the target position of a joint with forward kinematics and the application of latent difference vectors. As illustrative example of an artistic application, this latter method is used for an artificial dancer that plays a digital instrument. The paper presents the implementation of these two methods and provides some preliminary results.
Batteries typically consist of multiple individual cells connected in series. Here we demonstrate single-cell state of charge (SOC) and state of health (SOH) diagnosis in a 24 V class lithium-ion battery. To this goal, we introduce and apply a novel, highly efficient algorithm based on a voltage-controlled model (VCM). The battery, consisting of eight single cells, is cycled over a duration of five months under a simple cycling protocol between 20 % and 100 % SOC. The cell-to-cell standard deviations obtained with the novel algorithm were 1.25 SOC-% and 1.07 SOH-% at beginning of cycling. A cell-averaged capacity loss of 9.9 % after five months cycling was observed. While the accuracy of single-cell SOC estimation was limited (probably owed to the flat voltage characteristics of the lithium iron phosphate, LFP, chemistry investigated here), single-cell SOH estimation showed a high accuracy (2.09 SOH-% mean absolute error compared to laboratory reference tests). Because the algorithm does not require observers, filters, or neural networks, it is computationally very efficient (three seconds analysis time for the complete data set consisting of eight cells with approx. 780.000 measurement points per cell).
Strings P
(2021)
Strings is an audiovisual performance for an acoustic violin and two generative instruments, one for creating synthetic sounds and one for creating synthetic imagery. The three instruments are related to each other conceptually , technically, and aesthetically by sharing the same physical principle, that of a vibrating string. This submission continues the work the authors have previously published at xCoAx 2020. The current submission briefly summarizes the previous publication and then describes the changes that have been made to Strings. The P in the title emphasizes, that most of these changes have been informed by experiences collected during rehearsals (in German Proben). These changes have helped Strings to progress from a predominantly technical framework to a work that is ready for performance.
Durch das Verbundprojekt Gendering MINT digital – Open Science aktiv gestalten wurde ermöglicht, die immer noch marginale Inklusion von Genderwissen in MINT für ein erfolgreiches Gender Mainstreaming zu verbessern. Außerdem konnte das Projekt zur Vernetzung von Genderforschung, Lehre in den Gender Studies und Gleichstellungsarbeit beitragen sowie Transferwissen zur Kompetenzbildung in den MINT-Disziplinen erproben, evaluieren und für einen nachhaltigen Einsatz adaptieren.
Strings
(2020)
This article presents the currently ongoing development of an audiovisual performance work with the title Strings. This work provides an improvisation setting for a violinist, two laptop performers, and two generative systems. At the core of Strings lies an approach that establishes a strong correlation among all participants by means of a shared physical principle. The physical principle is that of a vibrating string. The article discusses how this principle is used in both natural and simulated forms as main interaction layer between all performers and as natural or generative principle for creating audio and video.
Ultra-low-power passive telemetry systems for industrial and biomedical applications have gained much popularity lately. The reduction of the power consumption and size of the circuits poses critical challenges in ultra-low-power circuit design. Biotelemetry applications like leakage detection in silicone breast implants require low-power-consuming small-size electronics. In this doctoral thesis, the design, simulation, and measurement of a programmable mixed-signal System-on-Chip (SoC) called General Application Passive Sensor Integrated Circuit (GAPSIC) is presented. Owing to the low power consumption, GAPSIC is capable of completely passive operation. Such a batteryless passive system has lower maintenance complexity and is also free from battery-related health hazards. With a die area of 4.92 mm² and a maximum analog power consumption of 592 µW, GAPSIC has one of the best figure-of-merits compared to similar state-of-the-art SoCs. Regarding possible applications, GAPSIC can read out and digitally transmit the signals of resistive sensors for pressure or temperature measurements. Additionally, GAPSIC can measure electrocardiogram (ECG) signals and conductivity.
The design of GAPSIC complies with the International Organization for Standardization (ISO) 15693/NFC (near field communication) 5 standard for radio frequency identification (RFID), corresponding to the frequency range of 13.56 MHz. A passive transponder developed with GAPSIC comprises of an external memory storage and very few other external components, like an antenna and sensors. The passive tag antenna and reader antenna use inductive coupling for communication and energy transfer, which enables passive operation. A passive tag developed with GAPSIC can communicate with an NFC compatible smart device or an ISO 15693 RFID reader. An external memory storage contains the programmable application-specific firmware.
As a mixed-signal SoC, GAPSIC includes both analog and digital circuitries. The analog block of GAPSIC includes a power management unit, an RFID/NFC communication unit, and a sensor readout unit. The digital block includes an integrated 32-bit microcontroller, developed by the Hochschule Offenburg ASIC design center, and digital peripherals. A 16-kilobyte random-access memory and a read-only 16-kilobyte memory constitute the GAPSIC internal memory. For the fabrication of GAPSIC, one poly, six-metal 0.18 µm CMOS process is used.
The design of GAPSIC includes two stages. In the first stage, a standalone RFID/NFC frontend chip with a power management unit, an RFID/NFC communication unit, a clock regenerator unit, and a field detector unit was designed. In the second stage, the rest of the functional blocks were integrated with the blocks of the RFID/NFC frontend chip for the final integration of GAPSIC. To reduce the power consumption, conventional low-power design techniques were applied extensively like multiple power supplies, and the operation of complementary metal-oxide-semiconductor (CMOS) transistors in the sub-threshold region of operation, as well as further innovative circuit designs.
An overvoltage protection circuit, a power rectifier, a bandgap reference circuit, and two low-dropout (LDO) voltage regulators constitute the power management unit of GAPSIC. The overvoltage protection circuit uses a novel method where three stacked transistor pairs shunt the extra voltage. In the power rectifier, four rectifier units are arranged in parallel, which is a unique approach. The four parallel rectifier units provide the optimal choice in terms of voltage drop and the area required.
The communication unit is responsible for RFID/NFC communication and incorporates demodulation and load modulation circuitry. The demodulator circuit comprises of an envelope detector, a high-pass filter, and a comparator. Following a new approach, the bandgap reference circuit itself acts as the load for the envelope detector circuit, which minimizes the circuit complexity and area. For the communication between the reader and the RFID/NFC tag, amplitude-shift keying (ASK) is used to modulate signals, where the smallest modulation index can be as low as 10%. A novel technique involving a comparator with a preset offset voltage effectively demodulates the ASK signal. With an effective die area of 0.7 mm² and power consumption of 107 µW, the standalone RFID/NFC frontend chip has the best figure-of-merits compared to the state-of-the-art frontend chips reported in the relevant literature. A passive RFID/NFC tag developed with the standalone frontend chip, as well as temperature and pressure sensors demonstrate the full passive operational capability of the frontend chip. An NFC reader device using a custom-built Android-based application software reads out the sensor data from the passive tag.
The sensor readout circuit consists of a channel selector with two differential and four single-ended inputs with a programmable-gain instrumentation amplifier. The entire sensor readout part remains deactivated when not in use. The internal memory stores the measured offset voltage of the instrumentation amplifier, where a firmware code removes the offset voltage from the measured sensor signal. A 12-bit successive approximation register (SAR) type analog-to-digital-converter (ADC) based on a charge redistribution architecture converts the measured sensor data to a digital value. The digital peripherals include a serial peripheral interface, four timers, RFID/NFC interfaces, sensor readout unit interfaces, and 12-bit SAR logic.
Two sets of studies with custom-made NFC tag antennas for biomedical applications were conducted to ascertain their compatibility with GAPSIC. The first study involved the link efficiency measurements of NFC tag antennas and an NFC reader antenna with porcine tissue. In a separate experiment, the effect of a ferrite compared to air core on the antenna-coupling factor was investigated. With the ferrite core, the coupling factor increased by four times.
Among the state-of-the-art SoCs published in recent scientific articles, GAPSIC is the only passive programmable SoC with a power management unit, an RFID/NFC communication interface, a sensor readout circuit, a 12-bit SAR ADC, and an integrated 32-bit microcontroller. This doctoral research includes the preliminary study of three passive RFID tags designed with discrete components for biomedical and industrial applications like measurements of temperature, pH, conductivity, and oxygen concentration, along with leakage detection in silicone breast implants. Besides its small size and low power consumption, GAPSIC is suitable for each of the biomedical and industrial applications mentioned above due to the integrated high-performance microcontroller, the robust programmable instrumentation amplifier, and the 12-bit analog-to-digital converter. Furthermore, the simulation and measurement data show that GAPSIC is well suited for the design of a passive tag to monitor arterial blood pressure in patients experiencing Peripheral Artery Disease (PAD), which is proposed in this doctoral thesis as an exemplary application of the developed system.
Decarbonisation Strategies in Energy Systems Modelling: APV and e-tractors as Flexibility Assets
(2023)
This work presents an analysis of the impact of introducing Agrophotovoltaic technologies and electric tractors into Germany’s energy system. Agrophotovoltaics involves installing photovoltaic systems in agricultural areas, allowing for dual usage of the land for both energy generation and food production. Electric tractors, which are agricultural machinery powered by electric motors, can also function as energy storage units, providing flexibility to the grid. The analysis includes a sensitivity study to understand how the availability of agricultural land influences Agrophotovoltaic investments, followed by the examination of various scenarios that involve converting diesel tractors to electric tractors. These scenarios are based on the current CO2 emission reduction targets set by the German Government, aiming for a 65% reduction below 1990 levels by 2030 and achieving zero emissions by 2045. The results indicate that approximately 3% of available agricultural land is necessary to establish a viable energy mix in Germany. Furthermore, the expansion of electric tractors tends to reduce the overall system costs and enhances the energy-cost-efficiency of Agrophotovoltaic investments.
Vorhofflimmern ist die häufigste tachykarde Herzrhythmusstörung weltweit. Dabei verliert das Herz seinen normofrequenten Sinusrhythmus und schlägt nicht mehr regelmäßig, sondern zu schnell und unregelmäßig. Vorhofflimmern ist normalerweise keine lebensbedrohliche Herzrhythmusstörung, aber es kann zu einem Schlaganfall führen. Die Ursache dieser Herzrhythmusstörung sind die Kreisende bzw. die fokalen Erregungen im linken Atrium, die hauptsächliche aus einer oder mehreren Pulmonalvenen kommen. Die übliche Therapieverfahren des Vorhofflimmerns ist die Pulmonalvenenisolation.
Diese Bachelorthesis beschäftigt sich daher mit der Modellierung unterschiedlicher linksatrialer Fokus-Modelle und intrakardialer Elektrodenkatheter für die Diagnostik und Terminierung von Vorhofflimmern mittels Pulmonalvenenisolation im Offenburger Herzrhythmusmodell nach Schalk, Krämer und Benke, welches in CST
Studio Suite realisiert wurde.
Zu Beginn wurden die verschiedenen linksatrialen fokalen Flimmerquellen modelliert und daraufhin simuliert. Hierbei wurde jeweils eine Simulation mit linksatrialen fokalen Flimmerquellen, die aus einzelnen, dualen oder allen vier Pulmonalvenen kommen, durchgeführt. Es wurde ebenfalls eine weitere Simulation mit Biosignalen (aus der Realität) erstellt. Mit diesen Simulationen konnte nun der elektrische Erregungsablauf sichtbar gemacht werden. Daraufhin wurden die Katheter für die Diagnostik und für die Pulmonalvenenisolation modelliert und in das bestehende Offenburger Herzrhythmusmodell integriert. Bei den Diagnostik-Kathetern handelte es sich um 10-polige Lasso® Katheter, zwei Varianten von PentaRay® NAV eco Katheter und 4-polige Diagnostik-Katheter „OSYPKA FINDER pure®“. Ablationskatheter sind zwei Varianten von Pentaspline Basket pose Katheter und HELIOSTAR™ Ablation Ballon. Abschließend wurden verschiedene Varianten von Isolationsverfahren der Pulmonalvenen modelliert und daraufhin die linksatrialen fokalen Flimmerquellen nach der Isolation der Pulmonalvenen simuliert.
This paper presents a streaming-based E-Learning environment where closer integration between learning and work is achieved by integrating multimedia services into manufacturing processes. It contains a comprehensive and detailed explanation of the proposed E-Learning streaming framework, especially the adaption of streaming services to mobile environments. We first analyze several scenarios where E-Learning streaming services can be integrated into manufacturing processes. To allow systematic and tailor-made integration, we develop a model and a specification language for E-Learning streaming services and apply the model using practical scenarios from real manufacturing processes. Adaption of multimedia streaming services to mobile devices is discussed based on Synchronized Multimedia Integration Language (SMIL). Last, we comment on the benefits of using E-Learning streaming services as part of manufacturing processes and analyze the acceptance of the developed system. The key components of our E-Learning environment are 1) an xml based streaming service specification language, 2) adaption of multimedia E-Learning services to mobile environments, and 3) Web Services for searching, registration, and creation of E-Learning streaming services.
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.
Artificial intelligence (AI), and in particular machine learning algorithms, are of increasing importance in many application areas but interpretability and understandability as well as responsibility, accountability, and fairness of the algorithms' results, all crucial for increasing the humans' trust into the systems, are still largely missing. Big industrial players, including Google, Microsoft, and Apple, have become aware of this gap and recently published their own guidelines for the use of AI in order to promote fairness, trust, interpretability, and other goals. Interactive visualization is one of the technologies that may help to increase trust in AI systems. During the seminar, we discussed the requirements for trustworthy AI systems as well as the technological possibilities provided by interactive visualizations to increase human trust in AI.
Projektmanagement und mit ihm die PM-Prozesse, Methoden und Werkzeuge entwickeln sich stetig weiter, in kleinen, kaum spürbaren Schritten oder in großen unübersehbaren Veränderungen. In den letzten Jahren war der Diskurs über das Pro & Contra agiler Vorgehensweisen so allgegenwärtig, dass andere Aspekte nicht immer die notwendige Aufmerksamkeit bekamen. Erkannte Notwendigkeiten der PM-Entwicklung konnten noch nicht in spürbare Fortschritte umgewandelt werden. Einflüsse der Globalisierung und der IT, aber auch die aus der zunehmenden Forderung nach Nachhaltigkeit resultierenden Veränderungen in der Projektarbeit sollen daher genauer betrachtet werden. Ist erst einmal die Sensibilität für relevante Trends beim Projektpersonal geschaffen, rücken ein aktualisiertes Kompetenzprofil und ein erweiterter Methodenkanon in greifbare Nähe.
The invention concerns a method for spectrum monitoring a given frequency band, in which the spectral power density (S(f)) within the given frequency band is determined for all noise and signal components in the frequency band and, in order to detect the presence of one or more signals within the given frequency band, it is evaluated whether the spectral power density (S(f)) exceeds a threshold value (&lgr;). According to the invention, the threshold value (&lgr;) is calculated in accordance with an estimation of a distribution density (hR(S)) for the noise component of the spectral power density (S(f)) within the given frequency band and in accordance with a predefined value for the false-alarm probability (Pfa).
The invention relates to a container (1) for a liquid medium (3), in particular a blood bag, comprising a flexible outer wall (5) and a device (13) connected to the container (1) for acquiring and/or storing data. According to the invention, the device (13) for acquiring and/or storing data is arranged within the flexible outer wall (5), wherein positioning means (15) are provided which hold the device (13) for acquiring and/or storing data in a floating manner in the liquid medium when the container (1) is filled with said liquid medium (3), and wherein the device (13) or the device (13) and the positioning means (15) are designed such that the mass of liquid medium (3) which is displaced in each case is essentially equal to the mass of the device (13) or to the mass of the device (13) and the positioning means (15).
A wet-chemical treatment system for electrochemically coating flat substrates with coating material, has having a basin for receiving an electrolyte, a transporting means, by means of which the flat substrates can be transported through the electrolyte horizontally, and at least one contact element which comprises a shaft having an axis of rotation and a cylindrical circumferential surface suitable for rolling on the substrate, wherein the circumferential surface comprises at least one electrically insulated segment and at least one electrically conductive segment which can be connected to a current source in such a way that the polarity can be reversed, wherein the axis of rotation of the contact element is positioned above the surface of the electrolyte, and wherein the contact element is designed as a consumable electrode.
본 발명은 기판들을 금속화하기 위한 디바이스에 관한 것이다. 특별히, 본 발명은 습식-화학물질 연속 (인-라인) 처리 시스템 환경에서 솔라 셀들을 전기도금하기 위해 사용되는 컨택 엘리먼트(contact element)들의 분야에 관한 것이다. 코팅 재료로 평평한 기판들(1)들을 전기화학적으로 코팅하기 위한 본 발명에 따른 습식-화학물질 처리 시스템은 전해질 용액, 이송 수단들 - 이송 수단들을 이용하여 평평한 기판(1)이 전해질 용액을 통과하여 수평으로 이송될 수 있는 - 을 수용하는 용기(basin), 및 회전축(5)을 갖는 샤프트(4) 및 기판(1) 위에서 구르기에 적합한 원통형의 원주 표면을 포함하는 적어도 하나의 컨택 엘리먼트(2)를 가지며, 원주 표면은 극성이 역전될 수 있는 방식으로 전류 소스 (6)에 연결될 수 있는 적어도 하나의 전기적으로 전도성인 세그먼트 (3A) 및 적어도 하나의 전기적으로 절연된 세그먼트 (3B)를 포함하고, 컨택 엘리먼트 (2)의 회전축 (5)은 전해질 용액의 표면 위에 위치되고, 컨택 엘리먼트 (2)는 소모 전극(consumable electrode)으로 디자인된다.
The invention relates to a device for metalising substrates. In particular, the invention relates to the field of contact elements used to electroplate solar cells within the context of a wet-chemical continuous treatment system. A wet-chemical treatment system according to the invention, for electrochemically coating flat substrates (1) with coating material, has a tank for accommodating an electrolyte, transporting means, by means of which the flat substrates (1) can be transported through the electrolyte horizontally, and at least one contact element (2), which comprises a shaft (4) having an axis of rotation (5) and a cylindrical circumferential surface suitable for rolling on the substrate (1), wherein the circumferential surface comprises at least one electrically insulating segment (3B) and at least one electrically conductive segment (3A), which can be connected to a current source (6) in such a way that the polarity can be reversed, wherein the axis of rotation (5) of the contact element (2) is positioned above the surface of the electrolyte, and wherein the contact element (2) is designed as a consumable electrode.
Nasschemische Behandlungsanlage zum elektrochemischen Beschichten von flachen Substraten (1) mit Beschichtungsmaterial, mit einem Becken zur Aufnahme eines Elektrolyten, und mit Transportmitteln, mit welchen die flachen Substrate (1) horizontal durch den Elektrolyten transportierbar sind, sowie mit mindestens einem Kontaktelement (2), welches eine Welle (4) mit Drehachse (5) und eine zum Abrollen auf dem Substrat (1) geeignete zylindrische Umfangsfläche aufweist, wobei die Umfangsfläche mindestens ein elektrisch isoliertes Segment (3B) und mindestens ein elektrisch leitendes Segment (3A) umfasst, das mit einer Stromquelle (6) umpolbar verbindbar ist, wobei die Drehachse (5) des Kontaktelements (2) oberhalb der Oberfläche des Elektrolyten positioniert ist, und wobei das Kontaktelement (2) als Verbrauchselektrode ausgestaltet ist.
Die Erfindung betrifft eine Vorrichtung zum Metallisieren von Substraten. Insbesondere betrifft die Erfindung das Gebiet der zur Galvanisierung von Solarzellen verwendeten Kontaktelemente im Rahmen einer nasschemischen Durchlauf-Behandlungsanlage. Eine erfindungsgemäße nasschemische Behandlungsanlage zum elektrochemischen Beschichten von flachen Substraten (1) mit Beschichtungsmaterial hat ein Becken zur Aufnahme eines Elektrolyten, sowie Transportmittel, mit welchen die flachen Substrate (1) horizontal durch den Elektrolyten transportierbar sind, und mindestens ein Kontaktelement (2), welches eine Welle (4) mit Drehachse (5) und eine zum Abrollen auf dem Substrat (1) geeignete zylindrische Umfangsfläche aufweist, wobei die Umfangsfläche mindestens ein elektrisch isoliertes Segment (3B) und mindestens ein elektrisch leitendes Segment (3A) umfasst, das mit einer Stromquelle (6) umpolbar verbindbar ist, wobei die Drehachse (5) des Kontaktelements (2) oberhalb der Oberfläche des Elektrolyten positioniert ist.
Die Erfindung betrifft das Gebiet des Transports flacher Substrate wie beispielsweise Siliziumsubstrate. Insbesondere betrifft die Erfindung den besonders schonenden und kontinuierlichen Transport solcher Substrate. Das erfindungsgemäße Verfahren dient dem Transport eines vertikal ausgerichteten flachen Substrats (1) in eine Transportrichtung innerhalb eines mit einem flüssigen Medium (F) gefüllten Transportkanals (2), wobei das flüssige Medium (F) gegen mindestens eine der Flachseiten des Substrats (1) strömt und eine die Summe aus Gewichts- und Auftriebskraft des Substrats (1) aufhebende Tragekomponente, sowie eine in Transportrichtung gerichtete Vorschubkomponente aufweist, so dass das Substrat (1) ohne mechanische Hilfsmittel getragen und transportiert wird. Die erfindungsgemäße Vorrichtung umfasst einen Transportkanal (2) zur Aufnahme eines flüssiges Mediums (F) sowie eines innerhalb dieses Mediums (F) in vertikaler Ausrichtung zu führenden Substrats (1), wobei der Transportkanal (2) in seinem Wandbereich (3, 4) Einströmöffnungen (5) aufweist.
Die Erfindung betrifft das Gebiet des Transports flacher Substrate wie beispielsweise Siliziumsubstrate. Insbesondere betrifft die Erfindung den besonders schonenden und kontinuierlichen Transport solcher Substrate. Das erfindungsgemäße Verfahren dient dem Transport eines vertikal ausgerichteten flachen Substrats (1) in eine Transportrichtung innerhalb eines mit einem flüssigen Medium (F) gefüllten Transportkanals (2), wobei das flüssige Medium (F) gegen mindestens eine der Flachseiten des Substrats (1) strömt und eine die Summe aus Gewichts- und Auftriebskraft des Substrats (1) aufhebende Tragekomponente, sowie eine in Transportrichtung gerichtete Vorschubkomponente aufweist, so dass das Substrat (1) ohne mechanische Hilfsmittel getragen und transportiert wird. Die erfindungsgemäße Vorrichtung umfasst einen Transportkanal (2) zur Aufnahme eines flüssiges Mediums (F) sowie eines innerhalb dieses Mediums (F) in vertikaler Ausrichtung zu führenden Substrats (1), wobei der Transportkanal (2) in seinem Wandbereich (3, 4) Einströmöffnungen (5) aufweist.
The invention relates to a method for determining properties of a pipeline, more particularly the position of a branch in a waste water pipeline, in which: a sound wave transmission signal (S, S') is fed into the pipeline (1) at a predetermined infeed point and propagates in the axial direction of the pipeline (1), wherein the frequency spectrum of the sound wave transmission signal (S, S') has a frequency component or a spectral range, the maximum frequency of which is lower than the lower limit frequency (fc) for the first upper mode; in which method components (Sr1, Sr2, Sr3, S'r1, S'r2, S'r3) of the sound wave transmission signal (S, S') reflected inside the pipeline (1) are detected as a sound wave reception signal (E, E'); and in which method, by evaluating the sound wave reception signal (E, E') in relation to the sound wave transmission signal (S, S'), the pipeline (1) is examined for the presence of reflection sites along the pipeline (1) that cause sound wave reflections (Sr1, Sr2, Sr3, S'r1, S'r2, S'r3), wherein at least the distance (I) of a reflection site from the infeed point is determined by evaluating the respective sound wave reception signal (E, E'). The invention further relates to a device for implementing said method.
Verfahren zur Bestimmung von Eigenschaften einer Rohrleitung, insbesondere der Position eines Abzweigs einer Abwasserrohrleitung,(a) bei dem ein Schallwellensendesignal (S, S') an einem vorgegebenen Einspeisepunkt in die Rohrleitung (1) eingespeist wird und sich in axialer Richtung der Rohrleitung (1) ausbreitet,(b) wobei das Frequenzspektrum des Schallwellensendesignals (S, S') eine Frequenzkomponente oder einen Spektralbereich aufweist, dessen maximale Frequenz kleiner ist als die untere Grenzfrequenz (f) für die erste Obermode,(c) bei dem innerhalb der Rohrleitung (1) reflektierte Anteile (S, S, S, S', S', S') des Schallwellensendesignals (S, S') als Schallwellenempfangssignal (E, E') detektiert werden, und(d) bei dem die Rohrleitung (1) durch eine Auswertung des Schallwellenempfangssignal (E, E') in Bezug auf das Schallwellensendesignal (S, S') hinsichtlich des Vorhandenseins von Schallwellenreflexionen (S, S, S, S', S', S') verursachenden Reflexionsorten entlang der Rohrleitung (1) untersucht wird,(e) wobei mittels der Auswertung des Schallwellenempfangssignals (E, E') zumindest jeweils der Abstand (I) eines Reflexionsortes von dem Einspeisepunkt bestimmt wird, dadurch gekennzeichnet,(f) dass die Schallgeschwindigkeit (c) der Grundmode bei der aktuellen Temperatur innerhalb der Rohrleitung (1) unter Verwendung eines Schallwellenmesssignals ermittelt wird, welches eine Frequenz oder ein Frequenzspektrum aufweist, bei dem das Schallwellenmesssignal innerhalb der Rohrleitung (1) mit ausreichender Genauigkeit als ebene Schallwelle behandelt werden kann, wobei hierzu die Laufzeiten des Schallwellenmesssignals über eine vorbekannte Strecke (L) in beiden Richtungen gemessen wird,(g) dass die so ermittelte Schallgeschwindigkeit (c) einer ebenen Schallwelle gleich der tatsächlichen Schallgeschwindigkeit der Grundmode bei der aktuellen Temperatur innerhalb der Rohrleitung (1) gesetzt wird, und(h) dass die so bestimmte Schallgeschwindigkeit zur Bestimmung des Abstand (I) eines Reflexionsortes von dem Einspeisepunkt verwendet wird.
Verfahren zur Bestimmung von Eigenschaften einer Rohrleitung, insbesondere der Position eines Abzweigs einer Abwasserrohrleitung, (a) bei dem ein Schallwellensendesignal (S, S') an einem vorgegebenen Einspeisepunkt in die Rohrleitung (1) eingespeist wird und sich in axialer Richtung der Rohrleitung (1) ausbreitet, (b) wobei das Frequenzspektrum des Schallwellensendesignals (S, S') eine Frequenzkomponente oder einen Spektralbereich aufweist, dessen maximale Frequenz kleiner ist als die untere Grenzfrequenz (fc) für die erste Obermode, (c) bei dem innerhalb der Rohrleitung (1) reflektierte Anteile (Sr1, Sr2, Sr3, S'r1, S'r2, S'r3) des Schallwellensendesignals (S, S') als Schallwellenempfangssignal (E, E') detektiert werden, und (d) bei dem die Rohrleitung (1) durch eine Auswertung des Schallwellenempfangssignal (E, E') in Bezug auf das Schallwellensendesignal (S, S') hinsichtlich des Vorhandenseins von Schallwellenreflexionen (Sr1, Sr2, Sr3, S'r1, S'r2, S'r3) verursachenden Reflexionsorten entlang der Rohrleitung (1) untersucht wird, (e) wobei mittels der Auswertung des Schallwellenempfangssignals (E, E') zumindest jeweils der Abstand (I) eines Reflexionsortes von dem Einspeisepunkt bestimmt wird.
Die Erfindung betrifft ein Verfahren zur Bestimmung von Eigenschaften einer Rohrleitung, insbesondere der Position eines Abzweigs einer Abwasserrohrleitung, bei dem ein Schallwellensendesignal (S, S‘) an einem vorgegebenen Einspeisepunkt in die Rohrleitung (1) eingespeist wird und sich in axialer Richtung der Rohrleitung (1) ausbreitet, wobei das Frequenzspektrum des Schallwellensendesignals (S, S‘) eine Frequenzkomponente oder einen Spektralbereich aufweist, dessen maximale Frequenz kleiner ist als die untere Grenzfrequenz (fc) für die erste Obermode, bei dem innerhalb der Rohrleitung (1) reflektierte Anteile (Sr1, Sr2, Sr3, S’r1, S’r2, S’r3) des Schallwellensendesignals (S, S‘) als Schallwellenempfangssignal (E, E‘) detektiert werden, und bei dem die Rohrleitung (1) durch eine Auswertung des Schallwellenempfangssignals (E, E‘) in Bezug auf das Schallwellensendesignal (S, S‘) hinsichtlich des Vorhandenseins von Schallwellenreflexionen (Sr1, Sr2, Sr3, S’r1, S’r2, S’r3) verursachenden Reflexionsorten entlang der Rohrleitung (1) untersucht wird, wobei mittels der Auswertung des Schallwellenempfangssignals (E, E‘) zumindest jeweils der Abstand (l) eines Reflexionsortes von dem Einspeisepunkt bestimmt wird. Des Weiteren betrifft die Erfindung eine Vorrichtung zur Realisierung des Verfahrens.
Die Erfindung betrifft einen elektromotorischen Aktor, insbesondere für einen mobilen Roboter, mit einem geschalteten, zylindrischen Linearreluktanzmotor-Antrieb (21), bestehend aus einem hohlzylindrischen Stator (23), welcher am Innenumfang zwischen umlaufenden Statorzähnen (23a) vorgesehene umlaufende Nuten (23b) aufweist, in welchen Motorwicklungen (27a, 27b, 27c, 27’a, 27’b, 27’c) angeordnet sind, und einem innerhalb des Stators (23) koaxial vorgesehenen zylindrischen oder hohlzylindrischen Translator (25) mit am Außenumfang vorgesehenen, umlaufenden Translatorzähnen (25a), wobei der Stator (23) im Bereich der Statorzähne (23a) und der Translator (25) im Bereich der Translatorzähne (25a) aus einem ferromagnetischen Material bestehen. Erfindungsgemäß ist der Translator (25) über eine mechanische Vorrichtung zur Speicherung und Abgabe von kinetischer Energie (31) fest oder nur für einen vorbestimmten Bereich eines Bewegungsbereichs des Translators (25) mit dem Stator (25) gekoppelt.
Die Erfindung betrifft ein Behältnis (1) für ein flüssiges Medium (3), insbesondere Blutbeutel, mit einer flexiblen Außenwandung (5) und einer mit dem Behältnis (1) verbundenen Vorrichtung (13) zur Erfassung und/oder Speicherung von Daten. Erfindungsgemäß ist die Vorrichtung (13) zur Erfassung und/oder Speicherung von Daten innerhalb der flexiblen Außenwandung (5) angeordnet, wobei Positionierungsmittel (15) vorgesehen sind, welche die Vorrichtung (13) zur Erfassung und/oder Speicherung von Daten bei mit dem flüssigen Medium (3) gefüllten Behältnis (1) schwimmend im flüssigen Medium (3) halten, und wobei die Vorrichtung (13) oder die Vorrichtung (13) und die Positionierungsmittel (15) so ausgebildet sind, dass die jeweils verdrängte Masse von flüssigem Medium (3) im Wesentlichen gleich der Masse der Vorrichtung (13) oder der Masse der Vorrichtung (13) und der Positionierungsmittel (15) ist.
Die Erfindung betrifft ein Behältnis (1) für ein flüssiges Medium (3), insbesondere Blutbeutel, mit einer flexiblen Außenwandung (5) und einer mit dem Behältnis (1) verbundenen Vorrichtung (13) zur Erfassung und/oder Speicherung von Daten. Erfindungsgemäß ist die Vorrichtung (13) zur Erfassung und/oder Speicherung von Daten innerhalb der flexiblen Außenwandung (5) angeordnet, wobei Positionierungsmittel (15) vorgesehen sind, welche die Vorrichtung (13) zur Erfassung und/oder Speicherung von Daten bei mit dem flüssigen Medium (3) gefüllten Behältnis (1) schwimmend im flüssigen Medium (3) halten, und wobei die Vorrichtung (13) oder die Vorrichtung (13) und die Positionierungsmittel (15) so ausgebildet sind, dass die jeweils verdrängte Masse von flüssigem Medium (3) im Wesentlichen gleich der Masse der Vorrichtung (13) oder der Masse der Vorrichtung (13) und der Positionierungsmittel (15) ist.
Messschraube zur Ermittlung von Schraubenbelastungen, die einen Schraubenkopf (8) und einen Schraubenschaft (9) mit einem oberen Schaftbereich (7) aufweist, der bei bestimmungsgemäßer Benutzung der Schraube nicht an einem Objekt anliegt, wobei mindestens zwei Dehnungsmesssensoren so im Schraubenschaft (9) angeordnet und dehnungskinematisch mit dem Schraubenschaft (9) gekoppelt sind, dass sie Dehnungswerte im Schraubenschaft (9) erfassen, aus denen über konstitutive Materialgesetze Belastungen in mehr als einer Achse im oberen Schaftbereich (7) bestimmt werden können, wobei die Dehnungsmesssensoren als faseroptische Sensoren an mehreren Stellen entlang mindestens einer optischen Faser (1) ausgebildet sind.
Die vorliegende Erfindung betrifft eine Messchraube zur Ermittlung von Schraubenbelastungen sowie ein Verfahren zu deren Herstellung. Die Messschraube umfasst mindestens zwei Dehnungsmesssensoren, die so im Schraubenschaft angeordnet und dehnungskinematisch mit dem Schraubenschaft gekoppelt sind, dass sie Dehnungswerte im Schraubenschaft erfassen, aus denenüber konstitutive Materialgesetze Belastungen in mehr als einer Achse im oberen freien Schaftbereich bestimmt werden können. Durch Möglichkeit der Bestimmung mehrachsiger Belastungen lassen sich Schrauben sachgerechter auslegen, so dass die Gefahr von Schraubenbrüchen reduziert wird.
Elektronische Pille zur steuerbaren Abgabe einer Substanz in einem menschlichen oder tierischen Körper, (a) mit einem Gehäuse (3), in welchem die abzugebende Substanz (17) aufgenommen und in welchem eine Abgabeöffnung (47) zur Abgabe der Substanz (17) vorgesehen ist, wobei die Substanz (17) zur Abgabe aus dem Gehäuse (3) mit einem vorbestimmten Druck beaufschlagt ist, (b) mit einer elektronischen Steuereinheit (53, 59, 61, 63), und (c) mit einer im Verlauf eines Abgabepfades angeordneten Ventileinheit (33), welche von der Steuereinheit (53, 59, 61, 63) von einer Geschlossen- Stellung in eine Geöffnet-Stellung steuerbar ist und umgekehrt, (d) dadurch gekennzeichnet, (e) dass die Ventileinheit (33) eine von der elektronischen Steuereinheit (53, 59, 61, 63) ansteuerbare Heizeinheit (49) umfasst, (f) dass die Ventileinheit (33) ein Schaltelement (39) umfasst, welches in der Geschlossen-Stellung zumindest mit einem Teilbereich dichtend an einem Ventilsitz (37) der Ventileinheit (33) anliegt und welches von der Heizeinheit (49) beheizbar ist, (g) dass das Schaltelement (39) zwei temperaturabhängige stabile Schaltstellungen aufweist, welche durch eine Formänderung des Schaltelements (39) definiert sind, und (h) die Heizeinheit (49) an der dem Ventilsitz (37) abgewandten Seite des Schaltelements (39) angeordnet und integriert mit dem Schaltelement (39) ausgebildet ist (i) wobei die Steuereinheit (53, 59, 61, 63) zum Öffnen der Ventileinheit (33) die Heizeinheit (49) aktiviert, so dass das Schaltelement (39) bei Überschreiten einer Schwellentemperatur aus der Geschlossen-Stellung in die Geöffnet-Stellung geschaltet wird und (j) wobei die Steuereinheit (53, 59, 61, 63) zum Schließen der Ventileinheit (33) die Heizeinheit (49) deaktiviert, so dass das Schaltelement bei Unterschreiten einer Schwellentemperatur aus der Geöffnet-Stellung in die Geschlossen-Stellung schaltet.
Die Erfindung betrifft eine elektronische Pille zur steuerbaren Abgabe einer Substanz, insbesondere eines Medikaments, in einem menschlichen oder tierischen Körper, mit einem Gehäuse (3), in welchem die abzugebende Substanz (17) aufgenommen und in welchem eine Abgabeöffnung (47) zur Abgabe der Substanz (17) vorgesehen ist, wobei die Substanz (17) zur Abgabe aus dem Gehäuse (3) mit einem vorbestimmten Druck beaufschlagbar ist, mit einer elektronischen Steuereinheit (53, 59, 61, 63) und mit einer im Verlauf eines Abgabepfades angeordneten Ventileinheit (33), welche von der Steuereinheit (53, 59, 61, 63) von einer Geöffnet-Stellung in eine Geschlossen-Stellung steuerbar ist. Erfindungsgemäß ist im Gehäuse (3) im Verlauf des Abgabepfades für die abzugebende Substanz (17) eine Drosselstrecke (45) vorgesehen.
The application relates to an electronic pill for dispensing a substance, in particular a drug, in a human or animal body in a controllable manner, said electronic pill having a housing (3) in which the substance (17) to be dispensed is accommodated and in which a dispensing opening (47) for dispensing the substance (17) is provided, wherein the substance (17) can be subjected to a predetermined pressure in order to be dispensed from the housing (3), having an electronic control unit (53, 59, 61, 63), and having a valve unit (33) which is arranged in the course of a dispensing path and can be moved from an open position to a closed position by the control unit (53, 59, 61, 63). In the housing (3), a throttle section (45) is provided in the course of the dispensing path for the substance (17) to be dispensed.
Die Erfindung betrifft eine elektronische Pille zur steuerbaren Abgabe einer Substanz, insbesondere eines Medikaments, in einem menschlichen oder tierischen Körper, mit einem Gehäuse (3), in welchem die abzugebende Substanz (17) aufgenommen und in welchem eine Abgabeöffnung (47) zur Abgabe der Substanz (17) vorgesehen ist, wobei die Substanz (17) zur Abgabe aus dem Gehäuse (3) mit einem vorbestimmten Druck beaufschlagbar ist, mit einer elektronischen Steuereinheit (53, 59, 61, 63) und mit einer im Verlauf eines Abgabepfades angeordneten Ventileinheit (33), welche von der Steuereinheit (53, 59, 61, 63) von einer Geöffnet-Stellung in eine Geschlossen-Stellung steuerbar ist. Erfindungsgemäß ist im Gehäuse (3) im Verlauf des Abgabepfades für die abzugebende Substanz (17) eine Drosselstrecke (45) vorgesehen.
The invention relates to a multi railed track vehicle, designed with a conducting connection of pairs of rails with a connection resistance reducing agent for reducing the connection resistance to the rail. According to the invention, the connection resistance reducing agent is designed to generate arcs between at least one rail and the track vehicle.
Verfahren und Vorrichtung zur Gleisnebenschlusserzeugung durch Bahnfahrzeuge (DE102008038494A1)
(2010)
Die Erfindung betrifft ein mehrgleisiges Schienenfahrzeug, das zur elektrisch leitenden Verbindung von Gleispaaren und mit einem Übergangswiderstandsverringerungsmittel zur Verringerung des Übergangswiderstandes zum Gleis ausgebildet ist. Hierbei ist vorgesehen, dass das Übergangswiderstandsverringerungsmittel zum Generieren von Funken zwischen zumindet einem Gleis und dem Schienenfahrzeug ausgebildet ist.
The device (1) has a detection unit (38) that is provided for detecting two electromagnetic radiations that are radiated by a light source (10) after partial radiography of a medium with applied magnetic field (44). A determination unit (40) is provided for determining a phase relation between the two detected electromagnetic radiations. An evaluation unit (46) is provided for determining a concentration value of a magneto-optic substance in the medium on the basis of the determined phase relation. Independent claims are also included for the following: (1) a method for determining concentration value of a magneto-optic substance in a medium (2) a computer program product for performing a method for determining concentration value of a magneto-optic substance in a medium.
Vorrichtung und Verfahren zur optischen Messung der Entfernung eines Objekts (DE102007060966A1)
(2009)
Eine Vorrichtung zur optischen Messung der Entfernung eines Objekts weist eine Quelle zur Aussendung optischer Strahlung, die eine eine optische Strahlung transportierende Lichtleitfaser aufweist, ein optisches Element, welches die optische Strahlung fokussiert und auf das Objekt abbildet, und einen Empfänger auf, der die optische Strahlung empfängt und in ein elektrisches Signal zur Weitergabe an eine Steuereinrichtung umwandelt. Die Lichtleitfaser ist mittels einer Verschiebeeinrichtung relativ zu dem optischen Element verschieblich. Ein Abschnitt der Lichtleitfaser führt zu dem Empfänger und ist mittels einer Kopplungseinrichtung mit einem von der Quelle zur Aussendung optischer Strahlung ausgehenden Abschnitt der Lichtleitfaser zu einer einzigen, mittels der Verschiebeeinrichtung verschieblichen Lichtleitfaser gekoppelt.
Die vorliegende Erfindung betrifft ein Verfahren zur Laufzeitmessung mittels Ultraschall, bei dem ein komplexes Sendesignal erzeugt wird, mit dem zumindest ein Ultraschallsender durch Aussenden eines Ultraschallpulses angesteuert wird. Mit zumindest einem Ultraschallempfänger wird der Ultraschallpuls nach Durchlaufen einer Übertragungsstrecke empfangen und in ein komplexes Empfangssignal gewandelt. Das komplexe Empfangssignal wird mit dem komplexen Sendesignal korreliert, um ein komplexes Korrelationssignal zu erhalten. Das Korrelationssignal wird nicht nur nach Betrag, sondern auch nach Phase ausgewertet, um eine Laufzeit des Ultraschalls auf der Übertragungsstrecke zu bestimmen. Auf diese Weise wird zum einen eine höhere Genauigkeit der Laufzeitmessung erreicht, zum anderen beeinflussen andere akustische Laufwege des Ultraschallpulses die Messgenauigkeit nicht, so dass nur geringe Anforderungen an die Qualität der akustischen Übertragungsstrecke gestellt werden müssen.
Die Erfindung betrifft eine Anordnung zur Messung von Temperatur und Luftdruck sowie der Überwachung des Verschleißes von Fahrzeugreifen, wobei hierfür eine Drahtschleife in das Profil eingebettet wird, die bei verschlissenem Reifen unterbrochen wird, die Messung von Temperatur und Druck in einem sehr kleinen, in die Reifenwange einvulkanisierten elektronischen Transponder erfolgt (Bild 2), der die Meßwerte auf Anforderung des Tranceivers induktiv mit einem digitalen Trägerfrequenzverfahren über eine radial in der Reifenwange integrierte Flachspule auf einen am Fahrzeug montierten Transceiver überträgt. Der Transponder besteht erfindungsgemäß aus einem/wenigen Siliziumchips, auf denen Temperatursensor und mikromechanischer Drucksensor zusammen mit einem Mikroprozessor und zugehöriger Auswerte- und Übertragungselektronik integriert sind, sowie wenigen externen Komponenten, alle in einem Kunststoffgehäuse aus einem Material, das aus der gleichen Stoffgruppe kommt wie das Reifenmaterial oder mit diesem sich sehr innig verbinden läßt, zusammengefaßt. Die Kommunikation erfolgt erfindungsgemäß zwischen Transceiver und Transponder in geträgerter digitaler Form, wobei der Transceiver ein Kommando an den Transponder ausstrahlt, der dieses z. B. durch Durchführung der Messung, Kompensation- und Linearisierung der Meßwerte und Übertragung der Meßdaten und/oder weiterer im Transponder gespeicherter Daten beantwortet.
Die Erfindung betrifft eine mobile Vorrichtung zur Messung und Aufzeichnung von Temperaturzeitreihen, bei der die Temperatur in regelmäßigen, vorbestimmten Intervallen erfaßt wird und in einem Halbleiterspeicher abgelegt wird. Erfindungsgemäß werden alle erforderlichen Funktionen einschließlich des Sensors und des Speichers in einer integrierten Schaltung zusammengefügt, welche zusammen mit einer Batterie und einem zeitbestimmenden Element (Quarz) in Form einer Chip-Karte integriert werden. Die Chip-Karte kann erfindungsgemäß durch den Hersteller und den Anwender konfiguriert werden, wobei Daten über den Meßvorgang sowie die Meßintervalle auf der Karte gespeichert werden. Die Karte verfügt ferner erfindungsgemäß über mehrere Betriebszustände, wobei im Zustand "passiv" nahezu kein Strom verbraucht wird (Lagerung), im Zustand "aktiv" eine Meßwerterfassung stattfindet, im Zustand "ruhen" alle Funktionen bis auf eine Zeitgeberfunktion inaktiviert sind. Das Auslesen der Daten ist erfindungsgemäß über Paßworte in mehreren Zugangsebenen abgesichert, eine Manipulation wird ebenso verhindert. Die Anzahl der speicherbaren Meßwerte wird erfindungsgemäß durch ein digitales, blockorientiertes Kompressionsverfahren erhöht. Die Auswertung und Darstellung der Daten erfolgt erfindungsgemäß durch ein externes Datenverarbeitungssystem, wobei die Schnittstelle durch Formgebung und elektrische Ausführung kompatibel mit weitverbreiteten Standards ausgeführt ist.
Introduction: Subjects with mild to moderate hearing loss today often receive hearing aids (HA) with open-fitting (OF). In OF, direct sound reaches the eardrums with minimal damping. Due to the required processing delay in digital HA, the amplified HA sound follows some milliseconds later. This process occurs in both ears symmetrically in bilateral HA provision and is likely to have no or minor detrimental effect on binaural hearing. However, the delayed and amplified sound are only present in one ear in cases of unilateral hearing loss provided with one HA. This processing alters interaural timing differences in the resulting ear signals.
Methods: In the present study, an experiment with normal-hearing subjects to investigate speech intelligibility in noise with direct and delayed sound was performed to mimic unilateral and bilateral HA provision with OF.
Results: The outcomes reveal that these delays affect speech reception thresholds (SRT) in the unilateral OF simulation when presenting speech and noise from different spatial directions. A significant decrease in the median SRT from –18.1 to –14.7 dB SNR is observed when typical HA processing delays are applied. On the other hand, SRT was independent of the delay between direct and delayed sound in the bilateral OF simulation.
Discussion: The significant effect emphasizes the development of rapid processing algorithms for unilateral HA provision.
CNN-based deep learning models for disease detection have become popular recently. We compared the binary classification performance of eight prominent deep learning models: DenseNet 121, DenseNet 169, DenseNet 201, EffecientNet b0, EffecientNet lite4, GoogleNet, MobileNet, and ResNet18 for their binary classification performance on combined Pulmonary Chest Xrays dataset. Despite the widespread application in different fields in medical images, there remains a knowledge gap in determining their relative performance when applied to the same dataset, a gap this study aimed to address. The dataset combined Shenzhen, China (CH) and Montgomery, USA (MC) data. We trained our model for binary classification, calculated different parameters of the mentioned models, and compared them. The models were trained to keep in mind all following the same training parameters to maintain a controlled comparison environment. End of the study, we found a distinct difference in performance among the other models when applied to the pulmonary chest Xray image dataset, where DenseNet169 performed with 89.38 percent and MobileNet with 92.2 percent precision.
The COVID19 pandemic, a unique and devastating respiratory disease outbreak, has affected global populations as the disease spreads rapidly. Recent Deep Learning breakthroughs may improve COVID19 prediction and forecasting as a tool of precise and fast detection, however, current methods are still being examined to achieve higher accuracy and precision. This study analyzed the collection contained 8055 CT image samples, 5427 of which were COVID cases and 2628 non COVID. The 9544 Xray samples included 4044 COVID patients and 5500 non COVID cases. The most accurate models are MobileNet V3 (97.872 percent), DenseNet201 (97.567 percent), and GoogleNet Inception V1 (97.643 percent). High accuracy indicates that these models can make many accurate predictions, as well as others, are also high for MobileNetV3 and DenseNet201. An extensive evaluation using accuracy, precision, and recall allows a comprehensive comparison to improve predictive models by combining loss optimization with scalable batch normalization in this study. Our analysis shows that these tactics improve model performance and resilience for advancing COVID19 prediction and detection and shows how Deep Learning can improve disease handling. The methods we suggest would strengthen healthcare systems, policymakers, and researchers to make educated decisions to reduce COVID19 and other contagious diseases.
This paper presents the new Deep Reinforcement Learning (DRL) library RL-X and its application to the RoboCup Soccer Simulation 3D League and classic DRL benchmarks. RL-X provides a flexible and easy-to-extend codebase with self-contained single directory algorithms. Through the fast JAX-based implementations, RL-X can reach up to 4.5x speedups compared to well-known frameworks like Stable-Baselines3.
The use of artificial intelligence continues to impact a broad variety of domains, application areas, and people. However, interpretability, understandability, responsibility, accountability, and fairness of the algorithms' results - all crucial for increasing humans' trust into the systems - are still largely missing. The purpose of this seminar is to understand how these components factor into the holistic view of trust. Further, this seminar seeks to identify design guidelines and best practices for how to build interactive visualization systems to calibrate trust.
With the rising necessity of explainable artificial intelligence (XAI), we see an increase in task-dependent XAI methods on varying abstraction levels. XAI techniques on a global level explain model behavior and on a local level explain sample predictions. We propose a visual analytics workflow to support seamless transitions between global and local explanations, focusing on attributions and counterfactuals on time series classification. In particular, we adapt local XAI techniques (attributions) that are developed for traditional datasets (images, text) to analyze time series classification, a data type that is typically less intelligible to humans. To generate a global overview, we apply local attribution methods to the data, creating explanations for the whole dataset. These explanations are projected onto two dimensions, depicting model behavior trends, strategies, and decision boundaries. To further inspect the model decision-making as well as potential data errors, a what-if analysis facilitates hypothesis generation and verification on both the global and local levels. We constantly collected and incorporated expert user feedback, as well as insights based on their domain knowledge, resulting in a tailored analysis workflow and system that tightly integrates time series transformations into explanations. Lastly, we present three use cases, verifying that our technique enables users to (1)~explore data transformations and feature relevance, (2)~identify model behavior and decision boundaries, as well as, (3)~the reason for misclassifications.
There is an ongoing debate about the use and scope of Clayton M. Christensen´s idea of disruptive innovation, including the question of whether it is a management buzz phrase or a valuable theory. This discussion considers the general question of how innovation in the field of management theories and concepts finds its way to the different target groups. This conceptual paper combines the different concepts of the creation and dissemination of management trends in a basic framework based on a short review of models for the dissemination of management ideas. This framework allows an analysis of the character of new management ideas like disruptive innovation. By measuring the impact of the theory on the academic sphere using a bibliometric statistic of the number of academic publications on Google scholar and Scopus and a meta-analysis of research papers, we show the significant influence of disruptive innovation beyond pure management fads.
Variable refrigerant flow (VRF) and variable air volume (VAV) systems are considered among the best heating, ventilation, and air conditioning systems (HVAC) thanks to their ability to provide cooling and heating in different thermal zones of the same building. As well as their ability to recover the heat rejected from spaces requiring cooling and reuse it to heat another space. Nevertheless, at the same time, these systems are considered one of the most energy-consuming systems in the building. So, it is crucial to well size the system according to the building’s cooling and heating needs and the indoor temperature fluctuations. This study aims to compare these two energy systems by conducting an energy model simulation of a real building under a semi-arid climate for cooling and heating periods. The developed building energy model (BEM) was validated and calibrated using measured and simulated indoor air temperature and energy consumption data. The study aims to evaluate the effect of these HVAC systems on energy consumption and the indoor thermal comfort of the building. The numerical model was based on the Energy Plus simulation engine. The approach used in this paper has allowed us to reach significant quantitative energy saving along with a high level of indoor thermal comfort by using the VRF system compared to the VAV system. The findings prove that the VRF system provides 46.18% of the annual total heating energy savings and 6.14% of the annual cooling and ventilation energy savings compared to the VAV system.
Modern CNNs are learning the weights of vast numbers of convolutional operators. In this paper, we raise the fundamental question if this is actually necessary. We show that even in the extreme case of only randomly initializing and never updating spatial filters, certain CNN architectures can be trained to surpass the accuracy of standard training. By reinterpreting the notion of pointwise ($1\times 1$) convolutions as an operator to learn linear combinations (LC) of frozen (random) spatial filters, we are able to analyze these effects and propose a generic LC convolution block that allows tuning of the linear combination rate. Empirically, we show that this approach not only allows us to reach high test accuracies on CIFAR and ImageNet but also has favorable properties regarding model robustness, generalization, sparsity, and the total number of necessary weights. Additionally, we propose a novel weight sharing mechanism, which allows sharing of a single weight tensor between all spatial convolution layers to massively reduce the number of weights.
During pyrolysis, biomass is carbonised in the absence of oxygen to produce biochar with heat and/or electricity as co-products making pyrolysis one of the promising negative emission technologies to reach climate goals worldwide. This paper presents a simplified representation of pyrolysis and analyses the impact of this technology on the energy system. Results show that the use of pyrolysis can allow getting zero emissions with lower costs by making changes in the unit commitment of the power plants, e.g. conventional power plants are used differently, as the emissions will be compensated by biochar. Additionally, the process of pyrolysis can enhance the flexibility of energy systems, as it shows a correlation between the electricity generated by pyrolysis and the hydrogen installation capacity, being hydrogen used less when pyrolysis appears. The results indicate that pyrolysis, which is available on the market, integrates well into the energy system with a promising potential to sequester carbon.
3D Bin Picking with an innovative powder filled gripper and a torque controlled collaborative robot
(2023)
A new and innovative powder filled gripper concept will be introduced to a process to pick parts out of a box without the use of a camera system which guides the robot to the part. The gripper is a combination of an inflatable skin, and a powder inside. In the unjammed condition, the powder is soft and can adjust to the geometry of the part which will be handled. By applying a vacuum to the inflatable skin, the powder gets jammed and transforms to a solid shaped form in which the gripper was brought before applying the vacuum. This physical principle is used to pick parts. The flexible skin of the gripper adjusts to all kinds of shapes, and therefore, can be used to realize 3D bin picking. With the help of a force controlled robot, the gripper can be pushed with a consistent force on flexible positions depending of the filling level of the box. A Kuka LBR iiwa with joint torque sensors in all of its seven axis’ was used to achieve a constant contact pressure. This is the basic criteria to achieve a robust picking process.
Socially assistive robots (SARs) are becoming more prevalent in everyday life, emphasizing the need to make them socially acceptable and aligned with users' expectations. Robots' appearance impacts users' behaviors and attitudes towards them. Therefore, product designers choose visual qualities to give the robot a character and to imply its functionality and personality. In this work, we sought to investigate the effect of cultural differences on Israeli and German designers' perceptions and preferences regarding the suitable visual qualities of SARs in four different contexts: a service robot for an assisted living/retirement residence facility, a medical assistant robot for a hospital environment, a COVID-19 officer robot, and a personal assistant robot for domestic use. Our results indicate that Israeli and German designers share similar perceptions of visual qualities and most of the robotics roles. However, we found differences in the perception of the COVID-19 officer robot's role and, by that, its most suitable visual design. This work indicates that context and culture play a role in users' perceptions and expectations; therefore, they should be taken into account when designing new SARs for diverse contexts.
Recent advances in spiked shoe design, characterized by increased longitudinal stiffness, thicker midsole foams, and reconfigured geometry are considered to improve sprint performance. However, so far there is no empirical data on the effects of advanced spikes technology on maximal sprinting speed (MSS) published yet. Consequently, we assessed MSS via ‘flying 30m’ sprints of 44 trained male (PR: 10.32 s - 12.08 s) and female (PR: 11.56 s - 14.18 s) athletes, wearing both traditional and advanced spikes in a randomized, repeated measures design. The results revealed a statistically significant increase in MSS by 1.21% on average when using advanced spikes technology. Notably, 87% of participants showed improved MSS with the use of advanced spikes. A cluster analysis unveiled that athletes with higher MSS may benefit to a greater extent. However, individual responses varied widely, suggesting the influence of multiple factors that need detailed exploration. Therefore, coaches and athletes are advised to interpret the promising performance enhancements cautiously and evaluate the appropriateness of the advanced spike technology for their athletes critically.
High-tech running shoes and spikes ("super-footwear") are currently being debated in sports. There is direct evidence that distance running super shoes improve running economy; however, it is not well established to which extent world-class performances are affected over the range of track and road running events.
This study examined publicly available performance datasets of annual best track and road performances for evidence of potential systematic performance effects following the introduction of super footwear. The analysis was based on the 100 best performances per year for men and women in outdoor events from 2010 to 2022, provided by the world governing body of athletics (World Athletics).
We found evidence of progressing improvements in track and road running performances after the introduction of super distance running shoes in 2016 and super spike technology in 2019. This evidence is more pronounced for distances longer than 1500 m in women and longer than 5000 m in men. Women seem to benefit more from super footwear in distance running events than men.
While the observational study design limits causal inference, this study provides a database on potential systematic performance effects following the introduction of super shoes/spikes in track and road running events in world-class athletes. Further research is needed to examine the underlying mechanisms and, in particular, potential sex differences in the performance effects of super footwear.
We revisit the quantitative analysis of the ultrafast magnetoacoustic experiment in a freestanding nickel thin film by Kim and Bigot [J.-W. Kim and J.-Y. Bigot, Phys. Rev. B 95, 144422 (2017)] by applying our recently proposed approach of magnetic and acoustic eigenmode decomposition. We show that the application of our modeling to the analysis of time-resolved reflectivity measurements allows for the determination of amplitudes and lifetimes of standing perpendicular acoustic phonon resonances with unprecedented accuracy. The acoustic damping is found to scale as ∝ω2 for frequencies up to 80 GHz, and the peak amplitudes reach 10−3. The experimentally measured magnetization dynamics for different orientations of an external magnetic field agrees well with numerical solutions of magnetoelastically driven magnon harmonic oscillators. Symmetry-based selection rules for magnon-phonon interactions predicted by our modeling approach allow for the unambiguous discrimination between spatially uniform and nonuniform modes, as confirmed by comparing the resonantly enhanced magnetoelastic dynamics simultaneously measured on opposite sides of the film. Moreover, the separation of timescales for (early) rising and (late) decreasing precession amplitudes provide access to magnetic (Gilbert) and acoustic damping parameters in a single measurement.
While most ultrafast time-resolved optical pump-probe experiments in magnetic materials reveal the spatially homogeneous magnetization dynamics of ferromagnetic resonance (FMR), here we explore the magneto-elastic generation of GHz-to-THz frequency spin waves (exchange magnons). Using analytical magnon oscillator equations, we apply time-domain and frequency-domain approaches to quantify the results of ultrafast time-resolved optical pump-probe experiments in free-standing ferromagnetic thin films. Simulations show excellent agreement with the experiment, provide acoustic and magnetic (Gilbert) damping constants and highlight the role of symmetry-based selection rules in phonon-magnon interactions. The analysis is extended to hybrid multilayer structures to explore the limits of resonant phonon-magnon interactions up to THz frequencies.
The utilisation of artificial intelligence (AI) is progressively emerging as a significant mechanism for innovation in human resource management (HRM). The capacity to facilitate the transformation of employee performance across numerous responsibilities. AI development, there remains a dearth of comprehensive exploration into the potential opportunities it presents for enhancing workplace performance among employees. To bridge this gap in knowledge, the present work carried out a survey with 300 participants, utilises a fuzzy set-theoretic method that is grounded on the conceptualisation of AI, KS, and HRM. The findings of our study indicate that the exclusive adoption of AI technologies does not adequately enhance HRM engagements. In contrast, the integration of AI and KS offers a more viable HRM approach for achieving optimal performance in a dynamic digital society. This approach has the potential to enhance employees’ proficiency in executing their responsibilities and cultivate a culture of creativity inside the firm.
Recently, photovoltaic (PV) with energy storage systems (ESS) have been widely adopted in buildings to overcome growing power demands and earn financial benefits. The overall energy cost can be optimized by combining a well-sized hybrid PV/ESS system with an efficient energy management system (EMS). Generally, EMS is implemented within the overall functions of the Building Automation System (BAS). However, due to its limited computing resources, BAS cannot handle complex algorithms that aim to optimize energy use in real-time under different operating conditions. Furthermore, islanding the building's local network to maximize the PV energy share represents a challenging task due to the potential technical risks. In this context, this article addresses an improved approach based on upgrading the BAS data analytics capability by means of an edge computing technology. The edge communicates with the BAS low-level controller using a serial communication protocol. Taking advantage of the high computing ability of the edge device, an optimization-based EMS of the PV/ESS hybrid system is implemented. Different testing scenarios have been carried out on a real prototype with different weather conditions, and the results show the implementation feasibility and technical performance of such advanced EMS for the management of building energy resources. It has also been proven to be feasible and advantageous to operate the local energy network in island mode while ensuring system safety. Additionally, an estimated energy saving improvement of 6.23 % has been achieved using optimization-based EMS compared to the classical rule-based EMS, with better ESS constraints fulfillment.
Following the traditional paradigm of convolutional neural networks (CNNs), modern CNNs manage to keep pace with more recent, for example transformer-based, models by not only increasing model depth and width but also the kernel size. This results in large amounts of learnable model parameters that need to be handled during training. While following the convolutional paradigm with the according spatial inductive bias, we question the significance of \emph{learned} convolution filters. In fact, our findings demonstrate that many contemporary CNN architectures can achieve high test accuracies without ever updating randomly initialized (spatial) convolution filters. Instead, simple linear combinations (implemented through efficient 1×1 convolutions) suffice to effectively recombine even random filters into expressive network operators. Furthermore, these combinations of random filters can implicitly regularize the resulting operations, mitigating overfitting and enhancing overall performance and robustness. Conversely, retaining the ability to learn filter updates can impair network performance. Lastly, although we only observe relatively small gains from learning 3×3 convolutions, the learning gains increase proportionally with kernel size, owing to the non-idealities of the independent and identically distributed (\textit{i.i.d.}) nature of default initialization techniques.
We have developed a methodology for the systematic generation of a large image dataset of macerated wood references, which we used to generate image data for nine hardwood genera. This is the basis for a substantial approach to automate, for the first time, the identification of hardwood species in microscopic images of fibrous materials by deep learning. Our methodology includes a flexible pipeline for easy annotation of vessel elements. We compare the performance of different neural network architectures and hyperparameters. Our proposed method performs similarly well to human experts. In the future, this will improve controls on global wood fiber product flows to protect forests.
State-of-the-art models for pixel-wise prediction tasks such as image restoration, image segmentation, or disparity estimation, involve several stages of data resampling, in which the resolution of feature maps is first reduced to aggregate information and then sequentially increased to generate a high-resolution output. Several previous works have investigated the effect of artifacts that are invoked during downsampling and diverse cures have been proposed that facilitate to improve prediction stability and even robustness for image classification. However, equally relevant, artifacts that arise during upsampling have been less discussed. This is significantly relevant as upsampling and downsampling approaches face fundamentally different challenges. While during downsampling, aliases and artifacts can be reduced by blurring feature maps, the emergence of fine details is crucial during upsampling. Blurring is therefore not an option and dedicated operations need to be considered. In this work, we are the first to explore the relevance of context during upsampling by employing convolutional upsampling operations with increasing kernel size while keeping the encoder unchanged. We find that increased kernel sizes can in general improve the prediction stability in tasks such as image restoration or image segmentation, while a block that allows for a combination of small-size kernels for fine details and large-size kernels for artifact removal and increased context yields the best results.
Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling
(2023)
Convolutional neural networks encode images through a sequence of convolutions, normalizations and non-linearities as well as downsampling operations into potentially strong semantic embeddings. Yet, previous work showed that even slight mistakes during sampling, leading to aliasing, can be directly attributed to the networks' lack in robustness. To address such issues and facilitate simpler and faster adversarial training, [12] recently proposed FLC pooling, a method for provably alias-free downsampling - in theory. In this work, we conduct a further analysis through the lens of signal processing and find that such current pooling methods, which address aliasing in the frequency domain, are still prone to spectral leakage artifacts. Hence, we propose aliasing and spectral artifact-free pooling, short ASAP. While only introducing a few modifications to FLC pooling, networks using ASAP as downsampling method exhibit higher native robustness against common corruptions, a property that FLC pooling was missing. ASAP also increases native robustness against adversarial attacks on high and low resolution data while maintaining similar clean accuracy or even outperforming the baseline.
Motivated by the recent trend towards the usage of larger receptive fields for more context-aware neural networks in vision applications, we aim to investigate how large these receptive fields really need to be. To facilitate such study, several challenges need to be addressed, most importantly: (i) We need to provide an effective way for models to learn large filters (potentially as large as the input data) without increasing their memory consumption during training or inference, (ii) the study of filter sizes has to be decoupled from other effects such as the network width or number of learnable parameters, and (iii) the employed convolution operation should be a plug-and-play module that can replace any conventional convolution in a Convolutional Neural Network (CNN) and allow for an efficient implementation in current frameworks. To facilitate such models, we propose to learn not spatial but frequency representations of filter weights as neural implicit functions, such that even infinitely large filters can be parameterized by only a few learnable weights. The resulting neural implicit frequency CNNs are the first models to achieve results on par with the state-of-the-art on large image classification benchmarks while executing convolutions solely in the frequency domain and can be employed within any CNN architecture. They allow us to provide an extensive analysis of the learned receptive fields. Interestingly, our analysis shows that, although the proposed networks could learn very large convolution kernels, the learned filters practically translate into well-localized and relatively small convolution kernels in the spatial domain.
Assessing the robustness of deep neural networks against out-of-distribution inputs is crucial, especially in safety-critical domains like autonomous driving, but also in safety systems where malicious actors can digitally alter inputs to circumvent safety guards. However, designing effective out-of-distribution tests that encompass all possible scenarios while preserving accurate label information is a challenging task. Existing methodologies often entail a compromise between variety and constraint levels for attacks and sometimes even both. In a first step towards a more holistic robustness evaluation of image classification models, we introduce an attack method based on image solarization that is conceptually straightforward yet avoids jeopardizing the global structure of natural images independent of the intensity. Through comprehensive evaluations of multiple ImageNet models, we demonstrate the attack's capacity to degrade accuracy significantly, provided it is not integrated into the training augmentations. Interestingly, even then, no full immunity to accuracy deterioration is achieved. In other settings, the attack can often be simplified into a black-box attack with model-independent parameters. Defenses against other corruptions do not consistently extend to be effective against our specific attack.
Project website: https://github.com/paulgavrikov/adversarial_solarization
Entity Matching (EM) defines the task of learning to group objects by transferring semantic concepts from example groups (=entities) to unseen data. Despite the general availability of image data in the context of many EM-problems, most currently available EM-algorithms solely rely on (textual) meta data. In this paper, we introduce the first publicly available large-scale dataset for "visual entity matching", based on a production level use case in the retail domain. Using scanned advertisement leaflets, collected over several years from different European retailers, we provide a total of ~786k manually annotated, high resolution product images containing ~18k different individual retail products which are grouped into ~3k entities. The annotation of these product entities is based on a price comparison task, where each entity forms an equivalence class of comparable products. Following on a first baseline evaluation, we show that the proposed "visual entity matching" constitutes a novel learning problem which can not sufficiently be solved using standard image based classification and retrieval algorithms. Instead, novel approaches which allow to transfer example based visual equivalent classes to new data are needed to address the proposed problem. The aim of this paper is to provide a benchmark for such algorithms.
Information about the dataset, evaluation code and download instructions are provided under https://www.retail-786k.org/.
For the treatment of bone defects, biodegradable, compressive biomaterials are needed as replacements that degrade as the bone regenerates. The problem with existing materials has either been their insufficient mechanical strength or the excessive differences in their elastic modulus, leading to stress shielding and eventual failure. In this study, the compressive strength of CPC ceramics (with a layer thickness of more than 12 layers) was compared with sintered β-TCP ceramics. It was assumed that as the number of layers increased, the mechanical strength of 3D-printed scaffolds would increase toward the value of sintered ceramics. In addition, the influence of the needle inner diameter on the mechanical strength was investigated. Circular scaffolds with 20, 25, 30, and 45 layers were 3D printed using a 3D bioplotter, solidified in a water-saturated atmosphere for 3 days, and then tested for compressive strength together with a β-TCP sintered ceramic using a Zwick universal testing machine. The 3D-printed scaffolds had a compressive strength of 41.56 ± 7.12 MPa, which was significantly higher than that of the sintered ceramic (24.16 ± 4.44 MPa). The 3D-printed scaffolds with round geometry reached or exceeded the upper limit of the compressive strength of cancellous bone toward substantia compacta. In addition, CPC scaffolds exhibited more bone-like compressibility than the comparable β-TCP sintered ceramic, demonstrating that the mechanical properties of CPC scaffolds are more similar to bone than sintered β-TCP ceramics.
Die Erfindung betrifft in einem ersten Aspekt eine Vorrichtung zur transkutanen Aufbringung eines elektrischen Stimulationsreizes auf ein Ohr. Die Vorrichtung umfasst einen Schaltungsträger, mindestens zwei Elektroden sowie eine Steuerungseinheit, wobei die Steuerungseinheit dazu konfiguriert ist, anhand von Stimulationsparametern ein elektrisches Stimulationssignal an den Elektroden zu erzeugen. Dabei ist die Vorrichtung, insbesondere eine Oberfläche des Schaltungsträgers der Vorrichtung, auf eine anatomische Form eines Ohres angepasst, sodass Elektroden auf der Oberfläche des Schaltungsträgers aufgebracht sind und ausgewählte Bereiche des Ohres kontaktieren Die Vorrichtung ist dadurch kennzeichnet, dass diese weiterhin einen Sensor zur Erkennung mindestens eines physiologischen Parameter umfasst und eine Steuerungseinheit dazu konfiguriert ist, anhand des mindestens einen physiologischen Parameters die Stimulationsparameter für den Stimulationsreiz anzupassen.In einem weiteren Aspekt betrifft die Erfindung ein Verfahren zur Herstellung der erfindungsgemäßen Vorrichtung.
Die Erfindung betrifft ein Verfahren zum Maximieren der von einer analogen Entropiequelle abgeleiteten Entropie, wobei das Verfahren folgende Schritte aufweist:- Bereitstellen von Eingabedaten für die analoge Entropiequelle (2);- Erzeugen von Rückgabewerten durch die analoge Entropiequelle basierend auf den Eingabedaten (3); und- Gruppieren der Rückgabewerte, wobei das Gruppieren der Rückgabewerte ein Anwenden von Versätzen auf Rückgabewerte aufweist (4).
Sensors and actuators enable creation of context-aware applications in which applications can discover and take advantage of contextual information, such as user location, nearby people and objects. In this work, we use a general context definition, which can be applied to various devices, e.g., robots and mobile devices. Developing context-based software applications is considered as one of the most challenging application domains due to the sensors and actuators as part of a device. We introduce a new development approach for context-based applications by using use-case descriptions and Visual Programming Languages (VPL). The introduction of web-based VPLs, such as Scratch and Snap, has reinvigorated the usefulness of VPLs. We provide an in-depth discussion of our new VPL based method, a step by step development process to enable development of context-based applications. Two case studies illustrate how to apply our approach to different problem domains: Context-based mobile apps and context-based humanoid robot applications.
The main advantage of mobile context-aware applications is to provide effective and tailored services by considering the environmental context, such as location, time, nearby objects and other data, and adapting their functionality according to the changing situations in the context information without explicit user interaction. The idea behind Location-Based Services (LBS) and Object-Based Services (OBS) is to offer fully-customizable services for user needs according to the location or the objects in a mobile user's vicinity. However, developing mobile context-aware software applications is considered as one of the most challenging application domains due to the built-in sensors as part of a mobile device. Visual Programming Languages (VPL) and hybrid visual programming languages are considered to be innovative approaches to address the inherent complexity of developing programs. The key contribution of our new development approach for location and object-based mobile applications is a use case driven development approach based on use case templates and visual code templates to enable even programming beginners to create context-aware mobile applications. An example of the use of the development approach is presented and open research challenges and perspectives for further development of our approach are formulated.
Background/Purpose
Several methods are used to evaluate the outcome of total hip arthroplasty (THA), however, their relationship at different time points after surgery is unclear. The purpose of this exploratory study was to investigate correlations between self-report function, performance-based tests (PBTs) and biomechanical parameters in patients 12 months after THA.
Methods
Eleven patients were included in this preliminary cross-sectional study. Hip disability and Osteoarthritis Outcome Score (HOOS) was completed for self-reported function. As PBTs, the Timed-up-and-Go test (TUG) and 30-Second-Chair-Stand test (30CST) were used. Biomechanical parameters were derived from analyses of hip strength, gait and balance. Potential correlations were calculated using Spearman correlation coefficient r.
Results
HOOS scores and parameters of PBTs showed moderate to strong correlations (0.3 < r < 0.7). Correlation analysis between HOOS scores and biomechanical parameters revealed moderate to strong correlations for hip strength whereas correlations with gait parameters and balance were rather weak (r < 0.3). Moderate to strong correlations were also found between parameters of hip strength and 30CST.
Conclusion
For THA outcome assessment 12 months after surgery, our first results indicate that self-report measures or PBTs could be used. Analysis of hip strength also appears to be reflected in HOOS and PBT parameters and may be considered as an adjunct. Given the weak correlations with gait and balance parameters, we suggest that gait analysis and balance testing should be performed in addition to PROMs and PBTs as they may provide supplementary information, especially for THA patients that are at risk for falls.
Due to globalization and the resulting increase in competition on the market, products must be produced more and more cheaply, especially in series production, because buyers expect new variants or even completely new products in ever shorter cycles. Injection molding is the most important production process for manufacturing plastic components in large quantities. However, the conventional production of a mold is extremely time-consuming and costly, which creates a contradiction to the fast pace of the market. Additive tooling is an area of application of additive manufacturing, which in the field of injection molding is preferably used for the prototype production of mold inserts. This allows injection molding tools to be produced faster and more cheaply than through the subtractive manufacturing of metal tools. Material Jetting processes using polymers (MJT-UV/P), also called Polyjet Modeling (PJM), have a great potential for use in additive tooling. Due to the poorer mechanical and thermal properties compared to conventional mold insert materials, e.g. steel or aluminum, the previously used design principles cannot be applied. Accordingly, new design guidelines are necessary, which are developed in this paper. The necessary information is obtained with the help of a systematic literature research. The design guidelines are mapped in a uniform design guide, which is structured according to the design process of injection molds. The guidelines do not only refer to the constructive design of the injection mold or the polymer mold insert, but to the entire design process and describe the four phases of planning, conception, development and realization. Particular attention is paid to the special geometric designs of a polymer mold insert and the thermomechanical properties of the mold insert materials. As a result, design guidelines are available that are adapted to the special requirements of additive tooling of molds inserts made of plastics for injection molding.
The increasing diffusion of rapidly developing AI technologies led to the idea of the experiment to combine TRIZ-based automated idea generation with the natural language processing tool ChatGPT, using the chatbot to interpret the automatically generated elementary solution principles. The article explores the opportunities and benefits of a novel AI-enhanced approach to teaching systematic innovation, analyses the learning experience, identifies the factors that affect students' innovation and problem-solving performance, and highlights the main difficulties students face, especially in interdisciplinary problems.
LogIKTram
(2023)
Der Anstieg des urbanen Verkehrs belastet zunehmend die Anwohner, die Nutzer der Infrastruktur sowie die Umwelt. Während für die Personenbeförderung die Straßenbahnen eine Entlastung bieten, existieren für den innerstädtischen Logistikverkehr keine passenden Angebote. Aus diesem Grund verfolgt das Projekt LogIKTram das Ziel, den Logistikverkehr mit einer Gütertram auf die Schiene zu verlagern. Hierfür werden ein Logistikkonzept sowie verschiedene Planungsmodelle entwickelt, die eine vereinfachte Nutzung erlauben.