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One of the major challenges impeding the energy transition is the intermittency of solar and wind electricity generation due to their dependency on weather changes. The demand-side energy flexibility contributes considerably to mitigate the energy supply/demand imbalances resulting from external influences such as the weather. As one of the largest electricity consumers, the industrial enterprises present a high demand-side flexibility potential from their production processes and on-site energy assets. In this direction, methods are needed with a focus on enabling the energy flexibility and ensure an active participation of such enterprises in the electricity markets especially with variable prices of electricity. This paper presents a generic model library for an industrial enterprise implemented with optimal control for energy flexibility purposes. The components in the model library represent the typical technical units of an industrial enterprise on material, media, and energy flow levels with their operative constraints. A case study of a plastic manufacturing plant using the generic model library is also presented, in which the results of two simulation with different electricity prices are compared and the behavior of the model can be assessed. The results show that the model provides an optimal scheduling of the manufacturing system according to the variations in the electricity prices, and ensures an optimal control for utilities and energy systems needed for the production.
Solar energy plays a central role in the energy transition. Clouds generate locally large fluctuations in the generation output of photovoltaic systems, which is a major problem for energy systems such as microgrids, among others. For an optimal design of a power system, this work analyzed the variability using a spatially distributed sensor network at Stuttgart Airport. It has been shown that the spatial distribution partially reduces the variability of solar radiation. A tool was also developed to estimate the output power of photovoltaic systems using irradiation time series and assumptions about the photovoltaic sites. For days with high fluctuations of the estimated photovoltaic power, different energy system scenarios were investigated. It was found the approach can be used to have a more realistic representation of aggregated PV power taking spatial smoothing into account and that the resulting PV power generation profiles provide a good basis for energy system design considerations like battery sizing.
The desire to connect more and more devices and to make them more intelligent and more reliable, is driving the needs for the Internet of Things more than ever. Such IoT edge systems require sound security measures against cyber-attacks, since they are interconnected, spatially distributed, and operational for an extended period of time. One of the most important requirements for the security in many industrial IoT applications is the authentication of the devices. In this paper, we present a mutual authentication protocol based on Physical Unclonable Functions, where challenge-response pairs are used for both device and server authentication. Moreover, a session key can be derived by the protocol in order to secure the communication channel. We show that our protocol is secure against machine learning, replay, man-in-the-middle, cloning, and physical attacks. Moreover, it is shown that the protocol benefits from a smaller computational, communication, storage, and hardware overhead, compared to similar works.
In recent years, Physical Unclonable Functions (PUFs) have gained significant attraction in the Internet of Things (IoT) for security applications such as cryptographic key generation and entity authentication. PUFs extract the uncontrollable production characteristics of physical devices to generate unique fingerprints for security applications. One common approach for designing PUFs is exploiting the intrinsic features of sensors and actuators such as MEMS elements, which typically exist in IoT devices. This work presents the Cantilever-PUF, a PUF based on a specific MEMS device – Aluminum Nitride (AlN) piezoelectric cantilever. We show the variations of electrical parameters of AlN cantilevers such as resonance frequency, electrical conductivity, and quality factor, as a result of uncontrollable manufacturing process variations. These variations, along with high thermal and chemical stability, and compatibility with silicon technology, makes AlN cantilever a decent candidate for PUF design. We present a cantilever design, which magnifies the effect of manufacturing process variations on electrical parameters. In order to verify our findings, the simulation results of the Monte Carlo method are provided. The results verify the eligibility of AlN cantilever to be used as a basic PUF device for security applications. We present an architecture, in which the designed Cantilever-PUF is used as a security anchor for PUF-enabled device authentication as well as communication encryption.
Physical unclonable functions (PUFs) are increasingly generating attention in the field of hardware-based security for the Internet of Things (IoT). A PUF, as its name implies, is a physical element with a special and unique inherent characteristic and can act as the security anchor for authentication and cryptographic applications. Keeping in mind that the PUF outputs 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 this work, the PUF output positioning (POP) method is proposed, which is a novel method for grouping the PUF outputs in order to maximize the extracted entropy. To achieve this, an offset data is introduced as helper data, which is used to relax the constraints considered for the grouping of PUF outputs, and deriving more entropy, while reducing the secret key error bits. To implement the method, the key enrollment and key generation algorithms are presented. Based on a theoretical analysis of the achieved entropy, it is proven that POP can maximize the achieved entropy, while respecting the constraints induced to guarantee the reliability of the secret key. Moreover, a detailed security analysis is presented, which shows the resilience of the method against cyber-security attacks. The findings of this work are evaluated by applying the method on a hybrid printed PUF, where it can be practically shown that the proposed method outperforms other existing group-based PUF key generation methods.
Steroid hormones (SHs) are a rising concern due to their high bioactivity, ubiquitous nature, and prolonged existence as a micropollutants in water, they pose a potential risk to both human health and the environment, even at low concentrations. Estrogens, progesterone, and testosterone are the three important types of steroids essential for human development and maintaining multiorgan balance, are focus to this concern. These steroid hormones originate
from various sources, including human and livestock excretions, veterinary medications, agricultural runoff, and pharmaceuticals, contributing to their presence in the environment. According to the recommendation of WHO, the guidance value for estradiol (E2) is 1 ng/L. There are several methods been attempted to remove the SH micropollutant by conventional water and wastewater technologies which are still under research. Among the various methods, electrochemical membrane reactor (EMR) is one of the emerging technologies that can address the challenge of insufficient SHs removal from the aquatic environment by conventional treatment. The degradation of SHs can be significantly influenced by various factors when treated with EMR.
In this project, the removal of SH and the important mechanism for the removal using carbon nanotube CNT-EMR is studied and the efficiency of CNT-EMR in treating the SH micropollutant is identified. By varying different parameters this experiment is carried out with the (PES-CNTs) ultrafiltration membrane. The study is carried out depending upon the SH removal based on the limiting factor such as cell voltage, flux, temperature, concentration, and type of the SH.
With recent developments in the Ukrainian-Russian conflict, many are discussing about Germany’s dependency on fossil fuel imports in its energy system, and how can the country proceed with reducing that dependency. With its wide-ranging consumption sectors, the electricity sector comes as the perfect choice to start with. Recent reports showed that the German federal government is already intending to have a fully renewable electricity by 2035 while exploiting all possible clean power options. This was published in the federal government’s climate emergency program (Easter Package) in early 2022. The aim of this package is to initiate a rapid transition and decarbonization of the electricity sector. The Easter Package expects an enormous growth of renewable energies to a completely new level, with already at least 80% renewable gross energy consumption, with extensive and broad deployment of different generation technologies on various scales. This paper will discuss this ambitious plan and outline some insights into this huge and rapidly increasing step, and show how much will Germany need in order to achieve this huge milestone towards a fully green supply of the electricity sector. Different scenarios and shares of renewables will be investigated in order to elaborate on preponed climate-neutral goal of the electricity sector by 2035. The results pointed out some promising aspects in achieving a 100% renewable power, with massive investments in both generation and storage technologies.
To deal with frequent power outages in developing countries, people turn to solutions like uninterruptible power supply (UPS), which stores electric energy during normal operating hours and use it to meet energy needs during rolling blackout intervals. Locally produced UPSs of poorer power quality are widely accessible in the marketplaces, and they have a negative impact on power quality. The charging and discharging of the batteries in these UPSs generate significant amount of power losses in weak grid environments. The Smart-UPS is our proposed smart energy metering (SEM) solution for low voltage consumers that is provided by the distribution company. It does not require batteries, therefore there is no power loss or harmonic distortion due to corresponding charging and discharging. Through load flow and harmonic analysis of both traditional UPS and Smart-UPS systems on ETAP, this paper examines their impact on the harmonics and stability of the distribution grid. The simulation results demonstrate that Smart-UPS can assist fixing power quality issues in a developing country like Pakistan by providing cleaner energy than the battery-operated traditional UPSs.
Following their success in visual recognition tasks, Vision Transformers(ViTs) are being increasingly employed for image restoration. As a few recent works claim that ViTs for image classification also have better robustness properties, we investigate whether the improved adversarial robustness of ViTs extends to image restoration. We consider the recently proposed Restormer model, as well as NAFNet and the "Baseline network" which are both simplified versions of a Restormer. We use Projected Gradient Descent (PGD) and CosPGD for our robustness evaluation. Our experiments are performed on real-world images from the GoPro dataset for image deblurring. Our analysis indicates that contrary to as advocated by ViTs in image classification works, these models are highly susceptible to adversarial attacks. We attempt to find an easy fix and improve their robustness through adversarial training. While this yields a significant increase in robustness for Restormer, results on other networks are less promising. Interestingly, we find that the design choices in NAFNet and Baselines, which were based on iid performance, and not on robust generalization, seem to be at odds with the model robustness.
BACKGROUND
Various neutral and alkaline peptidases are commercially available for use in protein hydrolysis under neutral to alkaline conditions. However, the hydrolysis of proteins under acidic conditions by applying fungal aspartic peptidases (FAPs) has not been investigated in depth so far. The aim of this study, thus, was to purify a FAP from the commercial enzyme preparation, ROHALASE® BXL, determine its biochemical characteristics, and investigate its application for the hydrolysis of food and animal feed proteins under acidic conditions.
RESULTS
A Trichoderma reesei derived FAP, with an apparent molecular mass of 45.8 kDa (sodium dodecyl sulfate–polyacrylamide gel electrophoresis; SDS-PAGE) was purified 13.8-fold with a yield of 37% from ROHALASE® BXL. The FAP was identified as an aspartate protease (UniProt ID: G0R8T0) by inhibition and nano-LC-ESI-MS/MS studies. The FAP showed the highest activity at 50°C and pH 4.0. Monovalent cations, organic solvents, and reducing agents were tolerated well by the FAP. The FAP underwent an apparent competitive product inhibition by soy protein hydrolysate and whey protein hydrolysate with apparent Ki-values of 1.75 and 30.2 mg*mL−1, respectively. The FAP showed promising results in food (soy protein isolate and whey protein isolate) and animal feed protein hydrolyses. For the latter, an increase in the soluble protein content of 109% was noted after 30 min.
CONCLUSION
Our results demonstrate the applicability of fungal aspartic endopeptidases in the food and animal feed industry. Efficient protein hydrolysis of industrially relevant substrates such as acidic whey or animal feed proteins could be conducted by applying fungal aspartic peptidases. © 2022 Society of Chemical Industry.
Linux and Linux-based operating systems have been gaining more popularity among the general users and among developers. Many big enterprises and large companies are using Linux for servers that host their websites, some even require their developers to have knowledge about Linux OS. Even in embedded systems one can find many Linux-based OS that run them. With its increasing popularity, one can deduce the need to secure such a system that many personnel rely on, be it to protect the data that it stores or to protect the integrity of the system itself, or even to protect the availability of the services it offers. Many researchers and Linux enthusiasts have been coming up with various ways to secure Linux OS, however new vulnerabilities and new bugs are always found, by malicious attackers, with every update or change, which calls for the need of more ways to secure these systems.
This Thesis explores the possibility and feasibility of another way to secure Linux OS, specifically securing the terminal of such OS, by altering the commands of the terminal, getting in the way of attackers that have gained terminal access and delaying, giving more time for the response teams and for forensics to stop the attack, minimize the damage, restore operations, and to identify collect and store evidence of the cyber-attack. This research will discuss the advantages and disadvantages of various security measures and compare and contrast with the method suggested in this research.
This research is significant because it paints a better picture of what the state of the art of Linux and Linux-based operating systems security looks like, and it addresses the concerns of security enthusiasts, while exploring new uncharted area of security that have been looked at as a not so significant part of protecting the OSes out of concern of the various limitations and problems it entails. This research will address these concerns while exploring few ways to solve them, as well as addressing the ideal areas and situations in which the proposed method can be used, and when would such method be more of a burden than help if used.
Soiling is an important issue in the renewable energy sector since it can result in significant yield losses, especially in regions with higher pollution or dust levels. To mitigate the impact of soiling on photovoltaic (PV) plants, it is essential to regularly monitor and clean the panels, as well as develop accurate soiling predictions that can affect cleaning strategies and enhance the overall performance of PV power plants. This research focuses on the problem of soiling loss in photovoltaic power plants and the potential to improve the accuracy of soiling predictions. The study examines how soiling can affect the efficiency and productivity of the modules and how to measure and predict soiling using machine learning (ML) algorithms. The research includes analyzing real data from large-scale ground-mounted PV sites and comparing different soiling measurement methods. It was observed that there were some deviations in the real soiling loss values compared to the expected values for some projects in southern Spain, thus, the main goal of this work is to develop machine learning models that could predict the soiling more accurately. The developed models have a low mean square error (MSE), indicating the accuracy and suitability of the models to predict the soiling rates. The study also investigates the impact of different cleaning strategies on the performance of PV power plants and provides a powerful application to predict both the soiling and the number of cleaning cycles.
Femtosecond (fs) time-resolved magneto-optics is applied to investigate laser-excited ultrafast dynamics of one-dimensional nickel gratings on fused silica and silicon substrates for a wide range of periodicities Λ = 400–1500 nm. Multiple surface acoustic modes with frequencies up to a few tens of GHz are generated. Nanoscale acoustic wavelengths Λ/n have been identified as nth-spatial harmonics of Rayleigh surface acoustic wave (SAW) and surface skimming longitudinal wave (SSLW), with acoustic frequencies and lifetimes being in agreement with theoretical calculations. Resonant magnetoelastic excitation of the ferromagnetic resonance (FMR) by SAW’s third spatial harmonic, and, most interestingly fingerprints of the parametric resonance at 1/2 SAW frequency have been observed. Numerical solutions of Landau–Lifshitz–Gilbert (LLG) equation magnetoelastically driven by complex polychromatic acoustic fields quantitatively reproduce all resonances at once. Thus, our results provide a solid experimental and theoretical base for a quantitative understanding of ultrafast fs-laser-driven magnetoacoustics and tailoring the magnetic-grating-based metasurfaces at the nanoscale.
AI-based Ground Penetrating Radar Signal Processing for Thickness Estimation of Subsurface Layers
(2023)
This thesis focuses on the estimation of subsurface layer thickness using Ground Penetrating Radar (GPR) A-scan and B-scan data through the application of neural networks. The objective is to develop accurate models capable of estimating the thickness of up to two subsurface layers.
Two different approaches are explored for processing the A-scan data. In the first approach, A-scans are compressed using Principal Component Analysis (PCA), and a regression feedforward neural network is employed to estimate the layers’ thicknesses. The second approach utilizes a regression one-dimensional Convolutional Neural Network (1-D CNN) for the same purpose. Comparative analysis reveals that the second approach yields superior results in terms of accuracy.
Subsequently, the proposed 1-D CNN architecture is adapted and evaluated for Step Frequency Continuous Wave (SFCW) radar, expanding its applicability to this type of radar system. The effectiveness of the proposed network in estimating subsurface layer thickness for SFCW radar is demonstrated.
Furthermore, the thesis investigates the utilization of GPR B-scan images as input data for subsurface layer thickness estimation. A regression CNN is employed for this purpose, although the results achieved are not as promising as those obtained with the 1-D CNN using A-scan data. This disparity is attributed to the limited availability of B-scan data, as B-scan generation is a resource-intensive process.
Linear acceleration is a key performance determinant and major training component of many sports. Although extensive research about lower limb kinetics and kinematics is available, consistent definitions of distinctive key body positions, the underlying mechanisms and their related movement strategies are lacking. The aim of this ‘Method and Theoretical Perspective’ article is to introduce a conceptual framework which classifies the sagittal plane ‘shin roll’ motion during accelerated sprinting. By emphasising the importance of the shin segment’s orientation in space, four distinctive key positions are presented (‘shin block’, ‘touchdown’, ‘heel lock’ and ‘propulsion pose’), which are linked by a progressive ‘shin roll’ motion during swing-stance transition. The shin’s downward tilt is driven by three different movement strategies (‘shin alignment’, ‘horizontal ankle rocker’ and ‘shin drop’). The tilt’s optimal amount and timing will contribute to a mechanically efficient acceleration via timely staggered proximal-to-distal power output. Empirical data obtained from athletes of different performance levels and sporting backgrounds are required to verify the feasibility of this concept. The framework presented here should facilitate future biomechanical analyses and may enable coaches and practitioners to develop specific training programs and feedback strategies to provide athletes with a more efficient acceleration technique.
The central purpose of this paper is to present a novel framework supporting the specification and the implementation of media streaming services using XML and Java Media Framework (JMF). It provides an integrated service development environment comprising of a streaming service model, a service specification language and several implementation and retrieval tools. Our approach is based on a clear separation of a streaming service specification, and its implementation by a distributed JMF application and can be used for different streaming paradigms, e.g. push and pull services.
The central purpose of this paper is to present a novel framework supporting the specification, the implementation and retrieval of media streaming services. It provides an integrated service development environment comprising of a streaming service model, a service specification language and several implementation and retrieval tools. Our approach is based on a clear separation of a streaming service specification, and its implementation by a distributed application and can be used for different streaming paradigms, e.g. push and pull services.
Purpose
Although start-ups have gained increasing scholarly attention, we lack sufficient understanding of their entrepreneurial strategic posture (ESP) in emerging economies. The purpose of this study is to examine the processes of ESP of new technology venture start-ups (NTVs) in an emerging market context.
Design/methodology/approach
In line with grounded theory guidelines and the inductive research traditions, the authors adopted a qualitative approach involving 42 in-depth semi-structured interviews with Ghanaian NTV entrepreneurs to gain a comprehensive analysis at the micro-level on the entrepreneurs' strategic posturing. A systematic procedure for data analysis was adopted.
Findings
From the authors' analysis of Ghanaian NTVs, the authors derived a three-stage model to elucidate the nature and process of ESP Phase 1 spotting and exploiting market opportunities, Phase II identifying initial advantages and Phase III ascertaining and responding to change.
Originality/value
The study contributes to advancing research on ESP by explicating the process through which informal ties and networks are utilised by NTVs and NTVs' founders to overcome extreme resource constraints and information vacuums in contexts of institutional voids. The authors depart from past studies in demonstrating how such ties can be harnessed in spotting and exploiting market opportunities by NTVs. On this basis, the paper makes original contributions to ESP theory and practice.
Though the basic concept of a ledger that anyone can view and verify has been around for quite some time, today’s blockchains bring much more to the table including a way to incentivize users. The coins given to the miner or validator were the first source of such incentive to make sure they fulfilled their duties. This thesis draws inspiration from other peer efforts and uses this same incentive to achieve certain goals. Primarily one where users are incentivised to discuss their opinions and find scientific or logical backing for their standpoint. While traditional chains form a consensus on a version of financial "truth", the same can be applied to ideological truths too. To achieve this, creating a modified or scaled proof of stake consensus mechanism is explored in this work. This new consensus mechanism is a Reputation Scaled - Proof of Stake. This reputation can be built over time by voting for the winning side consistently or by sticking to one’s beliefs strongly. The thesis hopes to bridge the gap in current consensus algorithms and incentivize critical reasoning.
The present document is aimed to propose a suitable thermal model for the cooling down process of a one piston air cooled reciprocating compressor. In order to achieve this, a thermographic camera is used to record the temperature of different measuring points throughout different operating conditions. This data is later analyzed, with statistical tools and graphical visualization. The thermal phenomena present in the thermal process is characterized according to the compressors' geometry. Finally, using the analysis and taking into consideration the thermal phenomena the optimal thermal model is selected. This paper belongs to a bigger project and the last step is to simulate the compressor and the accuracy of the proposed model.
Although short range wireless communication explicitly targets local and very regional applications, range continues to be an extremely important issue. The range directly depends on the so called link budget, which can be increased by the choice of modulation and coding schemes. Especially, the recent transceiver generation comes with extensive and flexible support for Software Defined Radio (SDR). The SX127x family from Semtech Corp. is a member of this device class and promises significant benefits for range, robust performance, and battery lifetime compared to competing technologies. This contribution gives a short overview into the technologies to support Long Range (LoRa ™), describes the outdoor setup at the Laboratory Embedded Systems and Communication Electronics of Offenburg University of Applied Sciences, shows detailed measurement results and discusses the strengths and weaknesses of this technology.
Social-Media-Content - Auswirkungen auf Fear of Missing Out und den Selbstwert junger Nutzer*innen
(2023)
Social-Media-Marketing ist ein wichtiger Baustein einer erfolgreichen Content-Strategie. Insbesondere jüngere Zielgruppen sind auf Social Media anzutreffen – und das oftmals über viele Stunden täglich. Neben den Vorteilen, die Social Media den Nutzer*innen bietet, gibt es aber auch Schattenseiten. Zwei negative Aspekte, die sogenannte Fear of Missing Out und ein verminderter Selbstwert, wurden im Frühjahr 2022 in einer empirischen Befragung von 1338 Personen zwischen 14 und 30 Jahren untersucht. Daneben wurden auch Daten zum grundsätzlichen Social-Media-Nutzungsverhalten erhoben. Die zentralen Erkenntnisse, die sich aus der Studie ableiten, werden in diesem Kapitel vorgestellt und mit Bezug auf ihre Relevanz für das Content-Marketing hin eingeordnet.
Investigation on Bowtie Antennas Operating at Very Low Frequencies for Ground Penetrating Radar
(2023)
The efficiency of Ground Penetrating Radar (GPR) systems significantly depends on the antenna performance as the signal has to propagate through lossy and inhomogeneous media. GPR antennas should have a low operating frequency for greater penetration depth, high gain and efficiency to increase the receiving power and should be compact and lightweight for ease of GPR surveying. In this paper, two different designs of Bowtie antennas operating at very low frequencies are proposed and analyzed.
The objective of this project is to enhance the operations of a micro-enterprise that deals with food ingredients. The emphasis is on streamlining procedures and executing effective tactics. By utilizing tools like SWOT analysis, evaluations, and strategy development, the company's strengths, weaknesses, opportunities, and threats were assessed. The company developed business-level and functional-level strategies to expedite growth and attain objectives based on the findings. Moreover, precise suggestions were given to minimize the quantity of SKUs and optimize operations. The work highlighted the significance of developing a process map for streamlining operations, boosting efficiency, and elevating customer contentment. Through the implementation of said recommendations and strategies, the company can strategically position itself for success within the highly competitive food ingredients industry.
The progress in machine learning has led to advanced deep neural networks. These networks are widely used in computer vision tasks and safety-critical applications. The automotive industry, in particular, has experienced a significant transformation with the integration of deep learning techniques and neural networks. This integration contributes to the realization of autonomous driving systems. Object detection is a crucial element in autonomous driving. It contributes to vehicular safety and operational efficiency. This technology allows vehicles to perceive and identify their surroundings. It detects objects like pedestrians, vehicles, road signs, and obstacles. Object detection has evolved from being a conceptual necessity to an integral part of advanced driver assistance systems (ADAS) and the foundation of autonomous driving technologies. These advancements enable vehicles to make real-time decisions based on their understanding of the environment, improving safety and driving experiences. However, the increasing reliance on deep neural networks for object detection and autonomous driving has brought attention to potential vulnerabilities within these systems. Recent research has highlighted the susceptibility of these systems to adversarial attacks. Adversarial attacks are well-designed inputs that exploit weaknesses in the deep learning models underlying object detection. Successful attacks can cause misclassifications and critical errors, posing a significant threat to the functionality and safety of autonomous vehicles. With the rapid development of object detection systems, the vulnerability to adversarial attacks has become a major concern. These attacks manipulate inputs to deceive the target system, significantly compromising the reliability and safety of autonomous vehicles. In this study, we focus on analyzing adversarial attacks on state-of-the-art object detection models. We create adversarial examples to test the models’ robustness. We also check if the attacks work on a different object detection model meant for similar tasks. Additionally, we extensively evaluate recent defense mechanisms to see how effective they are in protecting deep neural networks (DNNs) from adversarial attacks and provide a comprehensive overview of the most commonly used defense strategies against adversarial attacks, highlighting how they can be implemented practically in real-world situations.
Bud type carbon nanohorns (CNHs) are composed of carbon and have a closed conical tip at one end protruding from an aggregate structure. By employing a simple oxidation process in CO2 atmosphere, it is possible to open the CNH tips which increases their specific surface area by four fold. These tip opened CNHs combine the microporous nature of activated carbons and the crystalline mesoporous character of carbon nanotubes. The results for the high pressure CO2 gas adsorption of tip opened CNHs are reported herein for the first time and are found to be superior to traditional CO2 adsorbents like zeolites. The modified CNHs are also found to be promising materials for lithium ion batteries and the performance is found to be on a par with carbon nanotubes and carbon nanofibers.
Many different methods, such as screen printing, gravure, flexography, inkjet etc., have been employed to print electronic devices. Depending on the type and performance of the devices, processing is done at low or high temperature using precursor- or particle-based inks. As a result of the processing details, devices can be fabricated on flexible or non-flexible substrates, depending on their temperature stability. Furthermore, in order to reduce the operating voltage, printed devices rely on high-capacitance electrolytes rather than on dielectrics. The printing resolution and speed are two of the major challenging parameters for printed electronics. High-resolution printing produces small-size printed devices and high-integration densities with minimum materials consumption. However, most printing methods have resolutions between 20 and 50 μm. Printing resolutions close to 1 μm have also been achieved with optimized process conditions and better printing technology.
The final physical dimensions of the devices pose severe limitations on their performance. For example, the channel lengths being of this dimension affect the operating frequency of the thin-film transistors (TFTs), which is inversely proportional to the square of channel length. Consequently, short channels are favorable not only for high-frequency applications but also for high-density integration. The need to reduce this dimension to substantially smaller sizes than those possible with today’s printers can be fulfilled either by developing alternative printing or stamping techniques, or alternative transistor geometries. The development of a polymer pen lithography technique allows scaling up parallel printing of a large number of devices in one step, including the successive printing of different materials. The introduction of an alternative transistor geometry, namely the vertical Field Effect Transistor (vFET), is based on the idea to use the film thickness as the channel length, instead of the lateral dimensions of the printed structure, thus reducing the channel length by orders of magnitude. The improvements in printing technologies and the possibilities offered by nanotechnological approaches can result in unprecedented opportunities for the Internet of Things (IoT) and many other applications. The vision of printing functional materials, and not only colors as in conventional paper printing, is attractive to many researchers and industries because of the added opportunities when using flexible substrates such as polymers and textiles. Additionally, the reduction of costs opens new markets. The range of processing techniques covers laterally-structured and large-area printing technologies, thermal, laser and UV-annealing, as well as bonding techniques, etc. Materials, such as conducting, semiconducting, dielectric and sensing materials, rigid and flexible substrates, protective coating, organic, inorganic and polymeric substances, energy conversion and energy storage materials constitute an enormous challenge in their integration into complex devices.
This paper presents a system that uses a multi-stage AI analysis method for determining the condition and status of bicycle paths using machine learning methods. The approach for analyzing bicycle paths includes three stages of analysis: detection of the road surface, investigation of the condition of the bicycle paths, and identification of substrate characteristics. In this study, we focus on the first stage of the analysis. This approach employs a low-threshold data collection method using smartphone-generated video data for image recognition, in order to automatically capture and classify surface condition and status.
For the analysis convolutional neural networks (CNN) are employed. CNNs have proven to be effective in image recognition tasks and are particularly well-suited for analyzing the surface condition of bicycle paths, as they can identify patterns and features in images. By training the CNN on a large dataset of images with known surface conditions, the network can learn to identify common features and patterns and reliably classify them.
The results of the analysis are then displayed on digital maps and can be utilized in areas such as bicycle logistics, route planning, and maintenance. This can improve safety and comfort for cyclists while promoting cycling as a mode of transportation. It can also assist authorities in maintaining and optimizing bicycle paths, leading to more sustainable and efficient transportation system.
Synthesizing voice with the help of machine learning techniques has made rapid progress over the last years. Given the current increase in using conferencing tools for online teaching, we question just how easy (i.e. needed data, hardware, skill set) it would be to create a convincing voice fake. We analyse how much training data a participant (e.g. a student) would actually need to fake another participants voice (e.g. a professor). We provide an analysis of the existing state of the art in creating voice deep fakes and align the identified as well as our own optimization techniques in the context of two different voice data sets. A user study with more than 100 participants shows how difficult it is to identify real and fake voice (on avg. only 37% can recognize a professor’s fake voice). From a longer-term societal perspective such voice deep fakes may lead to a disbelief by default.
Schluckspecht project
(2022)
In this paper, the J-integral is derived for temperature-dependent elastic–plastic materials described by incremental plasticity. It is implemented using the equivalent domain integral method for assessment of three-dimensional cracks based on results of finite-element calculations. The J-integral considers contributions from inhomogeneous temperature fields and temperature-dependent elastic and plastic material properties as well as from gradients in the plastic strains and the hardening variables. Different energy densities are considered, the Helmholtz free energy and the stress-working density, providing a physical meaning of the J-integral as a fracture criteria for crack growth. Results obtained for a plate with two different crack configurations each loaded by a cool-down thermal shock show domain-independence of the incremental J-integral for different energy densities even for high temperature gradients and significant temperature-dependence of the yield stress and the hardening exponent in the presence of large scale yielding. Hence, the derived J-integral is an appropriate parameter for the assessment of cracks in thermomechanically loaded components.
Zur ergonomischen Unterstützung von Industriearbeitern werden zunehmend Exoskelette eingesetzt. Studien über die Wirkung und den Einfluss von Exoskeletten auf den Körper sind jedoch rar. Diese Arbeit beschäftigt sich daher mit der Wirkung des Rückenexoskeletts BionicBack des deutschen Exoskelett Herstellers hTRIUS auf die Wirbelsäulenkrümmung bei industriellen Hebearbeiten. Im Speziellen wird die Wirbelsäulenkrümmung beim Umpalettieren aus drei verschiedenen Hebehöhen (91 cm, 59 cm, 15 cm) mit Hilfe eines markerbasierten 3D Motion Capture Systems untersucht. Um den Versuchsaufbau alltagsnah und realistisch zu gestalten, wurde diese Pilotstudie in Kooperation mit der Firma Zehnder am Standort Lahr durchgeführt, die sowohl die Probanden als auch den Versuchsaufbau zur Verfügung stellte. Vier gesunde männliche Probanden mit einem durchschnittlichen Alter von 39,5 Jahren (SD = 6,5), einem durchschnittlichen Körpergewicht von 72,75 kg (SD = 7,1) und einer durchschnittlichen Körpergröße von 175 cm (SD = 2,6) wurden in zwei Schichten eingeteilt. Mit den Probanden wurden vor und nach der Schicht sowie an zwei aufeinander folgenden Tagen Messungen durchgeführt, wobei an einem Tag das BionicBack während der Arbeit und der Messung getragen wurde und am an-deren Tag nicht. Während einer Messung nahmen die Testpersonen ein Paket mit einem Gewicht von 21,1 kg dreimal von jeder Hebehöhe von einer Palette auf und legten es auf einer anderen ab. Anschließend wurde die Krümmung der Wirbelsäule am tiefsten Punkt der Hebebewegung untersucht, wobei die Gesamtkrümmung in dieser Position durch die Addition von drei repräsentativen Segmentwinkeln dargestellt wird. Die Abweichung dieser Gesamtkrümmungen in der tiefsten Beugeposition von der individuellen neutralen Wirbelsäulenstellung der Probanden im Stehen ergeben die Werte, die zwischen den einzelnen Versuchsbedingungen verglichen werden. Die Ergebnisse zeigen, dass das BionicBack den Abstand zur Neutralstellung bzw. die Gesamtkrümmung des Rückens im Vergleich zu ohne BionicBack bis zu -11,5° (Median: -11,5° (SD = 5,2); Mittelwert: -8,4° (SD = 6,4)) entsprechend -30% vor der Schicht und bis zu -5,6° (Median: -5,6° (SD = 3,5); Mittelwert: -4,1° (SD = 5,4)) ent-sprechend -17% nach der Schicht reduzieren kann. Die Betrachtung der einzelnen Segmentwinkel zeigt, dass die Reduzierung des Abstandes von der Neutralstellung hauptsächlich im Lendenwirbelbereich stattfindet. Der Vergleich der Wirbelsäulen-krümmung vor und nach der Schicht ohne BionicBack zeigt, dass die Wirbelsäulen-krümmung nach der Schicht, mit Ausnahme der tiefsten Hebehöhe, eine größere Abweichung von der Neutralstellung aufweist als vor der Schicht. Der Vergleich mit BionicBack zeigt, dass die Wirbelsäulenkrümmung nach der Schicht mit Ausnahme der niedrigsten Hubhöhe nicht bzw. weniger von der Neutralstellung abweicht als vor der Schicht. Aufgrund der Ergebnisse wird vermutet, dass das BionicBack durch die Unterstützung einer neutraleren Rückenhaltung das Verletzungsrisiko reduzieren kann. Des Weiteren wird vermutet, dass die Muskelermüdung während einer Arbeitsschicht einen Einfluss auf die Wirbelsäulenkrümmung beim Heben hat. Es wird angenommen, dass dieser Einfluss durch das BionicBack reduziert werden kann. Allerdings dürfen die Grenzen dieser Pilotstudie nicht außer Acht gelassen werden. Sei es die Anzahl der Versuchspersonen, die keine Aussage über die Allgemeingültigkeit zu-lässt und keine effektive statistische Analyse erlaubt, oder systematische Fehler, die aufgrund der Modellvereinfachung und der Methodik auftreten können. Weitere Untersuchungen sind erforderlich, um die Ergebnisse zu validieren. Diese Arbeit soll die Grundlage für weitere Studien mit einer weiterentwickelten Methodik und einer größeren Anzahl von Probanden bilden.
In dieser Abschlussarbeit wurden die vorgenommen Ziele seitens der Projektaufgabe im Rahmen der Bachelor-Thesis erfüllt. Hierbei wurde der Ist-Zustand des UniAuSter´s aufgenommen und technisch hinterfragt. Zusätzlich wurden die Grenzen der mechanischen Lösung aufgezeigt und mögliche Ursachen erläutert.
Des Weiteren konnten auf Grundlage der Berechnungen die Taktzeiten bestimmt und daraufhin über die Recherche eine Auswahl des Magnetventils getroffen werden, welches den zuvor ermittelten Anforderungen entspricht. Diese sind zum einen die einfache Anpassung der Taktgeschwindigkeit über eine Maschinensteuerung und die Möglichkeit, bis zu 30.000 Flaschen pro Stunde auszuschleusen.
Der vorgegebene maximale Bauraum, wurde trotz zusätzlich erforderlichen Komponenten nicht überschritten. Hierbei wurden Lösungen in der elektrischen sowie der pneumatischen Versorgung entwickelt. Weiterführend kann durch den Ringverteiler eine optimale Druckluftversorgung durch den integrierten Druckregler realisiert werden, Er ist durch seine Konstruktionsweise für die Anlage kein Störfaktor, sondern dient zusätzlich als Verschlauchungsführung.
Für den weiteren Verlauf des Projekts werden die konstruierten Komponenten weiter ausgearbeitet und die noch nicht vorhandenen technischen Zeichnungen erstellt . Zusätzlich wird eine endgültige Lösung für die Signalverarbeitung der Magnetventile über eine elektrische Drehdurchführung entwickelt. Um die gesamte Konstruktion auf ihre Funktion prüfen zu können, wird von der Hochschule Offenburg zusammen mit dem Projektpartner Kematec, ein Prototyp in naher Zukunft erstellt.
Das duale Krankenversicherungssystem, mit der Gesetzlichen und Privaten Krankenversicherung (GKV und PKV), ist sehr heterogen, und beide agieren in einem unterschiedlichen komplexen rechtlichen und strukturellen Rahmen. In der GKV sind rund 90 % der Bevölkerung versichert. Der folgende Beitrag zum Kundenmanagement in Krankenversicherungen fokussiert daher die GKV. Viele Maßnahmen des Kundenmanagements, insbesondere bezüglich der Services, haben jedoch trotz der unterschiedlichen Rahmenbedingungen sowohl in der GKV als auch in der PKV Relevanz und werden von Marktteilnehmern beider Systeme ergriffen.
Die direkte Vermarktung von Strom aus Wind und Sonne stellt einen wichtigen Schritt der Energiewende dar. Einerseits kann durch die Marktintegration die Unabhängigkeit von EEG-Subventionen gelingen. Andererseits wird über diese Mechanismen die Stromerzeugung an der Nachfrage orientiert, wodurch zur Stabilität des Stromnetzes beigetragen wird. Ein Beispiel dafür ist die lokale Vermarktung von PV-Strom in einem Mietshaus. Für deren Umsetzung benötigen die Akteure ein Mess- und Steuerungssystem, dass vor Ort Zähler- und Anlagendaten erfasst und die Abrechnung der Mieter vereinfacht. Außerdem sollte es Kennwerte wie beispielsweise den PV-Anteil berechnen und gegebenenfalls ein Blockheizkraftwerk steuern. Weder die Zählersysteme der Messstellenbetreiber noch die Steuerungssysteme von PV- oder Blockheizkraftwerken erfüllen diese Anforderungen ausreichend. In der Forschung ist man währenddessen bereits einen Schritt weiter und arbeitet an technischen Systemen, die für wesentlich komplexere Energiesystem- und Markttopologien ausgelegt werden. In dieser Arbeit werden die neuen technischen Anforderungen der Direktvermarktung in einem Mietshaus identifiziert und mit dem Stand aktueller Marktprodukte sowie dem System »OpenMUC« aus der Forschung verglichen.
Der Heel-Rise Test (HRT) wird in der Klinik und der Therapie benutzt, um die Funktionsfähigkeit der Wadenmuskulatur einzuschätzen. Eine Orientierung am Normwert von 25 Wiederholungen hilft dabei, die Muskulatur als normal oder anormal einzustufen. Dieser Wert beruht jedoch auf eine älteren und nicht mehr zeitgemäßen Studie. Auch ist fraglich, ob der absolut erreichte Wert eines HRTs eine direkte Aussage über die Funktionsfähigkeit der Plantarflexoren geben kann.
Das Ziel dieser Arbeit ist somit den HRT mit einer Maximalkraftmessung auf dem Isokineten zu vergleichen und diese auf einen möglichen Zusammenhang zu prüfen. Dazu kann folgende Forschungsfrage aufgestellt werden: „Können die Messergebnisse des HRT eine positive Korrelation mit einer Maximalkraftmessung am Isokineten eingehen?“
Für die Beantwortung der Forschungsfrage ist eine quantitative Untersuchung der beidseitigen Wadenkraft von 20 jungen und gesunden Teilnehmer*innen durchgeführt worden. Dabei wurde das Bein, mit dem die Kraftuntersuchung beginnt, randomisiert. Da ein linearer Zusammenhang zwischen den HRT-Messwerten und einer Maximalkraftmessung auf dem Isokineten vermutet wird, wird dieser durch eine Korrelationsanalyse nach Bravais-Pearson geprüft.
Der Vergleich der Kraftmessungen zeigt, dass die HRT-Ergebnisse eine moderate bis hohe positive Korrelation mit den Maximalkraftwerten auf dem Isokineten eingehen. Dabei hat die Beindominanz sowie die Testreihenfolge der Beine keinen großen Einfluss auf die Ergebnisse. Untersucht man Männer und Frauen getrennt, hebt sich jedoch die positive Korrelation auf und es kann ein geringer, bis kein Zusammenhang zwischen dem HRT und der Maximalkraft auf dem Isokineten festgestellt werden. Zudem ist zu erkennen, dass Männer in allen Kraftuntersuchungen höhere Kraftergebnisse erzielt haben. Da die Stichprobe nur junge, gesunde und aktive Menschen umfasst, sind Aussagen über erkrankte Personen, ältere Menschen oder den Einfluss der Leistungsfähigkeit nicht möglich.
Durch die positive Korrelation des HRT mit dem Goldstandard der Kraftdiagnostik, der Isokinetitk, scheint die Kritik am HRT entkräftet zu werden. Jedoch sind die Ergebnisse mit Vorsicht zu betrachten, da sich bei Betrachtung des Geschlechts die positive Korrelation aufhebt. Das Ergebnis der Arbeit soll, im Anbetracht der Limitation, trotzdem ermutigen, den HRT weiterhin für die Kraftdiagnostik der Wadenmuskulatur zu nutzen. Die eingeschränkte Stichprobengröße, eine fehlende Standardisierung der HRT-Durchführung, sowie die vielen Auswahlwahlmöglichkeiten in der Isokinetik machen es kompliziert die Ergebnisse dieser Arbeit auf andere Personengruppen oder Messmethoden zu übertragen. Dennoch gibt die Untersuchung einen ersten Einblick und ermöglicht die Aussagekraft des HRT zu stützen und somit seine Bedeutung und Qualität für die Kraftdiagnostik zu verbessern.
Die Bachelorarbeit beschäftigt sich mit der künstlerischen Selbstvermarktung im Neuzeitalter. Am Beispiel eines selbst produzierten Songs und dessen Selbstvermarktung analysiert und bewertet die Arbeit, ob Social Media jungen Künstler*innen mehr Erfolgschancen bieten kann und bildet einen Leitfaden für selbstvermarktende Musiker*innen.
Dabei wird auch die sich weiterentwickelnde Digitalisierung aufgegriffen, die Künstler*innen neue Vermarktungsmöglichkeiten gebracht hat. Die klassischen Major Labels, die Säulen der Musikindustrie, werden zusammenfassend vorgestellt.
Der Selbstvermarktungsweg wird in dieser Arbeit in folgende Ebenen aufgeteilt: On- und offline Kommunikationspolitik, Produktpolitik sowie Preis- und Distributionspolitik. Anhand der praktischen Umsetzung des selbst produzierten Songs, werden die erwähnten Vermarktungsmöglichkeiten nach Funktionalität getestet und im abschließenden Fazit ausgewertet.
A new RFID/NFC (ISO 15693 standard) based inductively powered passive SoC (System on chip) for biomedical applications is presented here. The proposed SOC consists of an integrated 32 bit microcontroller, RFID/NFC frontend, sensor interface circuit, analog to digital converter and some peripherals such as timer, SPI interface and memory devices. An energy harvesting unit supplies the power required for the entire system for complete passive operation. The complete chip is realized on CMOS 0.18 μm technology with a chip area of 1.5 mm × 3.0 mm.
In this paper, a complete passive transponder device has been discussed which is meant to monitor leakage in silicone breast implants. The passive tag operates in the HF frequency range of 13.56MHz using RFID ISO 15693 standard. The complete system consists of the transponder, reader and a PC. This paper focusses on the development of such a state of the art passive RFID transponder to monitor the wellness of the silicone breast implants periodically in order to detect leakage in the same. Keyword: RFID (Radio frequency identification device), EM (Electromagnetic) field, Passive Transponder, Silicone breast implants.
Die Musik-, Kunst- und Kulturszene ist vielfältig und lebt von Individualität. An der Diskussionsrunde zum Thema „Überlebensstrategien während der Pandemie“ nehmen die Musiker*innen Lindy Huppertsberg, Pat Appleton, Martin Verdonk, Tommy Baldu und Markus Birkle am 10.05.2021 teil. Die Teilnehmer*innen der Diskussionsrunde erwirtschaften ihr Einkommen primär über Konzertgagen und sind als freischaffende Musiker*innen etabliert und erfolgreich in der Musikwelt tätig. Trotz großer Übereinstimmungen werden Strategien während der Krise bemerkenswert individuell gewählt. Ebenso vielschichtig ist der Fokus bei der Karriereplanung und Auswahl der musikalischen Projekte. Zwei essenzielle Themenbereiche kristallisieren sich im Verlauf der Unterhaltung heraus: Zum einen die persönlichen singulären Strategien für ein wirtschaftliches Überleben, zum anderen die Auseinandersetzung mit dem Verlust der Möglichkeit auf Resonanz und Empathie mit Mitmusiker*innen und dem Publikum. Die Frage wird aufgeworfen, ob Kulturschaffende einer Gesellschaft eine emotionale Stimme geben.
Das Ziel der vorliegenden Bachelorarbeit ist die Implementierung und Verbesserung der nichtmodellbasierten und pixelweisen Kalibrierung von Industriekameras in MATLAB. Hierfür wird eine homogene Helligkeitsregulierung zwischen Monitor und Kamera mittels Randfindung, Einstellen der Belichtungszeit und Regulierung der Monitorgrauwerte entwickelt, um systembasierte Fehler der Kamera wie die Vignettierung ausgleichen zu können. In mehreren Versuchen wird die Implementierung validiert. Im Rahmen der Bachelorarbeit wird herausgefunden, dass die homogene Helligkeitsregelung die Ergebnisse in einer orthogonalen Positionierung zum Monitor nicht wesentlich verändert. Vor allem aber wird die Kalibrierung bei größeren Winkeln robuster. Neben der Implementierung wird eine Benutzeroberfläche eingebunden, die auch Anwenderfehler in Bezug auf die Linearführungsschiene verhindern soll.
In thin-layer chromatography, fiber-bundle arrays have been introduced for spectral absorption measurements in the UV-region. Using all-silica fiber bundles, the exciting light will be detected after re-emission on the plate with a fiberoptic spectrometer. In addition, fluorescence light can be detected which will be masked by the re-emitted light. Therefore, it is helpful to separate the absorption and fluorescence on the TLC-plate. A modified three-array assembly has been developed: using one array for detection, the two others are used for excitation with broadband band deuterium-light and with UV-LEDs adjusted to the substances under test. As an example, the quantification of glucosamine in nutritional supplements or spinach leaf extract will be described. Using simply heating of the amino-plate for derivation, the reaction product of Glucosamine can be detected sensitively either by light absorption or by fluorescence, using the new fiber-optic assembly. In addition, the properties of the new 3-row fiber-optic array and the commercially available UV-LEDs will be shown, in the interesting wavelength region for excitation of fluorescence, from 260 nm to 360 nm. The squint angle having an influence on coupling efficiency and spatial resolution will be measured with the inverse farfield method. Some properties of UV-LEDs for analytical applications will be described and discussed, too.
Background
To assess the in-field walking mechanics during downhill hiking of patients with total knee arthroplasty five to 14 months after surgery and an age-matched healthy control group and relate them to the knee flexor and extensor muscle strength.
Methods
Participants walked on a predetermined hiking trail at a self-selected, comfortable pace wearing an inertial sensor system for recording the whole-body 3D kinematics. Sagittal plane hip, knee, and ankle joint angles were evaluated over the gait cycle at level walking and two different negative slopes. The concentric and eccentric lower extremity muscle strength of the knee flexors and extensors isokinetically at 50 and 120°/s were measured.
Findings
Less knee flexion angles during stance have been measured in patients in the operated limb compared to healthy controls in all conditions (level walking, moderate downhill, steep downhill). The differences increased with steepness. Muscle strength was lower in patients for both muscle groups and all measured conditions. The functional hamstrings to quadriceps ratio at 120°/sec correlated with knee angle during level and downhill walking at the moderate slope in patients, showing higher ratios with lower peak knee flexion angles.
Interpretation
The study shows that even if rehabilitation has been completed successfully and complication-free, five to 14 months after surgery, the muscular condition was still insufficient to display a normal gait pattern during downhill hiking. The muscle balance between quadriceps and hamstring muscles seems related to the persistence of a stiff knee gait pattern after knee arthroplasty. LoE: III.
Als Bachelorarbeit wurde ein Drehbuch ausgearbeitet. Hierbei handelt es sich um die Pilotfolge einer selbst konzipierten Serie.
Kurzzusammenfassung:
Anna, Tess, Felix und Vincent sind in ihren Zwanzigern und treten alle zur gleichen Zeit in einem Unternehmen ihre erste Stelle an. Neben den Unsicherheiten und Problemen, die mit einer neuen Stelle auftreten, müssen sich die vier auch mit ihren privaten Konflikten auseinandersetzen.
Viralität auf TikTok
(2023)
Die Social Media Plattform TikTok erfreut sich spätestens seit der Corona-Pandemie einer immer größer werdenden Gemeinschaft. Mittlerweile verfügt die App über mehr als 20 Millionen Nutzer:innen - alleine in Deutschland. Virale Videos sprießen förmlich aus dem Boden. Diese Masterarbeit beschäftig sich mit der Frage, welche Faktoren der Viralität zu Grunde liegen und ob man die Viralität maßgeblich beeinflussen kann. Dies erfolgt mittels theoretischer Grundlagen, einer quantitativen Nutzerumfrage und Experteninterivews mit erfolgreichen deutschen Creatorn. Abschließend werden Videos für TikTok konzipiert und analysiert.