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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.
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.
When people with hearing loss are provided with different devices in each ear, these devices usually have different processing latencies. This leads to static temporal offsets between both ears in the order of several milliseconds. This thesis measured effects of such offsets in stimulation timing on mechanisms of binaural hearing, such as sound localization and speech understanding in noise in hearing-impaired and normal-hearing listeners.
Total Cost of Ownership (TCO) is a key tool to have a complete understanding of the costs associated with an investment, as it allows to analyze not only the initial acquisition costs, but also the long-term costs related to operation, maintenance, depreciation, and other factors. In the context of the cement industry, TCO is especially important due to the complexity of the production processes and the wide variety of components and machinery involved in the process.
For this reason, a TCO analysis for the cement industry has been conducted in this study, with the objective of showing the different components of the cost of production. This analysis will allow the reader to gain knowledge about these costs, in the industrial model will be to make informed decisions on the adoption of technologies and practices that will allow them to reduce costs in the long run and improve their operational efficiency.
In particular, this study pursues to give visibility to technologies and practices that enable the reduction of carbon emissions in cement production, thus contributing to the sustainability of industry and the protection of the environment. By being at the forefront of sustainability issues, the cement industry can contribute to the achievement of environmentally friendly technologies and enable the development of people and industry.
The Oxyfuel technology has been selected as a carbon capture solution for the cement industry due to its practical application, low costs, and practical adaptation to non-capture processes. The adoption of this technology allows for a significant reduction in CO2 emissions, which is a crucial factor in achieving sustainability in the cement manufacturing process.
Carbon capture storage technologies represent a high investment, although these technologies increase the cost of production, the application of Oxyfuel technology is one of the most economically viable as the cheapest technology per capture according to the comparison. However, this price increase is a technical advantage as the carbon capture efficiency of this technology reaches 90%. This level of efficiency leads to a decrease in taxes for the generation of CO2 emissions, making the cement manufacturing process sustainable.
A balcony photovoltaic (PV) system, also known as a micro-PV system, is a small PV system consisting of one or two solar modules with an output of 100–600 Wp and a corresponding inverter that uses standard plugs to feed the renewable energy into the house grid. In the present study we demonstrate the integration of a commercial lithium-ion battery into a commercial micro-PV system. We firstly show simulations over one year with one second time resolution which we use to assess the influence of battery and PV size on self-consumption, self-sufficiency and the annual cost savings. We then develop and operate experimental setups using two different architectures for integrating the battery into the micro-PV system. In the passive hybrid architecture, the battery is in parallel electrical connection to the PV module. In the active hybrid architecture, an additional DC-DC converter is used. Both architectures include measures to avoid maximum power point tracking of the battery by the module inverter. Resulting PV/battery/inverter systems with 300 Wp PV and 555 Wh battery were tested in continuous operation over three days under real solar irradiance conditions. Both architectures were able to maintain stable operation and demonstrate the shift of PV energy from the day into the night. System efficiencies were observed comparable to a reference system without battery. This study therefore demonstrates the feasibility of both active and passive coupling architectures.
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.
Go ist eine 2009 veröffentlichte Programmiersprache mit einem statischen Typsystem. Seit Version 1.18 sind auch Generics ein Teil der Sprache. Deren Übersetzung wurde im de facto Standard-Compiler mittels Monomorphisierung umgesetzt. Diese bringt neben einigen Vorteilen auch Nachteile mit sich. Aus diesem Grund beschäftigt sich diese Arbeit mit einer alternativen Übersetzungsstrategie für Generics in Go und implementiert diese in einem neuen Compiler für Featherweight Generic Go, einem Subset von Go. Zum Schluss steht damit ein nahezu funktionierender Compiler, welcher schließlich Racket-Code ausgibt. Eine Evaluierung der Performanz der Übersetzungsstrategie ist allerdings noch ausstehend.
The accurate diagnosis of state of charge (SOC) and state of health (SOH) is of utmost importance for battery users and for battery manufacturers. State diagnosis is commonly based on measuring battery current and using it in Coulomb counters or as input for a current-controlled model. Here we introduce a new algorithm based on measuring battery voltage and using it as input for a voltage-controlled model. We demonstrate the algorithm using fresh and pre-aged lithium-ion battery single cells operated under well-defined laboratory conditions on full cycles, shallow cycles, and a dynamic battery electric vehicle load profile. We show that both SOC and SOH are accurately estimated using a simple equivalent circuit model. The new algorithm is self-calibrating, is robust with respect to cell aging, allows to estimate SOH from arbitrary load profiles, and is numerically simpler than state-of-the-art model-based methods.
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.
This paper has the objective of creating a framework for a different cultural dimension of corporate entrepreneurship leading to corporate entrepreneurial culture (CEC). The analysis of CEC is based on a review of existing concepts of organisational culture and entrepreneurship. They are combined to create a framework of CEC, including macro- and microlevels and examples of subcultures. Core ideas of the framework are validated by qualitative interviews with ten experts. The identified organisational category of the CEC framework is defined by the levels of micro-cultures or subcultures and includes the upper levels of the hierarchy, including the industry level. Geographic categories such as regional or national culture are also part of the system. The individual category of the CEC framework is characterised by competencies (including aspects such as motivation, creativity, mobilising others, coping with uncertainty, teamwork and social competencies) and entrepreneurial personalities. The results of the interviews show the importance of these individual competencies for a lively CEC. The different levels, such as national and professional cultures, as a dimension of the organisational category of the framework are also confirmed by the interviews. The findings indicate that the individual category of CEC could be used for job satisfaction or engagement and the degree of CEC of an organisation could be defined and developed by the organisational category. The identified framework contributes to an understanding of this complex topic and supports companies in the implementation of entrepreneurial ideas in different organisational contexts.
Lithium-ion batteries show strongly nonlinear behaviour regarding the battery current and state of charge. Therefore, the modelling of lithium-ion batteries is complex. Combining physical and data-driven models in a grey-box model can simplify the modelling. Our focus is on using neural networks, especially neural ordinary differential equations, for grey-box modelling of lithium-ion batteries. A simple equivalent circuit model serves as a basis for the grey-box model. Unknown parameters and dependencies are then replaced by learnable parameters and neural networks. We use experimental full-cycle data and data from pulse tests of a lithium iron phosphate cell to train the model. Finally, we test the model against two dynamic load profiles: one consisting of half cycles and one dynamic load profile representing a home-storage system. The dynamic response of the battery is well captured by the model.
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.
In this paper, we study the runtime performance of symmetric cryptographic algorithms on an embedded ARM Cortex-M4 platform. Symmetric cryptographic algorithms can serve to protect the integrity and optionally, if supported by the algorithm, the confidentiality of data. A broad range of well-established algorithms exists, where the different algorithms typically have different properties and come with different computational complexity. On deeply embedded systems, the overhead imposed by cryptographic operations may be significant. We execute the algorithms AES-GCM, ChaCha20-Poly1305, HMAC-SHA256, KMAC, and SipHash on an STM32 embedded microcontroller and benchmark the execution times of the algorithms as a function of the input lengths.
The contribution of the RoofKIT student team to the SDE 21/22 competition is the extension of an existing café in Wuppertal, Germany, to create new functions and living space for the building with simultaneous energetic upgrading. A demonstration unit is built representing a small cut-out of this extension. The developed energy concept was thoroughly simulated by the student team in seminars using Modelica. The system uses mainly solar energy via PVT collectors as the heat source for a brine-water heat pump (space heating and hot water). Energy storage (thermal and electrical) is installed to decouple generation and consumption. Simulation results confirm that carbon neutrality is achieved for the building operation, consuming and generating around 60 kWh/m2a.
Due to its performance, the field of deep learning has gained a lot of attention, with neural networks succeeding in areas like Computer Vision (CV), Neural Language Processing (NLP), and Reinforcement Learning (RL). However, high accuracy comes at a computational cost as larger networks require longer training time and no longer fit onto a single GPU. To reduce training costs, researchers are looking into the dynamics of different optimizers, in order to find ways to make training more efficient. Resource requirements can be limited by reducing model size during training or designing more efficient models that improve accuracy without increasing network size.
This thesis combines eigenvalue computation and high-dimensional loss surface visualization to study different optimizers and deep neural network models. Eigenvectors of different eigenvalues are computed, and the loss landscape and optimizer trajectory are projected onto the plane spanned by those eigenvectors. A new parallelization method for the stochastic Lanczos method is introduced, resulting in faster computation and thus enabling high-resolution videos of the trajectory and secondorder information during neural network training. Additionally, the thesis presents the loss landscape between two minima along with the eigenvalue density spectrum at intermediate points for the first time.
Secondly, this thesis presents a regularization method for Generative Adversarial Networks (GANs) that uses second-order information. The gradient during training is modified by subtracting the eigenvector direction of the biggest eigenvalue, preventing the network from falling into the steepest minima and avoiding mode collapse. The thesis also shows the full eigenvalue density spectra of GANs during training.
Thirdly, this thesis introduces ProxSGD, a proximal algorithm for neural network training that guarantees convergence to a stationary point and unifies multiple popular optimizers. Proximal gradients are used to find a closed-form solution to the problem of training neural networks with smooth and non-smooth regularizations, resulting in better sparsity and more efficient optimization. Experiments show that ProxSGD can find sparser networks while reaching the same accuracy as popular optimizers.
Lastly, this thesis unifies sparsity and neural architecture search (NAS) through the framework of group sparsity. Group sparsity is achieved through ℓ2,1-regularization during training, allowing for filter and operation pruning to reduce model size with minimal sacrifice in accuracy. By grouping multiple operations together, group sparsity can be used for NAS as well. This approach is shown to be more robust while still achieving competitive accuracies compared to state-of-the-art methods
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.
Alexander von Humboldt, a German scientist and explorer of the 19th century, viewed the natural world holistically and described the harmony of nature among the diversity of the physical world as a conjoining between all physical disciplines. He noted in his diary: “Everything is interconnectedness.”
The main feature of Humboldt’s pioneering work was later named “Humboldtian science”, meaning the accurate study of interconnected real phenomena in order to find a definite law and a dynamic cause.
Following Humboldt's idea of nature, an Internet edition of his works must preserve the author’s original intention, retain an awareness of all relevant works, and still adhere to the requirements of scholarly edition.
At the present time, however, the highly unconventional form of his publications has undermined the awareness and a comprehensive study of Humboldt’s works.
Digital libraries should supply dynamic links to sources, maps, images, graphs and relevant texts. New forms of interaction and synthesis between humanistic texts and scientific observation need to be created.
Information technology is the only way to do justice to the broad range of visions, descriptions and the idea of nature of Humboldt’s legacy. It finally leads to virtual research environments as an adequate concept to redesign our digital archives, not only for Humboldt’s documents, but for all interconnected data.
The Humboldt Portal has been designed and implemented as part of an ongoing research project to develop an information system on the Internet to share the documents and rare books of Alexander von Humboldt, a 19th century German scientist and explorer, who viewed the natural world holistically and described the harmony of nature among the diversity of the physical world. Even after more than two centuries he is admired for his ability to see the natural world and human nature in the context of a complex network of relationships. The design and implementation of the Humboldt Portal are also oriented to support further research on Humboldt’s intellectual perspective.
Although all of Humboldt's works can be found on the internet as digitized documents, the complexity and internal inter-connectivity of his vision of nature cannot be adequately represented only by digitized papers or scanned documents in digital libraries.
As a consequence a specific portal of the Humboldt's documents was developed, which extends the standards of digital libraries and offers a technical approach for the adequate presentation of highly interconnected data.
Due to the continuous scientific and literary research, new insights and requirements for the digital presentation of Humboldt documents are constantly emerging, so that this article only provides a summary of the concepts realized at now. Consequently, the design and implementation of the Humboldt Portal is both: a consequence of a continuing research project and oriented to support more research on Humboldt´s intellectual holistic perspective, which was an anticipation to the System Approach of the last Century.