Offenburg University of Applied Sciences
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Numerische Untersuchung von Hohlproben unter Wasserstoffeinfluss
No full textDie Hohlprobentechnik soll als Alternative zur Autoklavtechnik eingesetzt werden,
um Werkstoffe unter Druckwasserstoffeinfluss charakterisieren zu können. Daher
wird in dieser Arbeit die Hohlprobengeometrie unter LCF-Belastung mit Hilfe
der Finite-Elemente-Methode untersucht. Dabei wird besonders auf den Einfluss
des Innendrucks, der Belastung und der Temperatur eingegangen. Die Ergebnisse
werden mit der Vollprobengeometrie verglichen, um die Eignung der Hohlprobe als
Alternative zur Vollprobe zu untersuchen. Ohne Innendruck ist kein Unterschied
im Verformungsverhalten zwischen Voll- und Hohlprobe zu erkennen. Bei hohen
Innendrücken kann die Hohlprobe ihre Formstabilität verlieren. Daher können in
Experimenten nicht alle Kombinationen aus Temperatur und Innendruck untersucht
werden.
Im zweiten Teil der Arbeit wird die belastungsabhängige Wasserstoffdiffusion an einer
angerissenen Hohlprobe numerisch untersucht. Durch die Spannungsgradienten an der
Rissspitze wird die Wasserstoffkonzentration beeinflusst. Um einen Zusammenhang
zwischen der Plastizität und der Diffusion zu untersuchen, wird eine plastische und
eine Diffusionszone ausgewertet. Hier zeigt sich, dass die Diffusionszone hauptsächlich
von der Risslänge und weniger von der Belastung abhängt
Machine-Learning-Verfahren in betriebswirtschaftlichen Entscheidungen im Kontext menschlicher Verantwortung
No full textMachine Learning (ML) als das aktuell wohl am meisten diskutierte Teilgebiet von Künstlicher Intelligenz (KI) verspricht und realisiert bereits sinnvolle Unterstützung u.a. beim autonomen Fahren, der Predictive Maintenance, der Verbrechensvorbeugung, dem Zusammenführen von Angebot und Nachfrage durch Empfehlungslisten oder im Kundenservice mit Softbots.1 All diesen Anwendung ist letztlich gemeinsam, dass Entscheidungen zu treffen sind, und zwar möglichst rational vor dem Hintergrund von subjektiven Präferenzsystemen und den in Betracht gezogenen Handlungsalternativen. Die Entscheidungsgegenstände betreffen Fragen, wann ein Fahrzeug leicht abgebremst werden soll, in welcher Gegend schwerpunktmäßig Polizeipräsenz gezeigt werden soll oder wann eine Maschine gewartet werden soll
Aliasing and adversarial robust generalization of CNNs
No full textMany commonly well-performing convolutional neural network models have shown to be susceptible to input data perturbations, indicating a low model robustness. To reveal model weaknesses, adversarial attacks are specifically optimized to generate small, barely perceivable image perturbations that flip the model prediction. Robustness against attacks can be gained by using adversarial examples during training, which in most cases reduces the measurable model attackability. Unfortunately, this technique can lead to robust overfitting, which results in non-robust models. In this paper, we analyze adversarially trained, robust models in the context of a specific network operation, the downsampling layer, and provide evidence that robust models have learned to downsample more accurately and suffer significantly less from downsampling artifacts, aka. aliasing, than baseline models. In the case of robust overfitting, we observe a strong increase in aliasing and propose a novel early stopping approach based on the measurement of aliasing
Entwicklung von Cyberrisiko-Szenarien
No full textDie Modellierung von Risikoszenarien ist allgemein und mit Bezug auf Cyberrisiken eine herausfordernde Tätigkeit. Domain-Expertise und Methodenkenntnisse sind erforderlich, um ein Gesamtbild entwickeln zu können. Der vorliegende Beitrag greift auf die Cyber Threat Intelligence und das STIX-Rahmenwerk zurück und verbindet die Ergebnisse mit einer Szenariotechnik
Design of a 3D Printed Force Sensor in the Field of Robotics Utilizing an Embedded Constantan Wire as Sensing Element
No full textThe development of a 3D printed force sensor for a gripper was studied applying an embedded constantan wire as sensing element. In the first section, the state of the art is explained. In the main section of the paper the modeling, simulation and verification of a sensor element are described for a three-point bending test made in accordance with the DIN EN ISO 178. The 3D printing process of the Fused Filament Fabrication (FFF) utilized for manufacturing the sensor samples in combination with an industrial robot are shown. A comparison between theory and practice are considered in detail. Finally, an outlook is given regarding the integration of the sensor element in gripper jaws
Attracting Future Students' Attention by an UX-Optimized Website
No full textAs a university it is more and more difficult to reach all target groups equally. Common problems like information overload, numerous institutions with same focuses or multi-channel-communication make it hard to gain the attention of the target group. This paper is four-fold: we present an overview of the state of art and the importance of the study (I), based on which we highlight the approach to user experience analysis. First, we identified the irritations in the course of an expert evaluation (II) and verified them within the test, including the target groups (III). Finally, based on the results, we were able to pro-vide recommendations for action to improve the UX and to be used for the conception of an intranet (IV)
Screening of orange peel waste on valuable compounds by gradient multiple development diode-array high-performance thin-layer chromatography
Get PDFHigh-performance thin-layer chromatography (HPTLC), as the modern form of TLC (thin-layer chromatography), is suitable for detecting pharmaceutically active compounds over a wide polarity range using the gradient multiple development (GMD) technique. Diode-array detection (DAD) in conjunction with HPTLC can simultaneously acquire ultraviolet‒visible (UV‒VIS) and fluorescence spectra directly from the plate. Visualization as a contour plot helps to identify separated zones. An orange peel extract is used as an example to show how GMD‒DAD‒HPTLC in seven different developments with seven different solvents can provide an overview of the entire sample. More than 50 compounds in the extract can be separated on a 6-cm HPTLC plate. Such separations take place in the biologically inert stationary phase of HPTLC, making it a suitable method for effect-directed analysis (EDA). HPTLC‒EDA can even be performed with living organism, as confirmed by the use of Aliivibrio fischeri bacteria to detect bioluminescence as a measure of toxicity. The combining of gradient multiple development planar chromatography with diode-array detection and effect-directed analysis (GMD‒DAD‒HPTLC‒EDA) in conjunction with specific staining methods and time-of-flight mass spectrometry (TOF‒MS) will be the method of choice to find new chemical structures from plant extracts that can serve as the basic structure for new pharmaceutically active compounds
Can a simplified knee abduction moment estimation be used for athlete screening? Implications for ACL injury prevention
No full textThis study aimed to compare a simplified calculation of the knee abduction moment with the traditional inverse dynamics calculation when athletes perform fake-cut maneuvers with different complexities. In the simplified calculation, we multiply the force vector with its lever arm to the knee, projected onto the local coordinate system of the proximal thigh, hence neglecting the inertial contributions from distal segments. We found very strong ranking consistency using Spearman’s rank correlation coefficient when using the simplified method compared to the traditional calculation. Independent of the tasks, the simplified method resulted in higher moments than the inverse dynamics. This was caused by ignoring the moment caused by segment linear acceleration generating a counteracting moment by about 7%. An alternative to the complex calculations of inverse dynamics can be used to investigate the contributions of the GRF magnitude and its lever arm to the knee
Blockchain-IoT peer device storage optimization using an advanced time-variant multi-objective particle swarm optimization algorithm
Get PDFThe integration of Internet of Things devices onto the Blockchain implies an increase in the transactions that occur on the Blockchain, thus increasing the storage requirements.
A solution approach is to leverage cloud resources for storing blocks within the chain. The paper, therefore, proposes two solutions to this problem. The first being an improved hybrid architecture design which uses containerization to create a side chain on a fog node for the devices connected to it and an Advanced Time‑variant Multi‑objective Particle Swarm Optimization Algorithm (AT‑MOPSO) for determining the optimal number of blocks that should be transferred to the cloud for storage. This algorithm uses time‑variant weights for the velocity of the particle swarm optimization and the non‑dominated sorting and mutation schemes from NSGA‑III. The proposed algorithm was compared with results from the original MOPSO algorithm, the Strength Pareto Evolutionary Algorithm (SPEA‑II), and the Pareto Envelope‑based Selection Algorithm with region‑based selection (PESA‑II), and NSGA‑III. The proposed AT‑MOPSO showed better results than the aforementioned MOPSO algorithms in cloud storage cost and query probability optimization. Importantly, AT‑MOPSO achieved 52% energy efficiency compared to NSGA‑III.
To show how this algorithm can be applied to a real‑world Blockchain system, the BISS industrial Blockchain architecture was adapted and modified to show how the AT‑MOPSO can be used with existing Blockchain systems and the benefits it provides
충전식 배터리의 충전상태 및 건강상태를 결정하는 방법 및 장치 (KR20220070480A)
No full text본 발명은 특정한 배터리 유형의 충전식 배터리(106)의 충전상태(SOC) 또는 이와 물리적으로 관련된 매개변수, 특히 배터리에 포함된 잔류 충전량 Q를 결정하기 위한 방법 및 장치에 관한 것으로서, 본 발명의 방법은 해당 배터리(106) 또는 해당 배터리 유형에 대해 매개변수화된 전압-제어 배터리 모델(102)에 의해 작동한다. 배터리 전압 Umess 만이 측정되어 배터리 모델(102)에 입력변수로 사용할 수 있도록 만들어졌다. 본 발명은 또한 배터리(102)의 건강상태(SOH)를 결정하기 위한 방법 및 장치에 관한 것으로, 배터리 모델(102)은 SOC를 결정하는 데에도 사용되며 모델링된 배터리 전류 Imod 를 공급한다. 이로부터, 모델링된 충전량은 배터리(106)의 충전 및 방전 단계 동안 결정되고, 측정된 배터리 전류 Imess 로부터 결정된, 측정된 충전량과 비교할 수 있다. 배터리 모델(102)은 노화되지 않으므로 배터리의 SOH를 결정하는 데 사용할 수 있다