TY  - JOUR
A1  - Altherr, Lena
A1  - Ederer, Thorsten
A1  - Pöttgen, Philipp
A1  - Lorenz, Ulf
A1  - Pelz, Peter F.
ED  - Pelz, Peter F.
ED  - Groche, Peter
T1  - Multicriterial optimization of technical systems considering multiple load and availability scenarios
JF  - Applied Mechanics and Materials
N2  - Cheap does not imply cost-effective -- this is rule number one of zeitgeisty system design. The initial investment accounts only for a small portion of the lifecycle costs of a technical system. In fluid systems, about ninety percent of the total costs are caused by other factors like power consumption and maintenance. With modern optimization methods, it is already possible to plan an optimal technical system considering multiple objectives. In this paper, we focus on an often neglected contribution to the lifecycle costs: downtime costs due to spontaneous failures. Consequently, availability becomes an issue.
KW  - sustainability
KW  - availability
KW  - energy efficiency
KW  - mixed-integer linear programming
KW  - system synthesis
Y1  - 2015
SN  - 1660-9336
U6  - https://doi.org/10.4028/www.scientific.net/AMM.807.247
VL  - 807
SP  - 247
EP  - 256
ER  - 
TY  - CHAP
A1  - Büsgen, André
A1  - Klöser, Lars
A1  - Kohl, Philipp
A1  - Schmidts, Oliver
A1  - Kraft, Bodo
A1  - Zündorf, Albert
T1  - Exploratory analysis of chat-based black market profiles with natural language processing
T2  - Proceedings of the 11th International Conference on Data Science, Technology and Applications
N2  - Messenger apps like WhatsApp or Telegram are an integral part of daily communication. Besides the various positive effects, those services extend the operating range of criminals. Open trading groups with many thousand participants emerged on Telegram. Law enforcement agencies monitor suspicious users in such chat rooms. This research shows that text analysis, based on natural language processing, facilitates this through a meaningful domain overview and detailed investigations. We crawled a corpus from such self-proclaimed black markets and annotated five attribute types products, money, payment methods, user names, and locations. Based on each message a user sends, we extract and group these attributes to build profiles. Then, we build features to cluster the profiles. Pretrained word vectors yield better unsupervised clustering results than current
state-of-the-art transformer models. The result is a semantically meaningful high-level overview of the user landscape of black market chatrooms. Additionally, the extracted structured information serves as a foundation for further data exploration, for example, the most active users or preferred payment methods.
KW  - Clustering
KW  - Natural Language Processing
KW  - Information Extraction
KW  - Profile Extraction
KW  - Text Mining
Y1  - 2022
SN  - 978-989-758-583-8
U6  - https://doi.org/10.5220/0011271400003269
SN  - 2184-285X
N1  - 11th International Conference on Data Science, Technology and Applications DATA - Volume 1, 83-94, 2022, Lisbon, Portugal
SP  - 83
EP  - 94
ER  - 
TY  - CHAP
A1  - Ostkotte, Sebastian
A1  - Peters, Constantin
A1  - Hüning, Felix
A1  - Bragard, Michael
T1  - Design, implementation and verification of an rotational incremental position encoder based on the magnetic Wiegand effect
T2  - 2022 ELEKTRO (ELEKTRO)
N2  - This paper covers the use of the magnetic Wiegand effect to design an innovative incremental encoder. First, a theoretical design is given, followed by an estimation of the achievable accuracy and an optimization in open-loop operation.
Finally, a successful experimental verification is presented. For this purpose, a permanent magnet synchronous machine is controlled in a field-oriented manner, using the angle information of the prototype.
KW  - Position Encoder
KW  - Rotational Encoder
KW  - Wiegand Effect
KW  - Angle Sensor
KW  - Incremental Encoder
Y1  - 2022
SN  - 978-1-6654-6726-1
SN  - 978-1-6654-6727-8
U6  - https://doi.org/10.1109/ELEKTRO53996.2022.9803477
SN  - 2691-0616
N1  - 2022 ELEKTRO (ELEKTRO), 23-26 Mai 2022, Krakow, Poland.
PB  - IEEE
ER  - 
TY  - JOUR
A1  - Mandekar, Swati
A1  - Holland, Abigail
A1  - Thielen, Moritz
A1  - Behbahani, Mehdi
A1  - Melnykowycz, Mark
T1  - Advancing towards Ubiquitous EEG, Correlation of In-Ear EEG with Forehead EEG
JF  - Sensors
N2  - Wearable EEG has gained popularity in recent years driven by promising uses outside of clinics and research. The ubiquitous application of continuous EEG requires unobtrusive form-factors that are easily acceptable by the end-users. In this progression, wearable EEG systems have been moving from full scalp to forehead and recently to the ear. The aim of this study is to demonstrate that emerging ear-EEG provides similar impedance and signal properties as established forehead EEG. EEG data using eyes-open and closed alpha paradigm were acquired from ten healthy subjects using generic earpieces fitted with three custom-made electrodes and a forehead electrode (at Fpx) after impedance analysis. Inter-subject variability in in-ear electrode impedance ranged from 20 kΩ to 25 kΩ at 10 Hz. Signal quality was comparable with an SNR of 6 for in-ear and 8 for forehead electrodes. Alpha attenuation was significant during the eyes-open condition in all in-ear electrodes, and it followed the structure of power spectral density plots of forehead electrodes, with the Pearson correlation coefficient of 0.92 between in-ear locations ELE (Left Ear Superior) and ERE (Right Ear Superior) and forehead locations, Fp1 and Fp2, respectively. The results indicate that in-ear EEG is an unobtrusive alternative in terms of impedance, signal properties and information content to established forehead EEG.
KW  - in-ear EEG
KW  - correlation
KW  - forehead EEG
KW  - impedance spectroscopy
KW  - biopotential electrodes
Y1  - 2022
U6  - https://doi.org/10.3390/s22041568
SN  - 1424-8220
VL  - 22
IS  - 4
SP  - 1
EP  - 19
PB  - MDPI
CY  - Basel
ER  - 
TY  - CHAP
A1  - Altherr, Lena
A1  - Leise, Philipp
T1  - Resilience as a concept for mastering uncertainty
T2  - Mastering Uncertainty in Mechanical Engineering
Y1  - 2021
SN  - 978-3-030-78353-2
U6  - https://doi.org/10.1007/978-3-030-78354-9
N1  - Unterkapitel 6.3.1 des Kapitels "Strategies for Mastering Uncertainty"
SP  - 412
EP  - 417
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Altherr, Lena
A1  - Leise, Philipp
A1  - Pfetsch, Marc E.
A1  - Schmitt, Andreas
T1  - Optimal design of resilient technical systems on the example of water supply systems
T2  - Mastering Uncertainty in Mechanical Engineering
Y1  - 2021
SN  - 978-3-030-78356-3
N1  - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty"
SP  - 429
EP  - 433
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Leise, Philipp
A1  - Altherr, Lena
T1  - Experimental evaluation of resilience metrics in a fluid system
T2  - Mastering Uncertainty in Mechanical Engineering
Y1  - 2021
SN  - 978-3-030-78356-3
N1  - Unterkapitel des Kapitels "Strategies for Mastering Uncertainty"
SP  - 442
EP  - 447
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Lorenz, Imke-Sophie
A1  - Altherr, Lena
A1  - Pelz, Peter F.
T1  - Resilience enhancement of critical infrastructure – graph-theoretical resilience analysis of the water distribution system in the German city of Darmstadt
T2  - 14th WCEAM Proceedings
N2  - Water suppliers are faced with the great challenge of achieving high-quality and, at the same time, low-cost water supply. Since climatic and demographic influences will pose further challenges in the future, the resilience enhancement of water distribution systems (WDS), i.e. the enhancement of their capability to withstand and recover from disturbances, has been in particular focus recently. To assess the resilience of WDS, graph-theoretical metrics have been proposed. In this study, a promising approach is first physically derived analytically and then applied to assess the resilience of the WDS for a district in a major German City. The topology based resilience index computed for every consumer node takes into consideration the resistance of the best supply path as well as alternative supply paths. This resistance of a supply path is derived to be the dimensionless pressure loss in the pipes making up the path. The conducted analysis of a present WDS provides insight into the process of actively influencing the resilience of WDS locally and globally by adding pipes. The study shows that especially pipes added close to the reservoirs and main branching points in the WDS result in a high resilience enhancement of the overall WDS.
KW  - Resilient infrastructure
KW  - Resilience assessment
KW  - Resilience metric graph theory
KW  - Water distribution system
KW  - Case study
Y1  - 2020
SN  - 978-3-030-64228-0
SN  - 978-3-030-64227-3
U6  - https://doi.org/10.1007/978-3-030-64228-0_13
N1  - 14th WCEAM Proceedings. World Congress on Engineering Asset Management, 28-31 July 2019, Singapore

Part of the Lecture Notes in Mechanical Engineering book series (LNME)
SP  - 137
EP  - 149
PB  - Springer
CY  - Cham
ER  - 
TY  - CHAP
A1  - Schänzle, Christian
A1  - Altherr, Lena
A1  - Ederer, Thorsten
A1  - Pelz, Peter
T1  - TOR – Towards the energetically optimal ventilation system
KW  - Energy
KW  - Efficiency
KW  - Ventilation System
KW  - Discrete Optimisation
KW  - TGA
Y1  - 2015
N1  - EST 2015, Karlsruhe, 19-21 Mai 2015
ER  - 
TY  - CHAP
A1  - Nikolovski, Gjorgji
A1  - Reke, Michael
A1  - Elsen, Ingo
A1  - Schiffer, Stefan
T1  - Machine learning based 3D object detection for navigation in unstructured environments
T2  - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)
N2  - In this paper we investigate the use of deep neural networks for 3D object detection in uncommon, unstructured environments such as in an open-pit mine. While neural nets are frequently used for object detection in regular autonomous driving applications, more unusual driving scenarios aside street traffic pose additional challenges. For one, the collection of appropriate data sets to train the networks is an issue. For another, testing the performance of trained networks often requires tailored integration with the particular domain as well. While there exist different solutions for these problems in regular autonomous driving, there are only very few approaches that work for special domains just as well. We address both the challenges above in this work. First, we discuss two possible ways of acquiring data for training and evaluation. That is, we evaluate a semi-automated annotation of recorded LIDAR data and we examine synthetic data generation. Using these datasets we train and test different deep neural network for the task of object detection. Second, we propose a possible integration of a ROS2 detector module for an autonomous driving platform. Finally, we present the performance of three state-of-the-art deep neural networks in the domain of 3D object detection on a synthetic dataset and a smaller one containing a characteristic object from an open-pit mine.
KW  - 3D object detection
KW  - LiDAR
KW  - autonomous driving
KW  - Deep learning
KW  - Three-dimensional displays
Y1  - 2021
SN  - 978-1-6654-7921-9
U6  - https://doi.org/10.1109/IVWorkshops54471.2021.9669218
N1  - 2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops), 11-17 July 2021,  Nagoya, Japan.
SP  - 236
EP  - 242
PB  - IEEE
ER  -