TY  - CHAP
A1  - Schulte, Maximilian
A1  - Eggert, Mathias
T1  - Predicting hourly bitcoin prices based on long short-term memory neural networks
T2  - Proceedings of the International Conference on Wirtschaftsinformatik (WI) 2021
N2  - Bitcoin is a cryptocurrency and is considered a high-risk asset
class whose price changes are difficult to predict. Current research focusses
on daily price movements with a limited number of predictors. The paper at
hand aims at identifying measurable indicators for Bitcoin price movement s
and the development of a suitable forecasting model for hourly changes. The
paper provides three research contributions. First, a set of significant
indicators for predicting the Bitcoin price is identified. Second, the results of
a trained Long Short-term Memory (LSTM) neural network that predicts
price changes on an hourly basis is presented and compared with other
algorithms. Third, the results foster discussions of the applicability of neural
nets for stock price predictions. In total, 47 input features for a period of
over 10 months could be retrieved to train a neural net that predicts the
Bitcoin price movements with an error rate of 3.52 %.
Y1  - 2021
N1  - 16th International Conference on Wirtschaftsinformatik,
March 2021, Essen, Germany
ER  - 
TY  - CHAP
A1  - Funke, Harald
A1  - Beckmann, Nils
A1  - Keinz, Jan
A1  - Horikawa, Atsushi
T1  - 30 years of dry low NOx micromix combustor research for hydrogen-rich fuels: an overview of past and present activities
T2  - Proceedings of the ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition, September 21–25, 2020, Virtual, Online. Vol.: 4B: Combustion, Fuels, and Emissions
KW  - Micromix
KW  - Hydrogen
KW  - Fuel-flexibility
KW  - NOx
KW  - Emissions
Y1  - 2021
SN  - 978-0-7918-8413-3
U6  - http://dx.doi.org/10.1115/GT2020-16328
N1  - Paper No. GT2020-16328, V04BT04A069
PB  - American Society of Mechanical Engineers (ASME)
ER  - 
TY  - JOUR
A1  - Ayed, Anis Haj
A1  - Kusterer, Karsten
A1  - Funke, Harald
A1  - Keinz, Jan
A1  - Bohn, D.
T1  - CFD based exploration of the dry-low-NOx hydrogen micromix combustion technology at increased energy densities
JF  - Propulsion and Power Research
KW  - Micromix combustion
KW  - Hydrogen gas turbine
KW  - Hydrogen combustion
KW  - High hydrogen combustion
KW  - Dry-low-NOx (DLN) combustion
Y1  - 2017
SN  - 2212-540X
U6  - http://dx.doi.org/10.1016/j.jppr.2017.01.005
VL  - 6
IS  - 1
SP  - 15
EP  - 24
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - CHAP
A1  - Ayed, Anis Haj
A1  - Striegan, Constantin J. D.
A1  - Kusterer, Karsten
A1  - Funke, Harald
A1  - Kazari, M.
A1  - Horikawa, Atsushi
A1  - Okada, Kunio
T1  - Automated design space exploration of the hydrogen fueled "Micromix" combustor technology
N2  - Combined with the use of renewable energy sources for
its production, Hydrogen represents a possible alternative gas
turbine fuel for future low emission power generation. Due to
its different physical properties compared to other fuels such
as natural gas, well established gas turbine combustion
systems cannot be directly applied for Dry Low NOx (DLN)
Hydrogen combustion. This makes the development of new
combustion technologies an essential and challenging task
for the future of hydrogen fueled gas turbines.
The newly developed and successfully tested “DLN
Micromix” combustion technology offers a great potential to
burn hydrogen in gas turbines at very low NOx emissions.
Aiming to further develop an existing burner design in terms
of increased energy density, a redesign is required in order to
stabilise the flames at higher mass flows and to maintain low
emission levels.
For this purpose, a systematic design exploration has
been carried out with the support of CFD and optimisation
tools to identify the interactions of geometrical and design
parameters on the combustor performance. Aerodynamic
effects as well as flame and emission formation are observed
and understood time- and cost-efficiently. Correlations
between single geometric values, the pressure drop of the
burner and NOx production have been identified as a result.
This numeric methodology helps to reduce the effort of
manufacturing and testing to few designs for single
validation campaigns, in order to confirm the flame stability
and NOx emissions in a wider operating condition field.
Y1  - 2017
N1  - Proceedings of the 1st Global Power and Propulsion Forum
GPPF 2017, Jan 16-18, 2017, Zurich, Switzerland
SP  - 1
EP  - 8
ER  - 
TY  - CHAP
A1  - Heuermann, Holger
A1  - Harzheim, Thomas
A1  - Mühmel, Marc
T1  - A maritime harmonic radar search and rescue system using passive and active tags
T2  - 2020 17th European Radar Conference (EuRAD)
KW  - Harmonic Radar
KW  - Rescue System
KW  - Frequency Doubler
KW  - Transponder
KW  - Tag
Y1  - 2021
SN  - 978-2-87487-061-3
U6  - http://dx.doi.org/10.1109/EuRAD48048.2021.00030
N1  - Proceedings of the 17th European Radar Conference, 
13th - 15th January 2021, Utrecht, Netherlands
SP  - 73
EP  - 76
PB  - IEEE
ER  - 
TY  - JOUR
A1  - Engemann, Heiko
A1  - Du, Shengzhi
A1  - Kallweit, Stephan
A1  - Cönen, Patrick
A1  - Dawar, Harshal
T1  - OMNIVIL - an autonomous mobile manipulator for flexible production
JF  - Sensors
Y1  - 2020
SN  - 1424-8220
U6  - http://dx.doi.org/10.3390/s20247249
N1  - Special issue: Sensor Networks Applications in Robotics and Mobile Systems
VL  - 20
IS  - 24, art. no. 7249
SP  - 1
EP  - 30
PB  - MDPI
CY  - Basel
ER  - 
TY  - CHAP
A1  - Mistler, M.
A1  - Butenweg, Christoph
A1  - Anthoine, A.
T1  - Evaluation of the failure criterion for masonry by homogenisation
T2  - Proceedings of the Seventh International Conference on Computational Structures Technology : [Lisbon, Portugal, 7 - 9 September 2004] / ed. by B. H. V. Topping and C.A. Mota Soares
Y1  - 2004
SN  - 0-948749-95-4
U6  - http://dx.doi.org/10.4203/ccp.79.201
PB  - Civil-Comp Press
CY  - Stirling
ER  - 
TY  - JOUR
A1  - Jablonski, Melanie
A1  - Münstermann, Felix
A1  - Nork, Jasmina
A1  - Molinnus, Denise
A1  - Muschallik, Lukas
A1  - Bongaerts, Johannes
A1  - Wagner, Torsten
A1  - Keusgen, Michael
A1  - Siegert, Petra
A1  - Schöning, Michael Josef
T1  - Capacitive field‐effect biosensor applied for the detection of acetoin in alcoholic beverages and fermentation broths
JF  - physica status solidi (a) applications and materials science
N2  - An acetoin biosensor based on a capacitive electrolyte–insulator–semiconductor (EIS) structure modified with the enzyme acetoin reductase, also known as butane-2,3-diol dehydrogenase (Bacillus clausii DSM 8716ᵀ), is applied for acetoin detection in beer, red wine, and fermentation broth samples for the first time. The EIS sensor consists of an Al/p-Si/SiO₂/Ta₂O₅ layer structure with immobilized acetoin reductase on top of the Ta₂O₅ transducer layer by means of crosslinking via glutaraldehyde. The unmodified and enzyme-modified sensors are electrochemically characterized by means of leakage current, capacitance–voltage, and constant capacitance methods, respectively.
KW  - acetoin
KW  - acetoin reductase
KW  - alcoholic beverages
KW  - biosensors
KW  - capacitive field-effect sensors
Y1  - 2021
U6  - http://dx.doi.org/10.1002/pssa.202000765
SN  - 1862-6319
VL  - 218
IS  - 13
PB  - Wiley-VCH
CY  - Weinheim
ER  - 
TY  - CHAP
A1  - Engemann, Heiko
A1  - Du, Shengzhi
A1  - Kallweit, Stephan
A1  - Ning, Chuanfang
A1  - Anwar, Saqib
T1  - AutoSynPose: Automatic Generation of Synthetic Datasets for 6D Object Pose Estimation
T2  - Machine Learning and Artificial Intelligence. Proceedings of MLIS 2020
N2  - We present an automated pipeline for the generation of synthetic datasets for six-dimension (6D) object pose estimation. Therefore, a completely automated generation process based on predefined settings is developed, which enables the user to create large datasets with a minimum of interaction and which is feasible for applications with a high object variance. The pipeline is based on the Unreal 4 (UE4) game engine and provides a high variation for domain randomization, such as object appearance, ambient lighting, camera-object transformation and distractor density. In addition to the object pose and bounding box, the metadata includes all randomization parameters, which enables further studies on randomization parameter tuning. The developed workflow is adaptable to other 3D objects and UE4 environments. An exemplary dataset is provided including five objects of the Yale-CMU-Berkeley (YCB) object set. The datasets consist of 6 million subsegments using 97 rendering locations in 12 different UE4 environments. Each dataset subsegment includes one RGB image, one depth image and one class segmentation image at pixel-level.
Y1  - 2020
SN  - 978-1-64368-137-5
U6  - http://dx.doi.org/10.3233/FAIA200770
N1  - Frontiers in Artificial Intelligence and Applications. Vol 332
SP  - 89
EP  - 97
PB  - IOS Press
CY  - Amsterdam
ER  - 
TY  - THES
A1  - Bronder, Thomas
T1  - Label-free detection of tuberculosis DNA with capacitive field-effect biosensors
Y1  - 2020
U6  - http://dx.doi.org/10.17192/z2021.0056
N1  - Dissertation, Universität, Marburg 2020
PB  - Philipps-Universität Marburg
CY  - Marburg
ER  -