TY - JOUR A1 - Beverungen, Daniel A1 - Eggert, Mathias A1 - Voigt, Matthias A1 - Rosemann, Michael T1 - Augmenting Analytical CRM Strategies with Social BI JF - International Journal of Business Intelligence Research (IJBIR) Y1 - 2013 U6 - http://dx.doi.org/10.4018/ijbir.2013070103 SN - 1947-3591 VL - 4 IS - 3 SP - 32 EP - 49 PB - IGI Global CY - Hershey ER - TY - JOUR A1 - Pietsch, Wolfram T1 - Augmenting voice of the customer analysis by analysis of belief JF - QFD-Forum Y1 - 2015 SN - 1431-6951 IS - 30 SP - 1 EP - 5 ER - TY - JOUR A1 - Schwabedal, Justus T. C. A1 - Sippel, Daniel A1 - Brandt, Moritz D. A1 - Bialonski, Stephan T1 - Automated Classification of Sleep Stages and EEG Artifacts in Mice with Deep Learning N2 - Sleep scoring is a necessary and time-consuming task in sleep studies. In animal models (such as mice) or in humans, automating this tedious process promises to facilitate long-term studies and to promote sleep biology as a data-driven f ield. We introduce a deep neural network model that is able to predict different states of consciousness (Wake, Non-REM, REM) in mice from EEG and EMG recordings with excellent scoring results for out-of-sample data. Predictions are made on epochs of 4 seconds length, and epochs are classified as artifactfree or not. The model architecture draws on recent advances in deep learning and in convolutional neural networks research. In contrast to previous approaches towards automated sleep scoring, our model does not rely on manually defined features of the data but learns predictive features automatically. We expect deep learning models like ours to become widely applied in different fields, automating many repetitive cognitive tasks that were previously difficult to tackle. Y1 - 2018 U6 - http://dx.doi.org/10.48550/arXiv.1809.08443 ER - TY - CHAP A1 - Veettil, Yadu Krishna Morassery A1 - Rakshit, Shantam A1 - Schopen, Oliver A1 - Kemper, Hans A1 - Esch, Thomas A1 - Shabani, Bahman ED - Bin Abdollah, Mohd Fadzli ED - Amiruddin, Hilmi ED - Singh, Amrik Singh Phuman ED - Munir, Fudhail Abdul ED - Ibrahim, Asriana T1 - Automated Control System Strategies to Ensure Safety of PEM Fuel Cells Using Kalman Filters T2 - Proceedings of the 7th International Conference and Exhibition on Sustainable Energy and Advanced Materials (ICE-SEAM 2021), Melaka, Malaysia N2 - Having well-defined control strategies for fuel cells, that can efficiently detect errors and take corrective action is critically important for safety in all applications, and especially so in aviation. The algorithms not only ensure operator safety by monitoring the fuel cell and connected components, but also contribute to extending the health of the fuel cell, its durability and safe operation over its lifetime. While sensors are used to provide peripheral data surrounding the fuel cell, the internal states of the fuel cell cannot be directly measured. To overcome this restriction, Kalman Filter has been implemented as an internal state observer. Other safety conditions are evaluated using real-time data from every connected sensor and corrective actions automatically take place to ensure safety. The algorithms discussed in this paper have been validated thorough Model-in-the-Loop (MiL) tests as well as practical validation at a dedicated test bench. KW - control system KW - PEM fuel cells KW - Kalman filter Y1 - 2022 SN - 978-981-19-3178-9 SN - 978-981-19-3179-6 (E-Book) U6 - http://dx.doi.org/10.1007/978-981-19-3179-6_55 SN - 2195-4356 N1 - The 7th International Conference and Exhibition on Sustainable Energy and Advanced Material (ICE-SEAM 2021) was organized by Universiti Teknikal Malaysia Melaka (UTeM), Malaysia, in association with the Universitas Sebelas Maret (UNS), Indonesia, on 23 November 2021 SP - 296 EP - 299 PB - Springer Nature CY - Singapore 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 - JOUR A1 - Gorzalka, Philip A1 - Schmiedt, Jacob Estevam A1 - Schorn, Christian T1 - Automated Generation of an Energy Simulation Model for an Existing Building from UAV Imagery JF - Buildings N2 - An approach to automatically generate a dynamic energy simulation model in Modelica for a single existing building is presented. It aims at collecting data about the status quo in the preparation of energy retrofits with low effort and costs. The proposed method starts from a polygon model of the outer building envelope obtained from photogrammetrically generated point clouds. The open-source tools TEASER and AixLib are used for data enrichment and model generation. A case study was conducted on a single-family house. The resulting model can accurately reproduce the internal air temperatures during synthetical heating up and cooling down. Modelled and measured whole building heat transfer coefficients (HTC) agree within a 12% range. A sensitivity analysis emphasises the importance of accurate window characterisations and justifies the use of a very simplified interior geometry. Uncertainties arising from the use of archetype U-values are estimated by comparing different typologies, with best- and worst-case estimates showing differences in pre-retrofit heat demand of about ±20% to the average; however, as the assumptions made are permitted by some national standards, the method is already close to practical applicability and opens up a path to quickly estimate possible financial and energy savings after refurbishment. KW - Modelica KW - heat transfer coefficient KW - heat demand KW - building energy modelling KW - building energy simulation Y1 - 2021 U6 - http://dx.doi.org/10.3390/buildings11090380 SN - 2075-5309 N1 - This article belongs to the Special Issue "Application of Computer Technology in Buildings" VL - 11 IS - 9 PB - MDPI CY - Basel ER - TY - JOUR A1 - Neu, Eugen A1 - Janser, Frank A1 - Khatibi, Akbar A. A1 - Orifici, Adrian C. T1 - Automated modal parameter-based anomaly detection under varying wind excitation JF - Structural Health Monitoring N2 - Wind-induced operational variability is one of the major challenges for structural health monitoring of slender engineering structures like aircraft wings or wind turbine blades. Damage sensitive features often show an even bigger sensitivity to operational variability. In this study a composite cantilever was subjected to multiple mass configurations, velocities and angles of attack in a controlled wind tunnel environment. A small-scale impact damage was introduced to the specimen and the structural response measurements were repeated. The proposed damage detection methodology is based on automated operational modal analysis. A novel baseline preparation procedure is described that reduces the amount of user interaction to the provision of a single consistency threshold. The procedure starts with an indeterminate number of operational modal analysis identifications from a large number of datasets and returns a complete baseline matrix of natural frequencies and damping ratios that is suitable for subsequent anomaly detection. Mahalanobis distance-based anomaly detection is then applied to successfully detect the damage under varying severities of operational variability and with various degrees of knowledge about the present operational conditions. The damage detection capabilities of the proposed methodology were found to be excellent under varying velocities and angles of attack. Damage detection was less successful under joint mass and wind variability but could be significantly improved through the provision of the currently encountered operational conditions. Y1 - 2016 U6 - http://dx.doi.org/10.1177/1475921716665803 SN - 1475-9217 VL - 15 IS - 6 SP - 1 EP - 20 PB - Sage CY - London ER - TY - THES A1 - Pfaff, Raphael T1 - Automated processing of the ISL Doppler images Y1 - 2007 N1 - Hagen, Fernuniv., Bachelorarbeit, 2007 ER - TY - CHAP A1 - Sildatke, Michael A1 - Karwanni, Hendrik A1 - Kraft, Bodo A1 - Schmidts, Oliver A1 - Zündorf, Albert T1 - Automated Software Quality Monitoring in Research Collaboration Projects T2 - ICSEW'20: Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops Y1 - 2020 U6 - http://dx.doi.org/10.1145/3387940.3391478 SP - 603 EP - 610 ER - TY - JOUR A1 - Schmitz, Günter A1 - Oligschläger, U. A1 - Eifler, G. A1 - Lechner, H. T1 - Automated System for Optimized Calibration of Engine Management Systems Y1 - 1994 N1 - SAE International Congress and Exposition, Detroit, Feb. 28 - March 3 ; SAE- Paper-No.: 940151 ; ; ISBN Set: 90-6191-521-X SP - 101 EP - 106 PB - Rotterdam [u.a.] CY - Balkema ER - TY - CHAP A1 - Morandi, Paolo A1 - Butenweg, Christoph A1 - Breis, Khaled A1 - Beyer, Katrin A1 - Magenes, Guido ED - Arion, Christian ED - Scupin, Alexandra ED - Ţigănescu, Alexandru T1 - Behaviour factor q for the seismic design of URM buildings T2 - The Third European Conference on Earthquake Engineering and Seismology September 4 – September 9, 2022, Bucharest N2 - Recent earthquakes showed that low-rise URM buildings following codecompliant seismic design and details behaved in general very well without substantial damages. Although advances in simulation tools make nonlinear calculation methods more readily accessible to designers, linear analyses will still be the standard design method for years to come. The present paper aims to improve the linear seismic design method by providing a proper definition of the q-factor of URM buildings. Values of q-factors are derived for low-rise URM buildings with rigid diaphragms, with reference to modern structural configurations realized in low to moderate seismic areas of Italy and Germany. The behaviour factor components for deformation and energy dissipation capacity and for overstrength due to the redistribution of forces are derived by means of pushover analyses. As a result of the investigations, rationally based values of the behaviour factor q to be used in linear analyses in the range of 2.0 to 3.0 are proposed. KW - unreinforced masonry buildings KW - modern constructions KW - seismic design KW - linear elastic analysis; KW - behaviour factor q Y1 - 2022 SN - 978-973-100-533-1 SP - 1184 EP - 1194 ER - TY - JOUR A1 - Gspandl, Stephan A1 - Pill, Ingo A1 - Reip, Michael A1 - Steinbauer, Gerald A1 - Ferrein, Alexander T1 - Belief Management for High-Level Robot Programs JF - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence [electronic resource] : Barcelona, Catalonia, Spain, 16 - 22 July 2011 / sponsored by International Joint Conferences on Artificial Intelligence (IJCAI) and the Association for the Advancement of Artificial Intelligence (AAAI). Ed. by Toby Walsh Y1 - 2011 N1 - International Joint Conference on Artificial Intelligence ; (22 : ; 2011.07.16-22 : ; Barcelona, Spain) ; IJCAI ; (22 : ; 2011.07.16-22 : ; Barcelona, Spain) SP - 900 EP - 905 ER - TY - JOUR A1 - Rens, Gavin A1 - Ferrein, Alexander T1 - Belief-node condensation for online POMDP algorithms N2 - Slightly extended version of the paper accepted at the Robotics and Artificial Intelligence Workshop, a special track of IEEE AFRICON-2013, held in Mauritius, 9-12 September 2013 Y1 - 2013 SP - 1 EP - 7 PB - IEEE CY - New York ER - TY - JOUR A1 - Schulte-Tigges, Joschua A1 - Förster, Marco A1 - Nikolovski, Gjorgji A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Kaszner, Daniel A1 - Matheis, Dominik A1 - Walter, Thomas T1 - Benchmarking of various LiDAR sensors for use in self-driving vehicles in real-world environments JF - Sensors N2 - Abstract In this paper, we report on our benchmark results of the LiDAR sensors Livox Horizon, Robosense M1, Blickfeld Cube, Blickfeld Cube Range, Velodyne Velarray H800, and Innoviz Pro. The idea was to test the sensors in different typical scenarios that were defined with real-world use cases in mind, in order to find a sensor that meet the requirements of self-driving vehicles. For this, we defined static and dynamic benchmark scenarios. In the static scenarios, both LiDAR and the detection target do not move during the measurement. In dynamic scenarios, the LiDAR sensor was mounted on the vehicle which was driving toward the detection target. We tested all mentioned LiDAR sensors in both scenarios, show the results regarding the detection accuracy of the targets, and discuss their usefulness for deployment in self-driving cars. KW - Lidar KW - Benchmark KW - Self-driving Y1 - 2022 U6 - http://dx.doi.org/10.3390/s22197146 SN - 1424-8220 N1 - This article belongs to the Special Issue "Sensor Fusion for Vehicles Navigation and Robotic Systems" VL - 22 IS - 19 PB - MDPI CY - Basel ER - TY - JOUR A1 - Burger, René A1 - Lindner, Simon A1 - Rumpf, Jessica A1 - Do, Xuan Tung A1 - Diehl, Bernd W.K. A1 - Rehahn, Matthias A1 - Monakhova, Yulia A1 - Schulze, Margit T1 - Benchtop versus high field NMR: Comparable performance found for the molecular weight determination of lignin JF - Journal of Pharmaceutical and Biomedical Analysis N2 - Lignin is a promising renewable biopolymer being investigated worldwide as an environmentally benign substitute of fossil-based aromatic compounds, e.g. for the use as an excipient with antioxidant and antimicrobial properties in drug delivery or even as active compound. For its successful implementation into process streams, a quick, easy, and reliable method is needed for its molecular weight determination. Here we present a method using 1H spectra of benchtop as well as conventional NMR systems in combination with multivariate data analysis, to determine lignin’s molecular weight (Mw and Mn) and polydispersity index (PDI). A set of 36 organosolv lignin samples (from Miscanthus x giganteus, Paulownia tomentosa and Silphium perfoliatum) was used for the calibration and cross validation, and 17 samples were used as external validation set. Validation errors between 5.6% and 12.9% were achieved for all parameters on all NMR devices (43, 60, 500 and 600 MHz). Surprisingly, no significant difference in the performance of the benchtop and high-field devices was found. This facilitates the application of this method for determining lignin’s molecular weight in an industrial environment because of the low maintenance expenditure, small footprint, ruggedness, and low cost of permanent magnet benchtop NMR systems. KW - NMR KW - PLS-regression KW - Molecular weight determination KW - Chemometrics KW - Biomass Y1 - 2022 SN - 0731-7085 U6 - http://dx.doi.org/10.1016/j.jpba.2022.114649 VL - 212 IS - Article number: 114649 PB - Elsevier CY - New York, NY ER -