TY - CHAP A1 - Wagner, Torsten A1 - Yoshinobu, T. A1 - Otto, R. A1 - Rao, C. A1 - Molina, R. A1 - Schöning, Michael Josef T1 - Licht-adressierbare potentiometrische Sensorsysteme – Konzepte und Anwendungen T2 - Sensoren und Mess-Systeme 2006 : Vorträge der 13. ITG/GMA-Fachtagung vom 13. bis 14.3.2006 in Freiburg/Breisgau Y1 - 2006 SN - 3-8007-2939-3 SP - 165 EP - 168 PB - VDE Verl. CY - Berlin ER - TY - CHAP A1 - Feldmann, Markus A1 - Pyschny, D. A1 - Döring, Bernd A1 - Kuhnhenne, Markus T1 - Life cycle assessment of steel constructions T2 - Life-cycle and sustainability of civil infrastructure systems : proceedings of the Third International Symposium on Life-Cycle Civil Engineering (IALCCE'12) : Vienna, Austria, October 3-6, 2012 Y1 - 2012 SN - 978-0-203-10336-4 SP - 321 PB - Taylor and Francis CY - Hoboken ER - TY - CHAP A1 - Kunfermann, Philipp A1 - Drumm, Christian T1 - Lifting XML schemas to ontologies - the concept finder algorithm T2 - MEDIATE 2005 First International Workshop on Mediation in Semantic Web Services Proceedings of the First International Workshop on Mediation in Semantic Web Services (MEDIATE 2005) Y1 - 2005 SP - 113 EP - 122 ER - TY - CHAP A1 - Wagner, Torsten A1 - Yoshinobu, T. A1 - Schöning, Michael Josef T1 - Light-addressable potentiometric sensor as semiconductor-based sensor platform for (bio-) chemical sensing T2 - Armenian Journal of Physics Y1 - 2008 SN - 1829-1171 SP - 99 EP - 103 ER - TY - CHAP A1 - Breuer, Lars A1 - Raue, Markus A1 - Mang, Thomas A1 - Schöning, Michael Josef A1 - Thoelen, Ronald A1 - Wagner, Torsten T1 - Light-stimulated hydrogel actuators with incorporated graphene oxide for microfluidic applications T2 - 12. Dresdner Sensor-Symposium 2015 Y1 - 2015 U6 - http://dx.doi.org/10.5162/12dss2015/P5.8 SP - 206 EP - 209 ER - TY - CHAP A1 - Breuer, Lars A1 - Guthmann, Eric A1 - Schöning, Michael Josef A1 - Thoelen, Ronald A1 - Wagner, Torsten T1 - Light-Stimulated Hydrogels with Incorporated Graphene Oxide as Actuator Material for Flow Control in Microfluidic Applications T2 - Proceedings Eurosensors 2017 Conference, Paris, France, 3–6 September 2017 Y1 - 2017 U6 - http://dx.doi.org/10.3390/proceedings1040524 SP - 1 EP - 4 ER - TY - CHAP A1 - Poth, Sebastian A1 - Monzon, Magaly A1 - Tippkötter, Nils A1 - Ulber, Roland T1 - Lignocellulosic biorefinery : process integration of hydrolysis and fermentation T2 - Proceedings / 11th European Workshop on Lignocellulosics and Pulp : August 16 - 19, 2010, Hamburg, Germany Y1 - 2010 SP - 65 EP - 68 PB - vTi CY - Hamburg ER - TY - CHAP A1 - Tran, Ngoc Trinh A1 - Trinh, Tu Luc A1 - Dao, Ngoc Tien A1 - Giap, Van Tan A1 - Truong, Manh Khuyen A1 - Dinh, Thuy Ha A1 - Staat, Manfred T1 - Limit and shakedown analysis of structures under random strength T2 - Proceedings of (NACOME2022) The 11th National Conference on Mechanics, Vol. 1. Solid Mechanics, Rock Mechanics, Artificial Intelligence, Teaching and Training, Hanoi, December 2-3, 2022 N2 - Direct methods comprising limit and shakedown analysis is a branch of computational mechanics. It plays a significant role in mechanical and civil engineering design. The concept of direct method aims to determinate the ultimate load bearing capacity of structures beyond the elastic range. For practical problems, the direct methods lead to nonlinear convex optimization problems with a large number of variables and onstraints. If strength and loading are random quantities, the problem of shakedown analysis is considered as stochastic programming. This paper presents a method so called chance constrained programming, an effective method of stochastic programming, to solve shakedown analysis problem under random condition of strength. In this our investigation, the loading is deterministic, the strength is distributed as normal or lognormal variables. KW - Reliability of structures KW - Stochastic programming KW - Chance constrained programming KW - Shakedown analysis KW - Limit analysis Y1 - 2022 SN - 978-604-357-084-7 SP - 510 EP - 518 PB - Nha xuat ban Khoa hoc tu nhien va Cong nghe (Verlag Naturwissenschaft und Technik) CY - Hanoi ER - TY - CHAP A1 - Staat, Manfred T1 - Limit and shakedown analysis under uncertainty T2 - Proceedings International Conference on Advances in Computational Mechanics (ACOME) Y1 - 2012 N1 - International Conference on Advances in Computational Mechanics (ACOME), August 14-16, 2012, Ho Chi Minh City, Vietnam SP - 837 EP - 861 ER - TY - CHAP A1 - Bohrn, Ulrich A1 - Stütz, Evamaria A1 - Fleischer, Maximilian A1 - Schöning, Michael Josef A1 - Wagner, Patrick T1 - Living cell-based gas sensor system for the detection of acetone in air Y1 - 2012 SN - 978-3-9813484-2-2 U6 - http://dx.doi.org/10.5162/IMCS2012/3.2.3 SP - 269 EP - 272 ER - TY - CHAP A1 - Uibel, Thomas A1 - Blaß, Hans Joachim T1 - Load Carrying Capacity of Joints with Dowel Type Fasteners in Solid Wood Panels T2 - Proceedings. CIB-W18 Meeting 2006, Florence, Italy 2006 Y1 - 2006 SN - 0945-6996 N1 - Paper 39-7-5 SP - 1 EP - 10 ER - TY - CHAP A1 - Dilthey, Ulrich A1 - Schleser, Markus A1 - Hegger, Josef A1 - Voss, Stefan ED - Reinhardt, Hans W. T1 - Load-bearing behaviour of polymer-impregnated textiles in concrete T2 - Fifth International Workshop on High Performance Fiber Reinforced Cement Composites (HPFRCC 5) : Mainz, July 10 - 13, 2007. (RILEM proceedings. 53) Y1 - 2007 SN - 978-2-35158-046-2 SP - 183 EP - 192 PB - RILEM Publ. CY - Bagneux ER - TY - CHAP A1 - Schürmann, Volker A1 - Wollert, Jörg T1 - Location based Services in der Gebäudeautomation T2 - Wireless Technologies Kongress 2008: von der Technologie zur Anwendung ; [10. Kongress, 23. - 24. September 2008, Bochum] Y1 - 2008 SN - 978-3-89838-608-1 SP - 313 EP - 322 PB - Aka CY - Heidelberg ER - TY - CHAP A1 - Böhm, Stefan A1 - Hellmanns, Mark A1 - Backes, Andreas A1 - Dilger, Klaus T1 - Lock-in thermography based NDT of automotive parts T2 - Proceedings of the 3rd World Congress on Adhesion and Related Phenomena : WCARP-III, October 15 -18, 2006, Beijing, China Y1 - 2006 SP - 382 EP - 384 PB - Beijing Adhesion Society of China CY - Beijing ER - TY - CHAP A1 - Anthrakidis, Anette A1 - Rusack, Markus A1 - Schwarzer, Klemens T1 - Low effort measurement method of PTC-efficiency T2 - SolarPACES 2010 : the CSP conference: electricity, fuels and clean water from concentrated solar energy ; 21 to 24 September 2010, Perpignan, France Y1 - 2010 SP - 48 EP - 49 PB - Soc. OSC CY - Saint Maur ER - TY - CHAP A1 - Funke, Harald A1 - Börner, Sebastian A1 - Keinz, Jan A1 - Hendrick, P. A1 - Recker, E. T1 - Low NOx Hydrogen combustion chamber for industrial gas turbine applications“, 14th International Symposium on Transport Phenomena and Dynamics of Rotating Machinery T2 - ISROMAC-14 : the Forteenth International Symposium on Transport Phenomena and Dynamics of Rotating Machinery ; Honolulu, Hawaii, February 27 - March 02nd, 2012 Y1 - 2012 N1 - International Symposium on Transport Phenomena and Dynamics of Rotating Machinery ; (14 ; 2012.02.27-03.02 ; Honolulu, Hawaii) ER - TY - CHAP A1 - Dachwald, Bernd T1 - Low-Thrust Mission Analysis and Global Trajectory Optimization Using Evolutionary Neurocontrol: New Results T2 - European Workshop on Space Mission Analysis ESA/ESOC, Darmstadt, Germany 10 { 12 Dec 2007 N2 - Interplanetary trajectories for low-thrust spacecraft are often characterized by multiple revolutions around the sun. Unfortunately, the convergence of traditional trajectory optimizers that are based on numerical optimal control methods depends strongly on an adequate initial guess for the control function (if a direct method is used) or for the starting values of the adjoint vector (if an indirect method is used). Especially when many revolutions around the sun are re- quired, trajectory optimization becomes a very difficult and time-consuming task that involves a lot of experience and expert knowledge in astrodynamics and optimal control theory, because an adequate initial guess is extremely hard to find. Evolutionary neurocontrol (ENC) was proposed as a smart method for low-thrust trajectory optimization that fuses artificial neural networks and evolutionary algorithms to so-called evolutionary neurocontrollers (ENCs) [1]. Inspired by natural archetypes, ENC attacks the trajectoryoptimization problem from the perspective of artificial intelligence and machine learning, a perspective that is quite different from that of optimal control theory. Within the context of ENC, a trajectory is regarded as the result of a spacecraft steering strategy that maps permanently the actual spacecraft state and the actual target state onto the actual spacecraft control vector. This way, the problem of searching the optimal spacecraft trajectory is equivalent to the problem of searching (or "learning") the optimal spacecraft steering strategy. An artificial neural network is used to implement such a spacecraft steering strategy. It can be regarded as a parameterized function (the network function) that is defined by the internal network parameters. Therefore, each distinct set of network parameters defines a different network function and thus a different steering strategy. The problem of searching the optimal steering strategy is now equivalent to the problem of searching the optimal set of network parameters. Evolutionary algorithms that work on a population of (artificial) chromosomes are used to find the optimal network parameters, because the parameters can be easily mapped onto a chromosome. The trajectory optimization problem is solved when the optimal chromosome is found. A comparison of solar sail trajectories that have been published by others [2, 3, 4, 5] with ENC-trajectories has shown that ENCs can be successfully applied for near-globally optimal spacecraft control [1, 6] and that they are able to find trajectories that are closer to the (unknown) global optimum, because they explore the trajectory search space more exhaustively than a human expert can do. The obtained trajectories are fairly accurate with respect to the terminal constraint. If a more accurate trajectory is required, the ENC-solution can be used as an initial guess for a local trajectory optimization method. Using ENC, low-thrust trajectories can be optimized without an initial guess and without expert attendance. Here, new results for nuclear electric spacecraft and for solar sail spacecraft are presented and it will be shown that ENCs find very good trajectories even for very difficult problems. Trajectory optimization results are presented for 1. NASA's Solar Polar Imager Mission, a mission to attain a highly inclined close solar orbit with a solar sail [7] 2. a mission to de ect asteroid Apophis with a solar sail from a retrograde orbit with a very-high velocity impact [8, 9] 3. JPL's \2nd Global Trajectory Optimization Competition", a grand tour to visit four asteroids from different classes with a NEP spacecraft Y1 - 2007 ER - TY - CHAP A1 - Kuhnhenne, Markus A1 - Feldmann, Markus A1 - Döring, Bernd A1 - Spranger, Sascha T1 - Luftdichtheit im Stahlleichtbau - Gebäudehüllen in Sandwichbauweise T2 - Dichte Gebäudehülle, Thermografie und Wohnungslüftung : 2. Europäisches BlowerDoor-Symposium : 16.3. - 17.3. 2007, Kassel Y1 - 2007 SP - 121 EP - 134 PB - Energie + Umwelt-Zentrum 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 - http://dx.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 - TY - CHAP A1 - Giresini, Linda A1 - Butenweg, Christoph A1 - Andreini, M. A1 - De Falco, A. A1 - Sassu, M. T1 - Macro-elements identification in historic chapels: the case of St. Venerio Chapel in Reggiolo - Emilia Romagna T2 - 9th International Conference on Structural Analyses of Historical Conctruction, 14 - 17 October, 2014, Mexico City Y1 - 2014 SP - 1 EP - 12 ER -