TY - JOUR A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich T1 - System concept and realization of a scalable neurocomputing architecture JF - Systems Analysis Modelling Simulation N2 - This paper describes the realization of a novel neurocomputer which is based on the concepts of a coprocessor. In contrast to existing neurocomputers the main interest was the realization of a scalable, flexible system, which is capable of computing neural networks of arbitrary topology and scale, with full independence of special hardware from the software's point of view. On the other hand, computational power should be added, whenever needed and flexibly adapted to the requirements of the application. Hardware independence is achieved by a run time system which is capable of using all available computing power, including multiple host CPUs and an arbitrary number of neural coprocessors autonomously. The realization of arbitrary neural topologies is provided through the implementation of the elementary operations which can be found in most neural topologies. Y1 - 1999 SN - 0232-9298 SN - 1029-4902 VL - 35 IS - 4 SP - 399 EP - 419 PB - Gordon and Breach Science Publishers CY - Amsterdam ER - TY - JOUR A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich A1 - Krumbiegel, Dirk A1 - Walter, Peter A1 - Wickel, Jochen T1 - Visual information retrieval for 3D product identification: a midterm report JF - KI - Künstliche Intelligenz Y1 - 1999 SN - 1610-1987 SN - 0933-1875 VL - 13 IS - 1 SP - 64 EP - 67 PB - Springer CY - Berlin ER - TY - CHAP A1 - Elsen, Ingo T1 - A pixel based approach to view based object recognition with self-organizing neural networks T2 - IECON'98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society N2 - This paper addresses the pixel based classification of three dimensional objects from arbitrary views. To perform this task a coding strategy, inspired by the biological model of human vision, for pixel data is described. The coding strategy ensures that the input data is invariant against shift, scale and rotation of the object in the input domain. The image data is used as input to a class of self organizing neural networks, the Kohonen-maps or self-organizing feature maps (SOFM). To verify this approach two test sets have been generated: the first set, consisting of artificially generated images, is used to examine the classification properties of the SOFMs; the second test set examines the clustering capabilities of the SOFM when real world image data is applied to the network after it has been preprocessed to be invariant against shift, scale and rotation. It is shown that the clustering capability of the SOFM is strongly dependant on the invariance coding of the images. Y1 - 1998 SN - 0-7803-4503-7 U6 - http://dx.doi.org/10.1109/IECON.1998.724032 N1 - Aachen, 31 August 1998 - 04 September 1998 SP - 2040 EP - 2044 PB - IEEE CY - New York ER - TY - CHAP A1 - Elsen, Ingo A1 - Kraiss, Karl-Friedrich A1 - Krumbiegel, Dirk T1 - Pixel based 3D object recognition with bidirectional associative memories T2 - International Conference on Neural Networks 1997 N2 - This paper addresses the pixel based recognition of 3D objects with bidirectional associative memories. Computational power and memory requirements for this approach are identified and compared to the performance of current computer architectures by benchmarking different processors. It is shown, that the performance of special purpose hardware, like neurocomputers, is between one and two orders of magnitude higher than the performance of mainstream hardware. On the other hand, the calculation of small neural networks is performed more efficiently on mainstream processors. Based on these results a novel concept is developed, which is tailored for the efficient calculation of bidirectional associative memories. The computational efficiency is further enhanced by the application of algorithms and storage techniques which are matched to characteristics of the application at hand. Y1 - 1997 SN - 0-7803-4122-8 N1 - June 9 - 12, 1997, Westin Galleria Hotel Houston, Texas, USA. SP - 1679 EP - 1684 PB - IEEE CY - New York ER - TY - CHAP A1 - Dey, Thomas A1 - Elsen, Ingo A1 - Ferrein, Alexander A1 - Frauenrath, Tobias A1 - Reke, Michael A1 - Schiffer, Stefan ED - Makedon, Fillia T1 - CO2 Meter: a do-it-yourself carbon dioxide measuring device for the classroom T2 - PETRA 2021: The 14th PErvasive Technologies Related to Assistive Environments Conference N2 - In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway. KW - embedded hardware KW - sensor networks KW - information systems KW - education KW - do-it-yourself Y1 - 2021 SN - 9781450387927 U6 - http://dx.doi.org/10.1145/3453892.3462697 N1 - PETRA '21: The 14th PErvasive Technologies Related to Assistive Environments Conference Corfu Greece 29 June 2021- 2 July 2021 SP - 292 EP - 299 PB - Association for Computing Machinery CY - New York ER - TY - JOUR A1 - Elsen, Ingo A1 - Hartung, Frank A1 - Horn, Uwe A1 - Kampmann, Markus A1 - Peters, Liliane ED - Voas, Jeffrey T1 - Streaming technology in 3G mobile communication systems JF - Computer : innovative technology for computer professionals N2 - Third-generation mobile communication systems will combine standardized streaming with a range of unique services to provide high-quality Internet content that meets the specific needs of the rapidly growing mobile market. Y1 - 2001 SN - 0018-9162 SN - 1558-0814 VL - 34 IS - 9 Seiten SP - 46 EP - 52 PB - IEEE CY - New York ER - TY - CHAP A1 - Walter, Peter A1 - Elsen, Ingo A1 - Müller, Holger A1 - Kraiss, Karl-Friedrich T1 - 3D object recognition with a specialized mixtures of experts architecture T2 - IJCNN'99. International Joint Conference on Neural Networks. Proceedings N2 - Aim of the AXON2 project (Adaptive Expert System for Object Recogniton using Neuml Networks) is the development of an object recognition system (ORS) capable of recognizing isolated 3d objects from arbitrary views. Commonly, classification is based on a single feature extracted from the original image. Here we present an architecture adapted from the Mixtures of Eaqerts algorithm which uses multiple neuml networks to integmte different features. During tmining each neural network specializes in a subset of objects or object views appropriate to the properties of the corresponding feature space. In recognition mode the system dynamically chooses the most relevant features and combines them with maximum eficiency. The remaining less relevant features arz not computed and do therefore not decelerate the-recognition process. Thus, the algorithm is well suited for ml-time applications. Y1 - 1999 SN - 0-7803-5529-6 U6 - http://dx.doi.org/10.1109/IJCNN.1999.836243 SN - 1098-7576 N1 - Washington, DC 10-16.07.1999 SP - 3563 EP - 3568 PB - IEEE CY - New York ER - TY - CHAP A1 - Eggert, Mathias A1 - Zähl, Philipp M. A1 - Wolf, Martin R. A1 - Haase, Martin ED - Cooper, Kendra M.L. ED - Bucchiarone, Antonio T1 - Applying leaderboards for quality improvement in software development projects T2 - Software Engineering for Games in Serious Contexts N2 - Software development projects often fail because of insufficient code quality. It is now well documented that the task of testing software, for example, is perceived as uninteresting and rather boring, leading to poor software quality and major challenges to software development companies. One promising approach to increase the motivation for considering software quality is the use of gamification. Initial research works already investigated the effects of gamification on software developers and come to promising. Nevertheless, a lack of results from field experiments exists, which motivates the chapter at hand. By conducting a gamification experiment with five student software projects and by interviewing the project members, the chapter provides insights into the changing programming behavior of information systems students when confronted with a leaderboard. The results reveal a motivational effect as well as a reduction of code smells. KW - Leaderboard KW - Gamification KW - Software testing KW - Software development Y1 - 2023 SN - 978-3-031-33337-8 (Print) SN - 978-3-031-33338-5 (Online) U6 - http://dx.doi.org/10.1007/978-3-031-33338-5_11 SP - 243 EP - 263 PB - Springer CY - Cham ER - TY - CHAP A1 - Eichenbaum, Julian A1 - Nikolovski, Gjorgji A1 - Mülhens, Leon A1 - Reke, Michael A1 - Ferrein, Alexander A1 - Scholl, Ingrid T1 - Towards a lifelong mapping approach using Lanelet 2 for autonomous open-pit mine operations T2 - 2023 IEEE 19th International Conference on Automation Science and Engineering (CASE) N2 - Autonomous agents require rich environment models for fulfilling their missions. High-definition maps are a well-established map format which allows for representing semantic information besides the usual geometric information of the environment. These are, for instance, road shapes, road markings, traffic signs or barriers. The geometric resolution of HD maps can be as precise as of centimetre level. In this paper, we report on our approach of using HD maps as a map representation for autonomous load-haul-dump vehicles in open-pit mining operations. As the mine undergoes constant change, we also need to constantly update the map. Therefore, we follow a lifelong mapping approach for updating the HD maps based on camera-based object detection and GPS data. We show our mapping algorithm based on the Lanelet 2 map format and show our integration with the navigation stack of the Robot Operating System. We present experimental results on our lifelong mapping approach from a real open-pit mine. Y1 - 2023 SN - 979-8-3503-2069-5 (Online) SN - 979-8-3503-2070-1 (Print) U6 - http://dx.doi.org/10.1109/CASE56687.2023.10260526 N1 - 19th International Conference on Automation Science and Engineering (CASE), 26-30 August 2023, Auckland, New Zealand. PB - IEEE ER - TY - CHAP A1 - Tischbein, Franziska A1 - Kean, Kilian A1 - Vertgewall, Chris Martin A1 - Ulbig, Andreas A1 - Altherr, Lena T1 - Determination of the topology of low-voltage distribution grids using cluster methods T2 - 27th International Conference on Electricity Distribution (CIRED 2023) N2 - Due to the decarbonization of the energy sector, the electric distribution grids are undergoing a major transformation, which is expected to increase the load on the operating resources due to new electrical loads and distributed energy resources. Therefore, grid operators need to gradually move to active grid management in order to ensure safe and reliable grid operation. However, this requires knowledge of key grid variables, such as node voltages, which is why the mass integration of measurement technology (smart meters) is necessary. Another problem is the fact that a large part of the topology of the distribution grids is not sufficiently digitized and models are partly faulty, which means that active grid operation management today has to be carried out largely blindly. It is therefore part of current research to develop methods for determining unknown grid topologies based on measurement data. In this paper, different clustering algorithms are presented and their performance of topology detection of low voltage grids is compared. Furthermore, the influence of measurement uncertainties is investigated in the form of a sensitivity analysis. Y1 - 2023 SN - 978-1-83953-855-1 U6 - http://dx.doi.org/10.1049/icp.2023.0478 N1 - 27th International Conference on Electricity Distribution (CIRED 2023), 12-15 June 2023, Rome, Italy. SP - 1 EP - 5 PB - IEEE ER -