TY - GEN A1 - Schmalenberg, Falko A1 - Vandenhouten, Ralf T1 - A DFD Based Approach to Model Data Processing Solutions T2 - Wissenschaftliche Beiträge 2016 N2 - This paper introduces procedures, which facilitate the development of as well as the linking between modular data processing processes into different and versatile system solutions. Based on the concept of data flow diagrams (Yourdon 1989), processes and data flows are used. With the ability of a process to harness any amount of in- and outputs with different sources and destinations, it is possible to model any conceivable data processing problem. By aggregating a diagram as a new process, it becomes possible to outsource partial process chains to different abstraction levels. As a result, even very complex solutions can be modeled and explained in a clear way. The introduced uniform termination flow while traversing the graph creates a good readability, which also makes it possible to quickly detect weaknesses. Moreover, this solution is comprehensive and advances the cooperation in teams and development. N2 - In diesem Beitrag wird ein Verfahren vorgestellt, welches die Entwicklung und Verknüpfung modularer Datenverarbeitungsprozesse zu beliebigen, unterschiedlichen Gesamtlösungen ermöglicht. Aufbauend auf dem Konzept der Datenflussdiagramme (Yourdon 1989) kommen Prozesse und Datenströme zum Einsatz. Dabei kann ein Prozess beliebig viele Inputs und Outputs mit unterschiedlichen Quellen und Senken haben und jedes denkbare Datenverarbeitungsproblem modelliert werden. Durch das verschachtelte Modellieren dieser Diagramme und deren Aggregation zu neuen Prozessen können Teilprozessketten auf unterschiedlichen Abstraktionsebenen ausgelagert werden. So lassen sich auch äußerst komplexe Lösungen übersichtlich modellieren, darstellen und erklären. Eine einheitliche Ablaufregel bei der Traversierung macht dieses Verfahren gut lesbar und lässt gegebenenfalls vorhandene Schwachstellen schnell erkennen. Zudem ist es verständlich und fördert die Zusammenarbeit sowie die gemeinsame Entwicklung. Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-5314 SN - 0949-8214 VL - 20 SP - 31 EP - 36 ER - TY - JOUR A1 - Vandenhouten, Ralf A1 - Lambertz, Manfred A1 - Langhorst, Peter A1 - Grebe, Reinhard T1 - Nonstationary time-series analysis applied to investigation of brainstem system dynamics JF - IEEE Transactions on Biomedical Engineering (T-BME) N2 - Previous investigations of the dynamic organization of the lower brainstem and its relation to peripheral and other central nervous systems were predominantly performed by linear methods. These are based on time-averaging algorithms, which merely can be applied to stationary signal intervals. Thus, the current concept of the common brainstem system (CBS) in the reticular formation (RF) of the lower brainstem and basic types of its functional organization have been developed. Here, the authors present experiments where neuronal activities of the RF and the nucleus tractus solitarii (NTS, first relay station of baroreceptor afferents) were recorded together with related parameters of electroencephalogram (EEG), respiration, and cardiovascular system. The RF neurons are part of the CBS, which participates in regulation and coordination of cardiovascular, respiratory, and motor systems, and vigilance. The physiological time series, thus acquired, yield information about the internal dynamic coordination of the participating regulation processes. The major problem in evaluating these data is the nonlinearity and nonstationarity of the signals. The authors used a set of especially designed time resolving methods to evaluate nonlinear dynamic couplings in the interaction between CBS neurons and cardiovascular signals, respiration and the EEG, and between NTS neurons (influenced by baroreceptor afferents) and CBS neurons. KW - time series analysis KW - neuron KW - radio frequency KW - electroencephalography KW - cardiology KW - central nervous system KW - relay KW - cardiovascular system KW - nonlinear dynamical system KW - design methodology Y1 - 2000 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-9337 SN - 1558-2531 VL - 47 IS - 6 SP - 729 EP - 737 ER - TY - CHAP A1 - Mietzner, Dana A1 - Vandenhouten, Ralf A1 - Hartmann, Frank ED - Tambouris, Efthimios T1 - Collaborative Problem Solving for Regional Development? – A New Approach of Public Participation T2 - Electronic Government and Electronic Participation N2 - In this paper, we present a concept prototype for a socio-technical assistant (s.TAS) as a collaborative problem-solving approach to support the regional development in a selected rural district. The presented concept considers insides from citizen participation as an open government instrument and strongly incorporates collaborative value creation to address regional development issues. The presented approach incorporates citizens and other regional stakeholders (e.g., companies, organizations, associations) as problem-solvers and strongly enables regional stakeholders and the public administration to develop solutions jointly as an ongoing learning process. In this sense, s.TAS addresses participation approaches and elaborates participation to collaboration. For the development of this participatory problem-solving approach, we conducted (1) a broad literature review on participatory approaches and (2) we implemented a qualitative, collaborative research approach with participants from different stakeholder groups. In several workshop rounds, supported by interviews and surveys we developed a concept prototype for the socio-technical assistant s.TAS, which is a technical, smart system, which supports information, communication, participation and collaboration in the selected region. Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-9177 SN - 978-1-61499-570-8 SP - 19 EP - 26 PB - IOS Press CY - Amsterdam ER - TY - JOUR A1 - Vandenhouten, Ralf A1 - Wendlandt, Ole T1 - High-precision Optical Position Measurement in Indoor Environments BT - A method for locating people by capturing multiple optical markers with a mobile device JF - Optik & Photonik N2 - Indoor localization is still a challenge today. Conventional methods based on satellite navigation, like GPS, can only be used outdoors. On the other hand, radio signal architectures, like WiFi or NFC, require high cost infrastructure to be installed inside the building. In collaboration with Ixellence GmbH, the research group for telematics of the University of Applied Science Wildau is developing a new inexpensive solution based on the camera of a mobile device. This approach only requires the availability of multiple identifiable landmarks that can be installed cost-efficiently in an indoor environment. Our investigations show that this method is very accurate and can produce repeatable, robust results. Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-9305 SN - 1863-1460 VL - 10 IS - 3 SP - 24 EP - 27 ER - TY - JOUR A1 - Vandenhouten, Ralf A1 - Selz, Miriam A1 - Doktor, Michael T1 - Werkzeuge für die gezielte Parodontalbetreuung mit individueller Risikoanalyse JF - PN Parodontologie Nachrichten N2 - Mit neuer Methode lässt sich die Wahrscheinlichkeit einer fortschreitenden Parodontitis abschätzen. Y1 - 2005 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-9355 UR - https://media.zwp-online.info/archiv/pub/sim/pn/2005/pn0205/pn0205_08_selz_dexcel.pdf SN - 1613-7191 VL - 2005 IS - 2 ER - TY - CHAP A1 - Metzler, Volker H. A1 - Vandenhouten, Ralf A1 - Krone, Jörg A1 - Grebe, Reinhard T1 - Unsupervised image segementation by stochastic reconstruction T2 - Proceedings of SPIE N2 - To segment complex and versatile image data from different modalities it is almost impossible to achieve satisfying results without the consideration of contextual information. In this approach, image segmentation is regarded as a high- dimensional optimization task, that can be solved by stochastical methods like evolutionary algorithms (EA). Initially, the iterative algorithm is provided with a set of good-quality sample segmentations. An efficient EA-based learning strategy generates a segmentation for a given target image from the provided samples. This two-level process consists of a global image-based optimization whose convergence is enhanced by locally operating pixel-based Boltzmann processes which restrict the search space to reasonable subsets. The stochastic reconstruction extracts the relevant information from the samples in order to adapt it onto the current segmentation problem, which results in a consistent labeling for the target image. The algorithm works unsupervised, because the range of possible labels and their contextual interpretation is provided implicitly by the sample segmentations. To prove the usefulness of the method experimental results based on both, reproducible phantom images and physiological NMR scans are presented. Moreover, an analysis of the basic segmentation and convergence properties is provided. Y1 - 1998 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-9329 SN - 1996-756X VL - 3338 ER - TY - GEN A1 - Bezruk, Valeriy A1 - Gedat, Egbert A1 - Holzheimer, Katja A1 - Vandenhouten, Ralf T1 - Automated recognition of sleep stages by electroencephalograms T2 - Wissenschaftliche Beiträge 2015 N2 - The assessment of different sleep stages and their disorders in diseases is an important part of telematic medicine. With an electroencephalogram, the different stages of sleep can be monitored and classified with respect to brain activity. By means of modern data management such as the patient monitor ixTrend, for example, the data can be recorded for long sleep phases and evaluated by a computer using appropriate software, such as Dataplore. Here, a new mathematical model for the automated classification of sleep stages is introduced. The statistical method of autocorrelation, applied to six known sleep stages, was extended by one new class for unknown signals. Due to this new class, it is not necessary to sort all recorded EEG signals into one of the known classes, thereby, minimising the probability of errors. Further, the dependence of the error probability on the duration of the analysed EEG signal was assessed. A minimal error probability of pmin = 0.15 was detected. Exemplary data for one patient are reported. N2 - Die Beurteilung der verschiedenen Schlafphasen und deren Störungen bei Erkrankungen spielt eine wichtige Rolle in der telematischen Medizin. Mit einem Elektroenzephalogramm können die Schlafphasen überwacht und in verschiedene Klassen der Hirnaktivität eingeteilt werden. Durch moderne Methoden des Datenmanagements, wie etwa den Patientenmonitor ixTrend, können die Daten über längere Schlafphasen aufgezeichnet und am Computer mit geeigneter Software, etwa Dataplore, analysiert werden. Hier wird ein neues mathematisches Modell zur automatischen Klassifizierung der Schlafphasen vorgestellt. Die statistische Methode der Autokorrelation, angewendet auf sechs bekannte Schlafphasen, wurde erweitert um eine neue Klasse nicht zuordenbarer Muster. Durch diese neue Klasse wird es vermieden, jedes aufgezeichnete EEG-Muster in eine der bekannten Klassen hineinzuzwingen. Dadurch wird der Fehler bei der Zuordnung verringert. Weiter wird der Einfluss der Länge des analysierten EEG auf die Fehlerquote der Zuordnung untersucht. Es zeigte sich eine minimale Fehlerquote von pmin = 0,15. Es werden beispielhafte Daten eines Patienten gezeigt. Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-3552 SN - 0949-8214 VL - 19 SP - 39 EP - 43 ER - TY - CHAP A1 - Pulwer, Silvio A1 - Fiebelkorn, Richard A1 - Zesch, Christoph A1 - Steglich, Patrick A1 - Villringer, Claus A1 - Villasmunta, Francesco A1 - Gedat, Egbert A1 - Handrich, Jan A1 - Schrader, Sigurd A1 - Vandenhouten, Ralf T1 - Endoscopic orientation by multimodal data fusion T2 - Proc. SPIE 10931, MOEMS and Miniaturized Systems XVIII N2 - To improve the feasibility of endoscopic inspection processes we developed a system that provides online information about position, orientation and viewing direction of endoscopes, to support the analysis of endoscopic images and to ease the operational handling of the equipment. The setup is based on an industrial endoscope consisting of a camera, various MEMS and multimodal data fusion. The software contains algorithms for feature and geometric structure recognition as well as Kalman filters. To track the distal end of the endoscope and to generate 3D point cloud data in real time the optical and photometrical characteristics of the system are registered and the movement of the endoscope is reconstructed by using image processing techniques. KW - endoscope KW - orientation KW - Kalman filter KW - visual odometry KW - mems KW - gyroscope KW - accelerometer Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:526-opus4-11420 SN - 1996-756X ER -