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A nonparametric goodness-of-fit test for random variables with values in a separable Hilbert space is investigated. To verify the null hypothesis that the data come from a specific distribution, an integral type test based on a Cramér-von-Mises statistic is suggested. The convergence in distribution of the test statistic under the null hypothesis is proved and the test's consistency is concluded. Moreover, properties under local alternatives are discussed. Applications are given for data of huge but finite dimension and for functional data in infinite dimensional spaces. A general approach enables the treatment of incomplete data. In simulation studies the test competes with alternative proposals.
Ensuring access to water and sanitation for all is Goal No. 6 of the 17 UN Sustainability Development Goals to transform our world. As one step towards this goal, we present an approach that leverages remote sensing data to plan optimal water supply networks for informal urban settlements. The concept focuses on slums within large urban areas, which are often characterized by a lack of an appropriate water supply. We apply methods of mathematical optimization aiming to find a network describing the optimal supply infrastructure. Hereby, we choose between different decentral and central approaches combining supply by motorized vehicles with supply by pipe systems. For the purposes of illustration, we apply the approach to two small slum clusters in Dhaka and Dar es Salaam. We show our optimization results, which represent the lowest cost water supply systems possible. Additionally, we compare the optimal solutions of the two clusters (also for varying input parameters, such as population densities and slum size development over time) and describe how the result of the optimization depends on the entered remote sensing data.
The integration of sensors is one of the major tasks in embedded, control and “internet of things” (IoT) applications. For the integration mainly digital interfaces are used, starting from rather simple pulse-width modulation (PWM) interface to more complex interfaces like CAN (Controller Area Network). Even though these interfaces are tethered by definition, a wireless realization is highly welcome in many applications to reduce cable and connector cost, increase the flexibility and realize new emerging applications like wireless control systems. Currently used wireless solutions like Bluetooth, WirelessHART or IO-Link Wireless use dedicated communication standards and corresponding higher protocol layers to realize the wireless communication. Due to the complexity of the communication and the protocol handling, additional latency and jitter are introduced to the data communication that can meet the requirements for many applications. Even though tunnelling of other bus data like CAN data is generally also possible the latency and jitter prevent the tunnelling from being transparent for the bus system. Therefore a new basic technology based on dual-mode radio is used to realize a wireless communication on the physical layer only, enabling a reliable and real-time data transfer. As this system operates on the physical layer it is independent of any higher layers of the OSI (open systems interconnection) model. Hence it can be used for several different communication systems to replace the tethered physical layer. A prototype is developed and tested for real-time wireless PWM, SENT (single-edge nibble transmission) and CAN data transfer with very low latency and jitter.
Algorithmic design and resilience assessment of energy efficient high-rise water supply systems
(2018)
High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
Multi-analyte biosensors may offer the opportunity to perform cost-effective and rapid analysis with reduced sample volume, as compared to electrochemical biosensing of each analyte individually. This work describes the development of an enzyme-based biosensor system for multi-parametric determination of four different organic acids. The biosensor array comprises five working electrodes for simultaneous sensing of ethanol, formate, d-lactate, and l-lactate, and an integrated counter electrode. Storage stability of the biosensor was evaluated under different conditions (stored at +4 °C in buffer solution and dry at −21 °C, +4 °C, and room temperature) over a period of 140 days. After repeated and regular application, the individual sensing electrodes exhibited the best stability when stored at −21 °C. Furthermore, measurements in silage samples (maize and sugarcane silage) were conducted with the portable biosensor system. Comparison with a conventional photometric technique demonstrated successful employment for rapid monitoring of complex media.
Malaria infection remains a significant risk for much of the population of tropical and subtropical areas, particularly in developing countries. Therefore, it is of high importance to develop sensitive, accurate and inexpensive malaria diagnosis tests. Here, we present a novel aptamer-based electrochemical biosensor (aptasensor) for malaria detection by impedance spectroscopy, through the specific recognition between a highly discriminatory DNA aptamer and its target Plasmodium falciparum lactate dehydrogenase (PfLDH). Interestingly, due to the isoelectric point (pI) of PfLDH, the aptasensor response showed an adjustable detection range based on the different protein net-charge at variable pH environments. The specific aptamer recognition allows sensitive protein detection with an expanded detection range and a low detection limit, as well as a high specificity for PfLDH compared to analogous proteins. The specific feasibility of the aptasensor is further demonstrated by detection of the target PfLDH in human serum. Furthermore, the aptasensor can be easily regenerated and thus applied for multiple usages. The robustness, sensitivity, and reusability of the presented aptasensor make it a promising candidate for point-of-care diagnostic systems.
Im Rahmen des europäischen Verbundprojekts INSYSME wurden von den deutschen Partnern die Systeme IMES und INODIS zur Verbesserung des seismischen Verhaltens von ausgefachten Stahlbetonrahmen entwickelt. Ziel beider Systeme ist es, Stahlbetonrahmen und Ausfachung zu entkoppeln, anstatt die Tragfähigkeit durch aufwendige und kostspielige zusätzliche Bewehrungseinlagen zu erhöhen. Erste Ergebnisse des Systems IMES für Belastungen in und senkrecht zu der Wandebene werden vorgestellt.
Im Rahmen des europäischen Verbundprojekts INSYSME wurden von den deutschen Partnern die Systeme IMES und INODIS zur Verbesserung des seismischen Verhaltens von ausgefachten Stahlbetonrahmen entwickelt. Ziel beider Systeme ist es, Stahlbetonrahmen und Ausfachung zu entkoppeln, anstatt die Tragfähigkeit durch aufwendige und kostspielige zusätzliche Bewehrungseinlagen zu erhöhen. Erste Ergebnisse des Systems IMES für Belastungen in und senkrecht zu der Wandebene werden vorgestellt.
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.
Das Forschungsprojekt Produktionseffizienz in der Kleinserie (ProeK) erarbeitet kostengünstige und effiziente Lösungsansätze für Prozessketten im Zukunftsfeld der Elektromobilität. Das Teilprojekt Karosserie setzt diese Zielsetzung durch innovative und praxisorientierte Produkt- und Prozesskonzepte mit neuartigen bauteilintegrierten Vorrichtungsfunktionen (BiV) um. Im Teilprojekt Außenhaut sollen Toleranzen adaptiv durch Anpassungen der Prozessparameter sowie Bauteilmanipulation kompensiert werden.