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Der Einsatz paralleler Hardware-Architekturen betrifft alle Software-Entwickler und -Entwicklerinnen: vom Supercomputer bis zum eingebetteten System werden Multi- und Manycore-Systeme inzwischen eingesetzt. Die Herausforderungen an das Software Engineering sind vielfältig. Zum einen ist (wieder) ein stärkeres Verständnis für die Hardware notwendig. Ohne eine skalierbare Partitionierung der Software und parallele Algorithmen bleibt die Rechenleistung ungenutzt. Zum anderen stehen neue Programmiersprachen im Vordergrund, die die Ausführung von parallelen Anweisungen ermöglichen.
Dieses Buch betrachtet unterschiedliche Aspekte bei der Entwicklung paralleler Systeme und berücksichtigt dabei auch eingebettete Systeme. Es verbindet Theorie und praktische Anwendung und ist somit für Studierende und Anwender in der Praxis gleichermaßen geeignet. Durch die programmiersprachenunabhängige Darstellung der Algorithmen können sie leicht für die eigene Anwendung angepasst werden. Viele praktische Projekte erleichtern das Selbststudium und vertiefen das Gelernte.
Simulation von Laserscannern in Pflanzenbeständen für die Entwicklung umfeldbasierter Funktionen
(2018)
Es werden drei Modellierungsansätze zur Simulation von Laserscannern in Pflanzenbeständen für die Entwicklung umfeldbasierter Fahrzeugfunktionen beschrieben. Das Sensorsignal der Distanzmessung wird dabei anhand realer Messwerte oder phänomenologisch und auf der Basis empirisch ermittelter Kennwerte in Abhängigkeit von objekt- und sensorspezifischen Einflussfaktoren abgebildet. Basierend auf den Methoden zur Simulation von Distanzmesssystemen der Open Source Simulationsumgebung Gazebo wurden die Modellierungsansätze als spezifische Sensor- und Umfeldmodelle implementiert. Die Modelle wurden insbesondere für den Einsatz an mobilen landwirtschaftlichen Arbeitsmaschinen und für die Anwendung in der Getreideernte optimiert.
Recent real-time networking developments have enabled ultra reliability, very low latency and high data rates in wired networks. Wireless networking developments have also shown that they can achieve very high data rates with consistency, but they still lack in providing ultra reliability and extremely low latency. Time Sensitive Networking (TSN) developments have brought these capabilities in Industry automation and Automotive industry too. Although TSN is standardized for wired networks for a long time, for wireless networks it will be standardized within the IEEE 802.11be standard for Wi-Fi and 3GPP Release 17 for 5G in the near future. This paper provides an overview of TSN in wired and wireless networks with the aim of comparing different simulators and presenting their offered functionality and shortcomings. These tools can be used to make oneself familiar with TSN algorithms, standards, and for the development and testing of time sensitive networks. Afterwards, the paper discusses open research questions for using TSN over wireless networks.
In modern times, closed-loop control systems (CLCSs) play a prominent role in a wide application range, from production machinery via automated vehicles to robots. CLCSs actively manipulate the actual values of a process to match predetermined setpoints, typically in real time and with remarkable precision. However, the development, modeling, tuning, and optimization of CLCSs barely exploit the potential of artificial intelligence (AI). This paper explores novel opportunities and research directions in CLCS engineering, presenting potential designs and methodologies incorporating AI. Combining these opportunities and directions makes it evident that employing AI in developing and implementing CLCSs is indeed feasible. Integrating AI into CLCS development or AI directly within CLCSs can lead to a significant improvement in stakeholder confidence. Integrating AI in CLCSs raises the question: How can AI in CLCSs be trusted so that its promising capabilities can be used safely? One does not trust AI in CLCSs due to its unknowable nature caused by its extensive set of parameters that defy complete testing. Consequently, developers working on AI-based CLCSs must be able to rate the impact of the trainable parameters on the system accurately. By following this path, this paper highlights two key aspects as essential research directions towards safe AI-based CLCSs: (I) the identification and elimination of unproductive layers in artificial neural networks (ANNs) for reducing the number of trainable parameters without influencing the overall outcome, and (II) the utilization of the solution space of an ANN to define the safety-critical scenarios of an AI-based CLCS.
Management of agricultural processes is often troubled by disconnections and data transfer failures. Limited cellular network coverage may prevent information exchange between mobile process participants.
The research projects KOMOBAR and ISOCom designed, implemented und field-tested a delay tolerant platform for robust communication in rural areas and challenging environments. An adaptable combination of infrastructure-based cellular networks and infrastructure-free multihop ad hoc communication (WLAN) leads to a variety of new communication opportunities. Temporal storage and forwarding of data on mobile farm machinery as well as dynamic platform configurations during process runtime strongly enhance reliability and robustness of data transfers.
We describe an automated approach, to easily track patients regaining their walking ability while recovering from neurological diseases like e.g. stroke. Based on captured gait data and objective measures derived out of it the rehabilitation process can be optimized and thus steered. In order to apply such system in clinical practice two key requirements have to be fulfilled: (i) the system needs to be applicable in terms of ease of use and performance; (ii) the derived measures need to be accurate.
Es ist davon auszugehen, dass weltweit etwa die Hälfte der industriell eingesetzten Wärme als Abwärme ungenutzt verloren geht (Quelle: Effiziente Energieversorgung durch Abwärme, Fachmagazin Energy 2.0, April 2012). Vor dem Hintergrund der Nachhaltigkeit und Energieeffizienz ist es eine verantwortungsvolle Aufgabe, diese ungenutzte Energieressource schrittweise zu erschließen. Für die bisherige Vernachlässigung verfügbarer Energiequellen gibt es spezifische Gründe, die erkannt und projektbezogen möglichst ausgeräumt werden müssen. Dazu hat die Hochschule Osnabrück in Kooperation mit dem Kompetenzzentrum Energie und dem Landkreis Osnabrück eine Studie erstellt.
Regionales Wärmekataster Industrie - ReWIn
Diese Konzeptstudie schafft durch eine vorangestellte Recherche der bereits entwickelten Methoden und Technologien zur Abwärmenutzung eine Grundlage zur Potenzialabschätzung und Aufstellung eines Wärmekatasters für den Landkreis Osnabrück.
In der Studie werden für die typisch energieintensiven Branchen des Landkreises methodische Berechnungsansätze mit statistischen, branchenbezogenen Energiekennwerten und vorerst anonymisierten Unternehmensdaten neuartig kombiniert, um eine regionale Potenzialkarte der Abwärme zu erstellen. Die Studie wurde vom Europäischen Fonds für regionale Entwicklung (EFRE) gefördert.
The Internet of Things (IoT) is the enabler for new innovations in several domains. It allows the connection of digital services with physical entities in the real world. These entities are devices of different categories and sizes range from large machinery to tiny sensors. In the latter case, devices are typically characterized by limited resources in terms of computational power, available memory and sometimes limited power supply. As a consequence, the use of security algorithms requires of them to work within the limited resources. This means to find a suitable implementation and configuration for a security algorithm, that performs properly on the device, which may become a challenging task. On the other side, there is the desire to protect valuable assets as strong as possible. Usually, security goals are recorded in security policies, but they do not consider resource availability on the involved device and its power consumption while executing security algorithms. This paper presents an IoT security configuration tool that helps the designer of an IoT environment to experiment with the trade-off between maximizing security and extending the lifetime of a resource constrained IoT device. The tool is controlled with high-level description of security goals in the form of policies. It allows the designer to validate various (security) configurations for a single IoT device up to a large sensor network.
Process modeling languages help to define and execute processes and workflows. The Business Process Model and Notation (BPMN) 2.0 is used for business processes in commercial areas such as banks, shops, production and supply industry. Due to its flexible notation, BPMN is increasingly being used in non-traditional business process domains like Internet of Things (IoT) and agriculture. However, BPMN does not fit well to scenarios taking place in environments featuring limited, delayed, intermittent or broken connectivity. Communication just exists for BPMN - characteristics of message transfers, their priorities and connectivity parameters are not part of the model. No backup mechanism for communication issues exists, resulting in error-prone and failing processes. This paper introduces resilient BPMN (rBPMN), a valid BPMN extension for process modeling in unreliable communication environments. The meta model addition of opportunistic message flows with Quality of Service (QoS) parameters and connectivity characteristics allows to verify and enhance process robustness at design time. Modeling of explicit or implicit, decision-based alternatives ensures optimal process operation even when connectivity issues occur. In case of no connectivity, locally moved functionality guarantees stable process operation. Evaluation using an agricultural slurry application showed significant robustness enhancements and prevented process failures due to communication issues.
The effects of reaction parameters on Hurn:xwiley:23670932:media:cptc202000216:cptc202000216-math-0001 production from ethanol photocatalysis in the gas phase have been investigated. The photocatalytic activity evolves from an early mass‐transfer limited regime to an independent one at later irradiation times, which is interpreted in terms of a photocatalytic site activity distribution. Ethanol molar fraction exhibits two different domains, with Hurn:xwiley:23670932:media:cptc202000216:cptc202000216-math-0002 production increasing up to a molar fraction of 0.12, beyond which it plateaus. Hurn:xwiley:23670932:media:cptc202000216:cptc202000216-math-0003 :AcH ratios are very sensitive to reaction conditions, reaching 1.8 at low reactant flows. UV light is converted to Hurn:x-wiley:23670932:media:cptc202000216:cptc202000216-math-0004 with an efficiency of nearly 3 %.