The main aim of this master’s thesis is to provide online path correction of 6 – axis robot leaded by an external distance measuring sensor interface. First part is describing the actual state and required options of some robot manufacturers. Next part justifies selection and is describing the real robotic cell. Third part is focused on programming of path correction of Kuka KR16 based on generated signal and also based on signal from distance sensor interface. There is also described the communication between PLC and robot and how to display data from robot to HMI. Last part is focused on data analysis and is describing some problems discovered by application of path correction.

Moderne Sensorik, Modellierungs- und Optimierungsmethoden im Rohstoffgewinnungsprozess liefern Daten in “Echtzeit” und bieten Entscheidungsassistenz in der Betriebssteuerung und Kurzfristplanung. In den vergangenen Jahren wurden sogenannte „Closed- Loop-Ansätze“ entwickelt, um diese Informationen in Kombination mit moderner Datenverarbeitungstechnologie für eine verbesserte Produktionssteuerung in der Rohstoffgewinnung nutzbar zu machen. Der Beitrag stellt ein Projekt vor, das sich genau dieser Entwicklung widmet, das im Europäischen Rahmenprogramm Horizon 2020 geförderte Projekt Real-Time Mining. Der Fokus des Projektes liegt auf der Gewinnung bergbaugeologisch komplexer Lagerstätten unter Anwendung hoch-selektiver Gewinnungsszenarien. Der Aufbau des Projektes, das Projektziel, die einzelnen Arbeitspakete und Schlüsseltechnologien werden kurz dargestellt. An zwei ausgewählten Beispielen wird auf zwei Hauptkomponenten von Real-Time Mining, die Aktualisierung der Lagerstättenmodelle unter Einbeziehung von Online-Sensorik und die Optimierung der Entscheidungsfindung im Produktionsprozess näher eingegangen.

Mobile laser scanning systems automate the acquisition of 3D point clouds of environments. The mapping systems are commonly mounted on cars or ships. This paper presents a flexible mapping solution mounted on an underground vehicle that is able to map underground mines in 3D in walking speeds. A clever choice of hard- and software enables the system to generate 3D maps without using GPS (global positioning system) information and without relying on highly expensive IMU (inertial measurement unit) systems.

Smartphones and other Internet of Things devices have become a rapidly growing topic. Along with the growth comes new technologies, likeWeb Real- Time Communication (WebRTC), that enables richer services to be built for the devices. These kind of services are typically consumed on-demand, in shorter periods at a time. Likewise have cloud computing exploded in popularity during the last years. Cloud computing offers compelling advantages, such as rapid elasticity and on-demand usage, that allow servers' resource utilization to be more effcient. The flexibility of allocating and releasing resources swiftly as they are required, enables services that run in the cloud to adopt to ephemeral workloads. The research in this thesis targets a real-time video streaming service that is based on WebRTC. Incoming streams are handled by Multipoint Control Units (MCUs) that have the responsibility to redistribute the incoming streams to the consumers. Scaling horizontally aligns well with the idea of cloud computing. The work in this thesis is based on the extreme case where each of the incoming streams are handled by a separate MCU. The thesis presents the process of finding a exible Cloud Execution Environment (CEE) for the streaming service. The process includes an analysis of the streaming service's requirements, an evaluation of existing solutions, and an implementation. Moreover, the thesis includes a discussion about the capabilities of the implemented system. The result of the thesis is a CEE upon which the streaming service can be deployed and managed. The developed CEE allows any workload that is encapsulated within a Docker container to be orchestrated, not exclusively the streaming service, which makes the implementation viable to other cloud computing projects. / Användandet av smartphones och andra "Internet of Things"-enheter ökar snabbt. I takt med ökningen, så släpps nya tekniker som möjliggör utveckling av mer avancerade tjänster. Ett exampel är Web Real-Time Communication (WebRTC). Den här typen av tjänster konsumeras oftast sporadiskt under kortare tidsintervall. även cloud computing har drastiskt ökat i popularitet under de senaste åren. Hög elasticitet samt möjligheten att allokera datorresurser på begäran har medfört att utnyttjandegraden av datorers kapacitet kan höjas. Flexibiliteten att snabbt kunna allokera och frigöra resurser möjliggör att tjänster kan utvecklas för att utnyttja upp- och nerskalningsm öjligheterna bättre, även för kortvariga lastökningar. Forskningen i rapporten riktar in sig på ett system för videoströmning mellan användare i realtid baserat påa WebRTC. Inkommande strömmar hanteras av Multipoint Control Units (MCUs), som har som uppgift att vidaredistribuera strömmarna till andra användare som vill spela upp strömmen. Horisontell skalning och cloud computing har mycket gemensamt. Det underliggande arbetet till den här rapporten fokuserar på ett extremfall, där varje inkommande videoström hanteras av en enskild MCU. Den här uppsatsen presenterar den process som användes för att ta fram en lämplig molnlösning för strömningssystemet. Processen beståar av en kravanalys av strömningssystemet, en jämförelse av befintliga lösningar samt en implementation av en molnlösning. Slutligen så innehåller uppsatsen en utvärdering av implementationen. Resultatet av uppsatsen är en molnlösning som videoströmningssystemet kan driftsättas och köras på. Molnlösningen är inte begränsad till videoströmningssystemet utan klarar av att hantera alla applikationer som paketerats inuti Docker-kapslar. Molnlösningen är så pass generell att den kan användas till andra projekt inom cloud computing.

Introduction. The aim of the study was to introduce a new BKV PCR protocol in our centre and to verify its accuracy as well as to assess the prevalence, risk factors of BK virus replication, course of BKV infection and therapeutic approaches in simultaneous pancreas and kidney (SPK) recipients in order to design a screening protocol. Methods. The results analysed by both Affigene® and Transplantation Virology, Basel PCR protocols were compared. Thereafter 183 SPK patients were examined to assess the prevalence of BK viremia, viruria and BKVN and to identify the risk factors of BKV replication. The cases of retransplantation after a graft loss due to BKVN were retrospectively described. Results. 100 of results were analysed according to the Affigene ® and Transplantation Virology, Basel PCR protocols with the accordance of 95%, Rho = 0,946, 95% CI: 0.920 - 0.963, P<0,0001, Bland-Altman plot analyses: bias Basel PCR protocol/Affigene® BKV trender: -0,1 (mean) *±1.96 SD: -1,6 - 1,3] for both methods. Point-prevalence was assessed in 183 patients; Viruria found in 17,3 %, viremia in 3.8% of patients. High-level viruria >107 copies/mL detected in 3,7% of patiets, high-level virémia >104 in 1,6% of patients simultaneously with high-level viruria. BKVN was found in 0,5% of patients. Diabetes duration...

In den letzten Jahren erreichten viele neue (emerging) Viren Europa, die zum Teil (z.T.) zoonotisch auf den Menschen übertragbar sind. So musste man sich mit Geflügel- und Schweinegrippe, Blauzungenkrankheit, Infektiöser Anämie der Einhufer oder auch SARS (severe acute respiratory syndrome) auseinandersetzen. Bedingt durch verschiedene Faktoren, wie Klimawandel oder zunehmende Globalisierung und damit einhergehendem Verkehr zwischen den Kontinenten verbesserten sich auch die Bedingungen für die Virusverbreitung, so dass viele für Deutschland untypische Krankheitserreger auch hier auftraten. Das West-Nil-Virus (WNV) ist in Europa bereits endemisch verbreitet und könnte somit eine besondere Gefahr für Deutschland darstellen. Es ist ein bekannter Zoonose-Erreger, und sein Eintrag und die rasche Verbreitung des Virus in Amerika 1999 zeigten wie gefährlich neue Viren in naiven Populationen sein können. Über die Verbreitung des Virus in Deutschland gibt es nur wenige Studien z.B. des Robert-Koch-Instituts (LINKE et al. 2007a) und des Friedrich-Loeffler-Instituts (SEIDOWSKI et al. 2010), wobei in keiner Studie tote Vögel als Untersuchungsmaterial genutzt wurden. Da das WNV in Amerika mit einem auffälligen Vogelsterben einherging, ist es naheliegend, den Virusnachweis zuerst bei toten Vögeln zu erbringen.

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Indiana University-Purdue University Indianapolis (IUPUI) / This project aims to develop a cloud-based platform that integrates sensors with business intelligence for real-time energy management at the plant level. It provides facility managers, an energy management platform that allows them to monitor equipment and plant-level energy consumption remotely, receive a warning, identify energy loss due to malfunction, present options with quantifiable effects for decision-making, and take actions, and assess the outcomes. The objectives consist of: 1. Developing a generic platform for the monitoring energy consumption of industrial equipment using sensors 2. Control the connected equipment using an actuator 3. Integrating hardware, cloud, and application algorithms into the platform 4. Validating the system using an Energy Consumption Forecast scenario A Demo station was created for testing the system. The demo station consists of equip- ment such as air compressor, motor and light bulb. The current usage of these equipment is measured using current sensors. Apart from current sensors, temperature sensor, pres- sure sensor and CO2 sensor were also used. Current consumption of these equipment was measured over a couple of days. The control system was tested randomly by turning on equipment at random times. Turning on the equipment resulted in current consumption which ensured that the system is running. Thus, the system worked as expected and user could monitor and control the connected equipment remotely.

No description available.

Real-time systems surround every facet of our lives. They can be found in anything from everyday objects like mobile phones and washing machines to objects critical to life and infrastructure including heart rate monitors and nuclear power plants. As time progresses these systems are becoming ever more complex. To cope with the increase in complexity, developers and researchers are turning to model driven development as a solution. One modeling language aimed specifically at real-time systems is UML-RT. This thesis proposes an algorithm that for a significant subset of UML-RT is able to provide a worst-case execution time analysis for capsules at a model level. Having access to the worst-case execution times allows developers to at an early stage reason about a given system. This allows for better resource allocation as well as the ability to perform scheduling analysis. Development of the algorithm was performed iteratively using the constructive research approach. We began by first gaining an understanding of the theory. We then successively developed a theoretical algorithm selecting one or a few UML-RT entities at a time. With each iteration the algorithm was redefined to incorporate the new entities. At the end of the development, we created an implementation of the algorithm as an Eclipse Modeling Framework plug-in using Java. We then created a set of hard coded capsule models which were used to validate the algorithm.