000 Informatik, Informationswissenschaft, allgemeine Werke
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Das Buch richtet sich an Studierende der Informatik oder verwandter Studiengänge und enthält Übungsaufgaben mit Lösungen aus Gebieten, die typischerweise in den ersten Semestern als Grundlagen behandelt werden. Ausgenommen ist der Bereich des Programmierens. Das Buch ergänzt den Grundkurs Informatik mit Übungen zu ausgewählten Kapiteln, ist aber auch in Kombination mit anderen Lehrbüchern verwendbar.
Parameter free Non-intrusive Load Monitoring (NILM) algorithms are a major step toward real-world NILM scenarios. The identification of appliances is the key element in NILM. The task consists of identification of the appliance category and its current state. In this paper, we present a param- eter free appliance identification algorithm for NILM using a 2D representation of time series known as unthresholded Recurrence Plots (RP) for appliance category identification. One cycle of voltage and current (V-I trajectory) are transformed into a RP and classified using a Spacial Pyramid Pooling Convolutional Neural Network architecture. The performance of our approach is evaluated on the three public datasets COOLL, PLAID and WHITEDv1.1 and compared to previous publications. We show that compared to other approaches using our architecture no initial parameters have to be manually tuned for each specific dataset.
Stuttering is a complex speech disorder identified by repetitions, prolongations of sounds, syllables or words and blockswhile speaking. Specific stuttering behaviour differs strongly,thus needing personalized therapy. Therapy sessions requirea high level of concentration by the therapist. We introduce STAN, a system to aid speech therapists in stuttering therapysessions. Such an automated feedback system can lower the cognitive load on the therapist and thereby enable a more consistent therapy as well as allowing analysis of stuttering over the span of multiple therapy sessions.
Mobile-access edge clouds provide distributed com-pute capacities for low-latency applications. 5G technology willpave the way for such mobile deployment scenarios. In thispaper, we propose an edge cloud infrastructure that supportslow-latency video analysis connected with bandwidth reductionfor a moving group of persons. As example, we consider a mobilebody camera scenario that monitors the situation in a certain areaand transmits it to an operations center. Our discussion focuseson three aspects: mobility support, low-latency video processing,and bandwidth reduction. For this, we propose a mobile edgecloud infrastructure with a central cloud. In order to optimizevideo processing we optimize the edge cloud device assignmentof the cameras depending on their movement by reassigning itto another cloud device. This requires live migration of ongoingvideo analysis between edge devices. Finally we discuss the useof a mobile central cloud.
Zahlensysteme und binäre Arithmetik – Nachricht und Information – Codierung und Datenkompression – Verschlüsselung – Schaltalgebra, Schaltnetze und Elemente der Computerhardware – Rechnerarchitekturen – Rechnernetze – Betriebssysteme – prozedurale und objektorientierte Programmierung (C und Java) – Automatentheorie und formale Sprachen – Berechenbarkeit und Komplexität – Suchen und Sortieren – Bäume und Graphen – Software-Engineering – Datenbanken – Anwendungsprogrammierung im Internet (HTML, CSS, JavaScript und PHP) – Deep Learning mit neuronalen Netzen
Forschungsbericht 2012
(2013)
Forschungsbericht 2013
(2014)
Forschungsbericht 2014
(2015)
Forschungsbericht 2015
(2016)
