Refine
Year of publication
Document Type
- Conference Proceeding (25)
- Article (peer reviewed) (10)
- Book (8)
- Report (2)
- Part of a Book (1)
Is part of the Bibliography
- no (46)
Keywords
- Augmented Reality (AR) (4)
- Mobile Robot (4)
- Robotic Research (4)
- Cognitive Mapping (3)
- Grundlagen Informatik (3)
- Machine Learning (3)
- Sonar Sensor (3)
- Computer vision (2)
- Forschung (2)
- Informatik (2)
Institute
Forschungsbericht 2013
(2014)
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.
Das Buch bietet eine umfassende und praxisorientierte Einführung in die wesentlichen Grundlagen und Konzepte der Informatik. Es umfasst den Stoff, der typischerweise in den ersten Semestern eines Informatikstudiums vermittelt wird, vertieft Zusammenhänge, die darüber hinausgehen und macht sie verständlich. Die Themenauswahl orientiert sich an der langfristigen Relevanz für die praktische Anwendung. Praxisnah und aktuell werden die Inhalte für Studierende der Informatik und verwandter Studiengänge sowie für im Beruf stehende Praktiker vermittelt. Die vorliegende fünfte Auflage wurde grundlegend überarbeitet und aktualisiert.
Data fusion plays a central role in more and more automotive applications, especially for driver assistance systems. On the one hand the process of data fusion combines data and information to estimate or predict states of observed objects.
On the other hand data fusion introduces abstraction layers for data description and allows building more flexible and modular systems.The data fusion process can be divided into a low-level processing (tracking and object discrimination) and a high level processing (situation assessment).
High level processing becomes more and more the focus of current research as different assistance applications will be combined into one comprehensive assistance system.
Different levels/strategies for data fusion can be distinguished: Fusion on raw data level, fusion on feature level and fusion on decision level.
All fusion strategies can be found in current driver assistance implementations.
The paper gives an overview of the different fusion strategies and shows their application in current driver assistance systems. For low level processing a raw data fusion approach in a stereo video system is described, as an example for feature level fusion the fusion of radar and camera data for tracking is explained.
As an example for a high level fusion algorithm an approach for a situation assessment based on multiple sensors is given. The paper describes practical realizations of these examples and points out their potential to further increase traffic safety with reasonably low cost for the overall system.
Zahlensysteme und binäre Arithmetik
Nachricht und Information
Codierung und Datenkompression
Verschlüsselung
Schaltalgebra, Schaltnetze und Elemente der Computerhardware
Rechnerarchitekturen
Rechnernetze
Betriebssysteme
Datenbanken
Automatentheorie und formale Sprachen
Berechenbarkeit und Komplexität
Suchen und Sortieren
Bäume und Graphen
prozedurale und objektorientierte Programmierung (C und Java)
Anwendungsprogrammierung im Internet (HTML, CSS, JavaScript und PHP)
Software-Engineering
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
Das Buch bietet eine umfassende und praxisorientierte Einführung in die wesentlichen Grundlagen und Konzepte der Informatik. Es umfasst den Stoff, der typischerweise in den ersten Semestern eines Informatikstudiums vermittelt wird, vertieft Zusammenhänge, die darüber hinausgehen und macht sie verständlich. Die Themenauswahl orientiert sich an der langfristigen Relevanz für die praktische Anwendung. Praxisnah und aktuell werden die Inhalte für Studierende der Informatik und verwandter Studiengänge sowie für im Beruf stehende Praktiker vermittelt.
The IT architecture for meter reading and utility services is at the core of new business models and has a decisive role as an enabler for resource efficiency measures. The communication architecture used by those services has significant impact on cost, flexibility and speed of new service rollout. This article describes how the dominant system model for meter reading came about, what alternative models exist, and what trade-offs those models have for rollout of new services by different stakeholders. Control of a self learning home automation system by dynamic tariff information (Real-Time-Pricing) is given as an application example.
Fault and anomaly detection in district heating substations: A survey on methodology and data sets
(2023)
District heating systems are essential building blocks for affordable, low-carbon heat supply. Early detection and elimination of faults is crucial for the efficiency of these systems and necessary to achieve the low temperatures targeted for 4th generation district heating systems. Especially methods for fault and anomaly detection in district heating substations are currently of high interest, as faults in substations can be repaired quickly and inexpensively, and smart meter data are becoming widely available. In this paper, we review recent scientific publications presenting data-driven approaches for fault and anomaly detection in district heating substations with a focus on methods and data sets. Our review indicates that researchers use a wide variety of methods, mostly focusing on unsupervised anomaly detection rather than fault detection. This is due to a lack of labeled data sets, preventing the use of supervised learning methods and quantitative analysis. Together with the lack of publicly available data sets, this impedes the accurate comparison of individual methods. To overcome this impediment, increase the comparability of different methods and foster competition, future research should focus on establishing publicly available data sets, and industry-relevant metrics as benchmarks.