Refine
Year of publication
Document Type
- Conference Proceeding (19)
- Article (10)
- Part of Periodical (10)
- Bachelor Thesis (5)
- Book (3)
- Part of a Book (2)
- Report (2)
- Working Paper (2)
- Doctoral Thesis (1)
- Master's Thesis (1)
Has Fulltext
- yes (55) (remove)
Keywords
- Hochschule Ruhr West (9)
- Zeitschrift (9)
- Fachhochschule (8)
- Mülheim an der Ruhr (8)
- Intergenerational Collaboration (2)
- Intergenerational Innovation (2)
- Künstliche Intelligenz (2)
- Academic-stress (1)
- Augmented Reality (1)
- Children Refugee (1)
Institute
A Large and Quick Induction Field Scanner for Examining the Interior of Extended Objects or Humans
(2017)
This study describes the techniques and signal properties of a large, powerful, and linear-scanning 1.5 MHz induction field scanner. The mechanical system is capable of quickly reading the volume of relative large objects, e.g., a test person. The general approach mirrors Magnetic Induction Tomography (MIT), but the details differ considerably from currently-described MIT systems: the setup is asymmetrical, and it operates in gradiometric modalities, either with coaxial excitation with destructive interference or with a single excitation loop and tilted receivers. Following this approach, the primary signals were almost completely nulled, and test objects' real or imaginary imprint was obtained directly. The coaxial gradiometer appeared advantageous: exposure to strong fields was reduced due to destructive interference. Meanwhile, the signals included enhanced components at higher spatial frequencies, thereby obtaining a gradually improved capability for localization. For robust signals, the excitation field can be powered towards the rated limits of human exposure to time-varying magnetic fields. Repeated measurements assessed the important signal integrity, which is affected by the scanner´s imperfections, particularly any motions or respiratory changes in living beings during or between repeated scans. The currently achieved and overall figure of merit for artifacts was 58 dB for inanimate test objects and 44 dB for a test person. Both numbers should be understood as worst case levels: a repeated scan with intermediate breathing and drift/dislocations requires 50 seconds, whereas a single measurement (with respiratory arrest) takes only about 5 seconds.
The task of object detection in the automotive sector can be performed by evaluating various
sensor data. The evaluation of LiDAR data for the detection of objects is a special challenge for
which systems with neural networks can be used. These neural networks are trained by means of a
data set. If you want to use the net with your own recordings or another data set, it is important
to know how well these systems work in combination with data from another sensor. This allows
the results to be estimated in advance and compared with the results of previous experiments.
In this work the sensor dependence of a LiDAR based object recognition with neural networks
will be analysed. The detector used in this work is PointRCNN [1], which was designed for the
KITTI dataset [2]. To check the sensor dependency, the ’AEV Autonomous Driving Dataset’
(A2D2) dataset [3] was selected as a further dataset. After an introduction to PointRCNN and its
functionality, the data of both datasets are analysed. Then the data of the second dataset will be
ported into the format of the KITTI dataset so that they can be used with PointRCNN. Through
experiments with varying combinations of training and validation data it shall be investigated to
what extent trained models can be transferred to other sensor data or datasets. Therefore, it shall
be investigated how strong the dependence of the detector (PointRCNN) on the used sensors is.
The results show that PointRCNN can be evaluated with a different dataset than the training
dataset while still being able to detect objects. The point density of the datasets plays a decisive
role for the quality of the detection. Therefore it can be said that PointRCNN has a sensor
dependency that varies with the nature of the point cloud and its density.
Keywords: LiDAR data, 3D object recognition, laser scanner, sensor dependency, PointRCNN,
PointNet++, PointNet, KITTI Dataset, AEV Autonomous Driving Dataset, A2D2 Dataset
Photoluminescence (PL) in GaN or InGaN layers monitored during epitaxial growth at high temperatures permits a quasi-continuous in situ characterization of opto-electronic properties. Therefore, epitaxial parameters can now be optimized at the earliest possible stage. A pulsed and high-power UV laser was required for PL excitation at high temperatures. Herein, the underlying nonlinear mechanism was studied via time-resolved PL experiments and rate equation-based modeling. A temperature-activated and saturable path for quenching over defects was identified. Beyond the saturation threshold, reasonably-intensive PL sets in. At high temperatures not only is the near band gap-PL present, but also—as a new observation—a defect-assisted PL emerges. Apart from these specific electronic transitions in high-temperature PL of GaN, a simple, but reasonably predictive model of the luminescent thin film has been set up to track down interference fringes in the PL spectra. It is worth mentioning that the spectral PL modulation (aiming at the Purcell effect) is often mixed up with ordinary Fabry–Pérot interference. A distinction has become key to properly analyze the spectral signatures of high-temperature PL in order to provide a reliable in situ characterization of GaN layers during epitaxial growth
Das Ziel der vorliegenden Arbeit ist es, die Eignung von MeshLab in einem Reverse-Engineering-Projekt zu überprüfen. Dazu wurden vor Beginn sechs Kriterien aufgestellt, auf die MeshLab untersucht wird. Das Ergebnis zeigt, dass MeshLab fünf von sechs Kriterien erfüllt und somit für einen Einsatz geeignet ist.
MeshLab ist ein Teil der Datenaufbereitung des Reverse Engineering. Es ist ein kostenloses Programm und somit in Kombination mit einem günstigen Scanner für einen Einsatz in Reverse-Engineering-Projekten mit einem geringen Kostenaufwand einsetzbar.
The aim of this bachelor thesis is to verify the suitability of MeshLab in a Reverse-Engineering-Project. Before the beginning six criterias were set up on which MeshLab is examined. The result shows that MeshLab fulfills five of six criterias and is therefore suitable for use.
MeshLab is a part of the data preparation from the Reverse Engineering. It is a free programm and in combination with a cheap scanner, it can be used in a Revere-Engineering-Project with a low Budget.
Fahrerassistenzsysteme werden eingesetzt, um dem Fahrer
eines Kraftfahrzeugs Handlungsabläufe abzunehmen. Diese Handlungsabläufe
werden definiert durch eine Aufgabenstellung, die vom Fahrer an das Fahrerassi-
stenzsystem übergeben oder systembedingt gelöst wird. Bei komplexen Fahreras-
sistenzsystemen ist an eine autonome Navigation im Straßenverkehr gedacht. Es
wird ein neues Verfahren vorgestellt, welches eine Bewegungssteuerung eines
autonomen Fahrzeugs durchführen kann. Es werden der Lenkwinkel und die Ge-
schwindigkeit beeinflußt. Für diese Aufgabe wird ein dynamischer Ansatz aus
dem Bereich der neuronalen Felder gewählt. Relevante Attribute für den Fahrt-
verlauf auf unterschiedlichem Abstraktionsniveau können dabei einfach (additiv)
verarbeitet werden.
We describe the general concept, system architecture, hardware, and the behavioral abilities of Cora (Cooperative Robot Assistant, see Fig. 1), an autonomous non mobile robot assistant. Outgoing from our basic assumption that the behavior to perform determines the internal and external structure of the behaving system, we have designed Cora anthropomorphic to allow for humanlike behavioral strategies in solving complex tasks. Although Cora was built as a prototype of a service robot system to assist a human partner in industrial assembly tasks, we will show that Cora’s behavioral abilities are also conferrable in a household environment. After the description of the hardware platform and the basic concepts of our approach, we present some experimental results by means of an assembly task.
DamokleS 4.0
(2019)
Dieser interne Bericht beschreibt die Zielsetzung, Durchführung und Auswertung des Projektes Damokles 4.0. Das Projekt zielt darauf ab, neue, digitale Technologien in die Schwerindustrie einzuführen um Produktionsprozesse zu modernisieren. Unter Einsatz neuer Technologien, insbesondere mobiler Geräte, soll ein cyberphyiskalisches System (CPS) eine kontextbasierte und künstlich intelligente Unterstützung der Mitarbeiter in den Bereichen der Schwerindustrie ermöglichen. Hierzu werden typische Anwendungsfälle und die damit verbundenen Szenarien zur Unterstützung der Mitarbeiter auf Basis von neuen, flexiblen, adaptiven und mobilen Technologien, wie Augmented Reality und künstlicher Intelligenz, modelliert. Um den Prototypen einer AR-Anwendung und einer kamerabasierte Personenverfolgung zu entwickeln, hat die Hochschule Ruhr West im kleinen Technikum am Campus Bottrop eine entsprechende industrielle Umgebung simuliert. Die Projektergebnisse zeigen die Anwendbarkeit der vorgeschlagenen Softwareansätze und die Ergebnisse einer Untersuchung der psychologischen Einflüsse auf die Mitarbeiter.
Learning the German language is one of the most critical challenges for refugee children in Germany. It is a prerequisite to allow communication and integration into the educational system. To solve the underlying problem, we conceptualized a set of principles for the design of language learning systems to support collaboration between teachers and refugee children, using a Design Science Research approach. The proposed design principles offer functional and non-functional requirements of systems, including the integration of open educational resources, different media types to develop visual and audio narratives that can be linked to the cultural and social background. This study also illustrates the use of the proposed design principles by providing a working prototype of a learning system. In this, refugee children can learn the language collaboratively and with freely accessible learning resources. Furthermore, we discuss the proposed design principles with various socio-technical aspects of the well-being determinants to promote a positive system design for different cultural and generational settings. Overall, despite some limitations, the implemented design principles can optimize the potential of open educational resources for the research context and derive further recommendations for further research.
Detection of air trapping in chronic obstructive pulmonary disease by low frequency ultrasound
(2012)
Background: Spirometry is regarded as the gold standard for the diagnosis of COPD, yet the condition is widely underdiagnosed. Therefore, additional screening methods that are easy to perform and to interpret are needed. Recently, we demonstrated that low frequency ultrasound (LFU) may be helpful for monitoring lung diseases. The objective of this study was to evaluate whether LFU can be used to detect air trapping in COPD. In addition, we evaluated the ability of LFU to detect the effects of short-acting bronchodilator medication.Methods: Seventeen patients with COPD and 9 healthy subjects were examined by body plethysmography and LFU. Ultrasound frequencies ranging from 1 to 40 kHz were transmitted to the sternum and received at the back during inspiration and expiration. The high pass frequency was determined from the inspiratory and the expiratory signals and their difference termed F. Measurements were repeated after inhalation of salbutamol.Results: We found signi ficant differences in F between COPD subjects and healthy subjects. These differences were already significant at GOLD stage 1 and increased with the severity of COPD. Sensitivity for detection of GOLD stage 1 was 83% and for GOLD stages worse than 1 it was 91%. Bronchodilator effects could not be detected reliably.Conclusions: We conclude that low frequency ultrasound is cost-effective, easy to perform and suitable for detecting air trapping. It might be useful in screening for COPD
Background:
Detection of influential actors in social media such as Twitter or Facebook plays an important role for improving the quality and efficiency of work and services in many fields such as education and marketing.
Methods:
The work described here aims to introduce a new approach that characterizes the influence of actors by the strength of attracting new active members into a networked community. We present a model of influence of an actor that is based on the attractiveness of the actor in terms of the number of other new actors with which he or she has established relations over time.
Results:
We have used this concept and measure of influence to determine optimal seeds in a simulation of influence maximization using two empirically collected social networks for the underlying graphs.
Conclusions:
Our empirical results on the datasets demonstrate that our measure stands out as a useful measure to define the attractors comparing to the other influence measures.
