Refine
Year of publication
- 2014 (38) (remove)
Document Type
- Conference Proceeding (21)
- Article (8)
- Part of a Book (2)
- Doctoral Thesis (2)
- Part of Periodical (2)
- Book (1)
- Preprint (1)
- Working Paper (1)
Language
- English (23)
- German (13)
- Multiple languages (2)
Keywords
- Fachhochschule (2)
- Hochschule Ruhr West (2)
- Mülheim an der Ruhr (2)
- Zeitschrift (2)
- Feldverteilung (1)
- Halberzeugnis (1)
- Hochtemperatur (1)
- Inprozesskontrolle (1)
- Rundstahl (1)
- Warmwalzen (1)
Ziel des Verbundprojektes APFel (Projektlaufzeit: 01.01.2010 ‐ 31.03.2014)war eine zeitlich vorwärts‐ und rückwärtsgerichtete Lokalisation von Personen innerhalb eines Kameranetzwerkes aus sich nicht überlappenden Kameras in Hyperechtzeit zu ermöglichen. Einsatzbereiche dieses Szenarios sind kritische Infrastrukturen wie Flughäfen und Flugplätze. Zunächst fokussierte das Projekt APFel auf die Lokalisation einer einzelnen Zielperson. Weiterführend wurden die entwickelten Verfahren auf die Analyse von Gruppen erweitert, um Personen als Teil einer Gruppe lokalisieren zu können.
Recommender systems have become an important application domain related to the development of personalized mobile services. Thus, various recommender mechanisms have been developed for filtering and delivering relevant information to mobile users. This paper presents a rich context model to provide the relevant content of news to the current context of mobile users. The proposed rich context model allows not only providing relevant news with respect to the user’s current context but, at the same time, also determines a convenient representation format of news suitable for mobile devices.
Electro-magnetic acoustic transducers (EMATs) are intended as non-contact and non-destructive ultrasound transducers for metallic material. The transmitted intensities from EMATS are modest, particularly at notable lift off distances. Some time ago a concept for a “coil only EMAT” was presented, without static magnetic field. In this contribution, such compact “coil only EMATs” with effective areas of 1–5 cm2 were driven to excessive power levels at MHz frequencies, using pulsed power technologies. RF induction currents of 10 kA and tens of Megawatts are applied. With increasing power the electroacoustic conversion efficiency also increases. The total effect is of second order or quadratic, therefore non-linear and progressive, and yields strong ultrasound signals up to kW/cm2 at MHz frequencies in the metal. Even at considerable lift off distances (cm) the ultrasound can be readily detected. Test materials are aluminum, ferromagnetic steel and stainless steel (non-ferromagnetic). Thereby, most metal types are represented. The technique is compared experimentally with other non-contact methods: laser pulse induced ultrasound and spark induced ultrasound, both damaging to the test object’s surface. At small lift off distances, the intensity from this EMAT concept clearly outperforms the laser pulses or heavy spark impacts.
This paper describes the design and development stages of a web-based framework, aiming to support the creation of mobile applications within the context of mobile learning. The suggested approach offers the opportunity to deploy and execute these applications on mobile devices. This web-based solution additionally offers the possibility to visualize the data collected by the mobile applications in a web-browser. Despite previous research efforts carried out in this domain, few of the projects have addressed these processes from a purely web-based perspective. Currently, a prototype of an authoring tool for creating mobile data collection applications is already implemented. In order to integrate and validate this solution in everyday educational settings, we are collaborating with a network of high schools. On the basis of workshops with teachers we will carry out, refinements and requirements for further enhancements will be collected and will be used to guide our coming efforts.
Building upon prior results, we present an alternative approach to efficiently classifying a complex set of 3D hand poses obtained from modern Time-Of-Flight-Sensors (TOF). We demonstrate it is possible to achieve satisfactory results in spite of low resolution and high noise (inflicted by the sensors) and a demanding outdoor environment. We set up a large database of pointclouds in order to train multilayer perceptrons as well as support vector machines to classify the various hand poses. Our goal is to fuse data from multiple TOF sensors, which observe the poses from multiple angles. The presented contribution illustrates that real-time capability can be maintained with such a setup as the used 3D descriptors, the fusion strategy as well as the online confidence measures are computationally efficient.
LEDs gelten als umweltfreundliche Beleuchtungstechnik. Für die Massenanwendung arbeiten die LED-Hersteller an einer Senkung der Kosten bzw. einer Erhöhung der Ausbeute, insbesondere bei der aufwendigen LED-Kristallbeschichtung auf den Wafern. Während der Beschichtung (MOCVD) werden optische In-situ-Messgeräte zur Überwachung des Prozesses genutzt. Die hier vorgestellte Untersuchung beschäftigt sich mit dem Einfluss von Super-Photolumineszenz-Effekten bei einer möglichen In-situ-Prozesskontrolle in der MOCVD.
Bipolar electrosurgical systems are used for the treatment of benign prostatic hyperplasia (BPH) in urology. In order to analyse electrothermal processes during surgery the power loss density distribution around a bipolar resectoscope is calculated out of the measured potential distribution in isotonic saline solution ex situ. During further analysis power loss density values act as input for the Penne's bioheat equation. To achieve results, which are as realistic as possible, a method to obtain power loss density values, depending on the observed tissue or medium in the operating field, is presented. Applying this method, the power loss density distribution in isotonic saline solution at 25 °C is compared to the distribution calculated for the average conductivity of biological tissue in the region of interest.
Efficient photoluminescence (PL) spectra from GaN and InGaN layers at temperatures up to 1100 K are observed with low noise floor and high dynamic resolution. A number of detailed spectral features in the PL can be directly linked to physical properties of the epitaxial grown layer. The method is suggested as an in situ monitoring tool during epitaxy of nitride LED and laser structures. Layer properties like thickness, band gap or film temperature distribution are feasible.
With a rapidly ageing population, it is increasingly important to de-
velop devices for elderly and disabled people that can support and aid
them in their daily lives, helping them to live at home as long as pos-
sible. The goal of this project is to implement a human-machine inter-
action and assistance system that can offer personalised health sup-
port for elderly people, or for those who have special needs in the
home environment.
Optimization of Encircling Eddy Current Sensors for Online Monitoring of Hot Rolled Round Steel Bars
(2014)
Modern manufacturing industries are continually working on quality enhancements for the hot rolling process of round products. One method for improving the finalisation of the rods is the implementation of an automatic size control system. As a result of these trends over the last few years, there has been an increasing demand for more accurate online measurements. Thus the reason for the research performed for this thesis. A particular challenge throughout this research was dealing with the temperature changes (up to 1200°C) from the in- and output of the fervent rolling stocks, and the effect this temperature changes had on the sensors. Furthermore, there is also high demand for developing fast and practical electronic measuring equipment, capable of measuring during high transport velocities (up to 120 m/s). The eddy current principle is just one of the very few methods available which can with-stand such harsh industrial environments. In fact, eddy current sensors are already being integrated into online monitoring tasks for hot rolling processes. The measurement uncertainty, however, is still considerably large for process control purposes. One reason for this lies within the ability for eddy current detectors to receive signals influenced by outward forces, i.e. forces dependent on its location, its geometry, the outside temperature and the material properties of a particular target. Thus the current accuracy for a cross-sectional area measurement, for example, is no higher than 1%. As a result, this thesis investigates the magnitude of all individual influential factors on the eddy current detectors, using model-based analysis techniques. The analytical model provides a solution for all rotationally symmetrical targets and the FEA model covers all of the other influencing parameters in a more time consuming manner. This thesis then provides different methods which are developed to separate the cross-sectional area measurement of a rod from all of the other influencing parameters. In addition, a material tracking approach for round products is developed. Two different kinds of prototypes, capable of measuring approximately 466 Tons of red-hot steel rods during the production process, are finally introduced in this thesis. The usefulness of the eddy current principle is validated by the provided field test results. The count accuracy for the identification of 2876 bars was found to be 99.93%, and the average measurement accuracy for the cross-sectional area experiments was reduced to ± 0.29 % when including all of the findings.
As smart homes are being more and more popular, the needs of finding assisting systems which interface between users and home environments are growing. Furthermore, for elderly and disabled people living in such homes it is totally important to develop devices, which can support and aid them in their ordinary daily life. This demands means and tools that extend independent living and promote improved health. In this work we reviewed the state of the art in the assistant systems in home environments. A case study of medical assisting system for elderly and people with disabilities is discussed deeply. A smart nfc-based person-specific assistant system for services in home environment is proposed. The role of this system is the assisting by controlling of home activities and adaption of home-human interface towards the needs of the considered person. For the special case of medical assisting the system has the ability of providing for elderly or disabled people person-specific medical assistance. The system has the ability of identifying its interaction partner using some biometric features. According to the recognized ID the system, first, adopts towards the needs of recognized person. Second the system represents person-specific list of medicaments either visually, on screen, or acoustic, speaker. And third the system gives an alarm in the case of taking medicament either later or earlier as normal taking time.
We present a study on 3D based hand pose recognition using a new generation of low-cost time-of-flight(ToF) sensors intended for outdoor use in automotive human-machine interaction. As signal quality is impaired compared to Kinect-type sensors, we study several ways to improve performance when a large number of gesture classes is involved. We investigate the performance of different 3D descriptors, as well as the fusion of two ToF sensor streams. By basing a data fusion strategy on the fact that multilayer perceptrons can produce normalized confidences individually for each class, and similarly by designing information-theoretic online measures for assessing confidences of decisions, we show that appropriately chosen fusion strategies can improve overall performance to a very satisfactory level. Real-time capability is retained as the used 3D descriptors, the fusion strategy as well as the online confidence measures are computationally efficient.
PROPRE is a generic and modular neural learning paradigm that autonomously extracts meaningful concepts of multimodal data flows driven by predictability across modalities in an unsupervised, incremental and online way. For that purpose, PROPRE consists of the combination of projection and prediction. Firstly, each data flow is topologically projected with a self-organizing map, largely inspired from the Kohonen model. Secondly, each projection is predicted by each other map activities, by mean of linear regressions. The main originality of PROPRE is the use of a simple and generic predictability measure that compares predicted and real activities for each modal stream. This measure drives the corresponding projection learning to favor the mapping of predictable stimuli across modalities at the system level (i.e. that their predictability measure overcomes some threshold). This predictability measure acts as a self-evaluation module that tends to bias the representations extracted by the system so that to improve their correlations across modalities. We already showed that this modulation mechanism is able to bootstrap representation extraction from previously learned representations with artificial multimodal data related to basic robotic behaviors [1] and improves performance of the system for classification of visual data within a supervised learning context [2]. In this article, we improve the self-evaluation module of PROPRE, by introducing a sliding threshold, and apply it to the unsupervised classification of gestures caught from two time-of-flight (ToF) cameras. In this context, we illustrate that the modulation mechanism is still useful although less efficient than purely supervised learning.
Currently in home environments, robot assisting systems with emotion understanding ability are generally achieved in two several manners. The first is the implementing of such systems in such a way that they offer general services for all considered persons without considering privacy, special needs of their interaction partners. The second way is the targetting of such systems for merely one person. In this work we present a robot assisting system, which has both the abilities of assisting several persons at the same time and sustaining their privacy and security issues. The robot can interact with it's interaction partner emotionally by analyzing the emotions of her expressed either visually, facial expression, or auditive, speech prosody. The role of this system is the providing of person-specific support in home environment. In order to identify its interaction partner the system uses diverse biometric traits. According to the recognized ID the system, first, adopts towards the needs of recognized person. Second the system loads the corresponding emotional profile of the detected interaction partner in order to practice a person-specific emotional human-robot interaction, which has an advantage over the person independent interaction.
This paper presents a web-based framework that allows the creation and deployment of mobile learning activities. We present an authoring tool that allows not-technically skilled persons to design mobile learning tasks and deploy them as a web-based mobile application. Since the presented approach is based exclusively on web-technologies, the deployed mobile application can be executed via a mobile browser and therefore is platform independent. Despite previous research efforts carried out in this domain, few of the projects have addressed this course of actions from a purely web-based perspective. Through the latest development of web technologies, mobile applications have access to internal sensors like camera, microphone and GPS and therefore allow data collection within web-applications. In order to validate whether the proposed framework can be applied in educational settings, we conducted a pilot study with experienced teachers and present the results of these efforts in this paper.
Die transurethrale Resektion der Prostata (TURP) ist ein Verfahren der Elektrochirurgie innerhalb der Urologie. Thema der Arbeit ist die Entwicklung einer Methodik für realitätsnahe vergleichende Untersuchungen der elektrothermischen Vorgänge um Resektoskope zur bipolaren TURP. Die Relevanz dieses Themas liegt in der aktuellen Diskussion, ob elektrothermische Verletzungen eine mögliche Ursache urethraler Komplikationen darstellen. In diesem Kontext sind nicht die Vorgänge an der Resektionselektrode sondern in nicht behandelten Arealen des Operationsgebiets von Interesse. Bisher durchgeführte Untersuchungen konzentrieren sich auf monopolare Systeme. Untersuchte bipolare Elektrodenanordnungen unterscheiden sich allerdings von heutigen bipolaren Resektoskopen. Die vorhandenen Erkenntnisse sind deshalb nur äußerst eingeschränkt anwendbar. Informationen zu thermischen Vorgängen bezüglich Spätkomplikationen liegen nicht vor.
Der gewählte Ansatz aus messtechnischer Bestimmung der 3D Potentialverteilung ex situ sowie modellbasierter und numerischer Analyse der sich daraus ergebenden 3D Verlustleistungsdichteverteilung und der darauf beruhenden Temperaturberechnung im operationsnahen Gewebe ermöglicht ein auf die Realität übertragbares Ergebnis. Die berechnete Temperatur dient des Weiteren als Grundlage einer medizinischen Einschätzung hinsichtlich des Potentials elektrothermischer Verletzungen. Ergebnis der Arbeit ist, dass vergleichende Untersuchungen bipolarer Resektoskope mit der entwickelten Methodik durchführbar sind. Für die untersuchte bipolare Elektrodenanordnung erscheinen elektrothermische Verletzungen als Ursache urethraler Strikturen bei konservativer Betrachtung und unter durchschnittlichen Operationsbedingungen ohne intraoperative Komplikationen unwahrscheinlich.
MeHRWert Ausgabe 5 Juni 2014
(2014)