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The detection of soil erosion processes in dams, hydraulic heave failure or corrosion processes of reinforcing steel in concrete are a small selection of measuring applications in civil engineering where the impedance analysis can be used to determine the measurand. Those measuring applications are having high requirements for the measuring hardware. For example a common interface for fast data exchange, high resolution, independent functionality and easy customizability to suit the measuring application. For that reason, a well-known application for steel-mill process monitoring can be used as a development platform. This hardware platform is based on a vector network analyzer and is meeting the requirements mainly. However, a couple of modifications has to be made, like replacing the ADC for a higher sample rate, Ethernet for easy and fast data exchange and the microcontroller for more calculation power.
Gallium Nitride (GaN) and Indium Gallium Nitride (InGaN) have become important semiconductor materials for the LED lighting industry. Recently, a photoluminescence (PL) technique for direct in-situ characterization of GaN and InGaN layers during epitaxial growth in a planetary metalorganic vapor phase epitaxy (MOVPE) reactor was reported. The PL signals reveal – at the earliest possible stage – information about current layer thickness, temperature, composition, surface roughness, and self-absorption. Thus, the PL data is valuable for both controlling and optimizing the growth parameters, thereby promising both better devices and a better yield for the LED industry. This technical report describes an extension of this PL technique to close coupled showerhead (CCS) reactors with narrow optical viewports. In contrast to the wide aperture optics in previous investigations, a compact and all-fiber optical probe without voluminous lens optics, filter elements or beam splitters was used.
Das CameraFramework wurde entwickelt, um mittels Socket-Kommunikation [1] als Middleware zwischen verschiedenen Kamerainstanzen mit eigenen Kameratreibern und Clienten zu fungieren. Über diesen Kommunikationsweg ist es möglich Clienten nicht nur lokal, sondern auch über das Netzwerk mit Kameradaten zu versorgen. Um neue Kameras mit dem Framework nutzen zu können, muss die Implementierung gewissen Regeln folgen, was durch ein vorgegebenes Basis-Interface (abstrakte Basis-Klasse in C++ [2]) fast vollständig sichergestellt ist. Neue Kameras werden zur Laufzeit über dynamische Bibliotheken geladen. Parameter für Kameras sind über ein XML-File [3] einzustellen. Funktionen zur Übergabe von neuen Kameradaten sind implementiert und müssen durch den Entwickler der einzelnen Kamerainterfaces aufgerufen werden.
Die Zuordnung von Kameradaten zum passenden Nutzer übernimmt das Framework. Jeder Clienterhält seinen eigenen konfigurierbaren Ringbuffer [4] um unabhängig von anderen Nutzern und Kameras zu sein. Die Aufgaben des Frameworks sind auf verschiedene Module, wie in Abbildung 1 dargestellt, aufgeteilt.
Practical application of object detection systems, in research or industry, favors highly optimized black box solutions. We show how such a highly optimized system can be further augmented in terms of its reliability with only a minimal increase of computation times, i.e. preserving realtime boundaries. Our solution leaves the initial (HOG-based) detector unchanged and introduces novel concepts of non-linear metrics and fusion of ROIs. In this context we also introduce a novel way of combining feature vectors for mean-shift grouping. We evaluate our approach on a standarized image database with a HOG detector, which is representative for practical applications. Our results show that the amount of false-positive detections can be reduced by a factor of 4 with a negligable complexity increase. Although introduced and applied to a HOG-based system, our approach can easily be adapted for different detectors.
The Bitcoin whitepaper states that security of the system is guaranteed as long as honest miners control more than half of the current total computational power. The whitepaper assumes a static difficulty, thus it is equally hard to solve a cryptographic proof-of-work puzzle for any given moment of the system history. However, the real Bitcoin network is using an adaptive difficulty adjustment mechanism. In this paper we introduce and analyze a new kind of attack on a mining difficulty retargeting function used in Bitcoin. A malicious miner is increasing his mining profits from the attack, named coin-hopping attack, and, as a side effect, an average delay between blocks is increasing. We propose an alternative difficulty adjustment algorithm in order to reduce an incentive to perform coin-hopping, and also to improve stability of inter-block delays. Finally, we evaluate the presented approach and show that the novel algorithm performs better than the original algorithm of Bitcoin.
Photolumineszenz (PL) aus Halbleiterstrukturen liefert Informationen bezüglich verschiedener Materialparameter wie z.B. Bandlücke, Schichtdicke sowie Temperatur. PL-Messungen werden klassischerweise erst ex situ und somit nach dem Produktionsprozess vorgenommen. Wird eine derartige PL-Messung während der Epitaxie einer Halbleiterstruktur und den damit verbundenen hohen Wachstumstemperaturen durchgeführt, erlaubt dies eine quasi-kontinuierliche In-situ-Charakterisierung der optoelektronischen Eigenschaften dieser Struktur zum frühestmöglichen Zeitpunkt, also noch in der Produktionsphase. Hierdurch wird eine In-situ-Optimierung der Prozessparameter ermöglicht, welche bei einer Ex-situ-Messung nicht gegeben ist. Die vorliegende Arbeit beschreibt zunächst theoretisch und dann anhand praktischer Messungen an industrienahen Epitaxie-Anlagen erstmals eine quasi-kontinuierliche In-situ-PL-Messung am Beispiel von wachsenden Nitrid-Halbleiterstrukturen. Über zeitaufgelöste PL-Messungen wird ein temperaturabhängiger Quenching-Mechanismus bei Gallium-Nitrid (GaN) und Indium-Gallium-Nitrid (InGaN) aufgezeigt, welcher den Einsatz von gepulsten Lasern als PL-Anregungsquelle bei hohen Wachstumstemperaturen einer Epitaxie erforderlich macht. Mit In-situ-PL-Messungen können hierdurch erstmals verschiedene Parameter einer gerade wachsenden Halbleiterschicht charakterisiert werden. Neben der Bestimmung der Temperatur und der Schichtdicke einer wachsenden, auf InGaN basierten LED-Struktur wird auch die Möglichkeit demonstriert, in einem frühen Stadium des Wachstums einer LED-Struktur ihre spätere Emissionswellenlänge bei Raumtemperatur vorherzusagen, und dies mit einer Genauigkeit von ± 1,3 nm (2σ). Diese Arbeit zeigt somit neben den industriell etablierten Messtechniken, wie z.B. pyrometrische Verfahren, eine weitere Möglichkeit zur Prozessüberwachung einer Epitaxie auf.
In this review, we describe current Machine Learning approaches to hand gesture recognition with depth data from time-of-flight sensors. In particular, we summarise the achievements on a line of research at the Computational Neuroscience laboratory at the Ruhr West University of Applied Sciences. Relating our results to the work of others in this field, we confirm that Convolutional Neural Networks and Long Short-Term Memory yield most reliable results. We investigated several sensor data fusion techniques in a deep learning framework and performed user studies to evaluate our system in practice. During our course of research, we gathered and published our data in a novel benchmark dataset (REHAP), containing over a million unique three-dimensional hand posture samples.
Enabling decentral collaborative innovation processes -a web based real time collaboration platform
(2018)
The main goal of this paper is to define a collaborative innovation process as well as a supporting tool. It is motivated through the increasing competition on global markets and the resultant propagation of decentralized projects with a high demand of innovative collaboration in global contexts. It bases on a project accomplished by the author group. A detailed literature review and the action design research methodology of the project led to an enhanced process model for decentral collaborative innovation processes and a basic realization of a browser based real time tool to enable these processes.The initial evaluation in a practical distributed setting has shown that the created tool is a useful way to support collaborative innovation processes.
Quality and dimensional accuracy of hot rolled steel rods depend on several process parameters. In fact many of these crucial parameters are not be sufficiently determined yet. By improving automation and process control costs and scrap of production can be decreased. As part of the research project PIREF, one of these parameters – the roll gap – is under investigation beside other topics. Before starting rolling, the roll gap is typically set to a fixed value according to the planed dimensions of the product, but the forces during the rolling of the rod cause an enlargement of the roll gap. In which way the rolls change their position and form shall be examined in our research project. Therefore a first experimental setup has been built up to determine the change in position of the rolls under applied force. This is realized by a pot core coil as sensor using impedance analysis. The first results are presented in this work as a proof-of-principle.