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Wissensmanagement (WM) und IT-gestütztes Lernen sind gerade in kleinen Behörden der Öffentlichen Verwaltung (ÖV), wie z.B. in ländlichen
Gemeinden, noch ausbaufähig. Am Beispiel des EU-Projekts EAGLE werden
Projektergebnisse als Verbesserungsansätze für ein arbeitsprozessorientiertes, IT-gestütztes Lernen vorgestellt. Neuartige Plattform-Features und ihr ÖV-spezifischer Nutzen werden erläutert. Die Ergebnisse der Plattformvalidierung werden vorgestellt. Ferner werden Vorschläge gemacht, wie die Ergebnisse aus EAGLE mit WM und weiteren Wissensquellen der ÖV, wie z.B. der Registratur, zu einem Gesamtkonzept mit bereits vorhandenen Fortbildungs- und WM-Ansätzen verbunden werden können.
Background:
Influential actors detection in social media such as twitter or Facebook can play a major role in gathering opinions on particular topics, improving the market
-
ing efficiency, predicting the trends, etc.
Proposed methods:
This work aims to extend our formally defined
T
measure to
present a new measure aiming to recognize the actor’s influence by the strength of
attracting new important actors into a networked community. Therefore, we propose a
model of the actor’s influence based on the attractiveness of the actor in relation to the
number of other attractors with whom he/she has established connections over time.
Results and conclusions:
Using an empirically collected social network for the
underlying graph, we have applied the above-mentioned measure of influence in
order to determine optimal seeds in a simulation of influence maximization. We study
our extended measure in the context of information diffusion because this measure is
based on a model of actors who attract others to be active members in a community.
This corresponds to the idea of the IC simulation model which is used to identify the
most important spreaders in a set of actors.
Keywords: Actor influence, Social media networks, Twitter, IC model, Information
diffusion, Independent cascade model, T measure
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.
Process Monitoring in Steel-Mills using Impedance Analysis: VNA Improvement for Data Acquisition
(2017)
The process automation extends over every manufacturing step of a product in the steel-mill to increase the quality, quantity and energy efficiency. The product dimensions are an important part of the quality control; these must maintain the specified tolerances. Additional to the cross-sectional-area, the measured data contains much more information about the manufacturing process, e.g. eccentricity, condition of the rolls and defects of the rod. For analyzing the measured data and to gather more information about the manufacturing process it is necessary to increase the speed of the data acquisition by performing some modifications of the VNA, e.g. faster analog to digital converter and microcontroller, improved firmware and optimized values of the passive electrical components for faster time constants and transient responses.
Das kEFIR‐Projekt untersucht die praktische Anwendung von thermographischen Verfahren zur Analyse der strukturellen Integrität von Windkraftrotorblättern. Das Projekt entstand in Zusammenarbeit der Hochschule Ruhr West (HRW) mit der IQbis Consulting GmbH im Rahmen eines ZIM‐Förderprojekts des Bundesministeriums für Wirtschaft und Energie (BMWi). Hintergrund ist die zunehmende Anzahl von Windkraftanlagen (WKA) und der somit steigende Wartungsaufwand. Um einen reibungslosen Betrieb dieser Anlagen zu gewährleisten und damit den besonderen Anforderungen an die Verfügbarkeit energieerzeugender Anlagen sicherzustellen, ist ein Bedarf an qualitativ hochwertigen Fehleranalysesystemen für im Betrieb befindlicher WKA von besonderer Bedeutung. Erfahrungsgemäß ist der Zeitaufwand für diese Inspektionen mit aktuellen Mitteln sehr groß und wird üblicherweise mit mehreren Arbeitstagen kalkuliert. Die Reproduzierbarkeit der gewonnenen Daten ist bei den derzeitigen Methoden meist nicht gewährleistet. Um frühzeitig auf Instabilitäten oder Schäden in den Rotorblättern einer WKA aufmerksam zu werden, ist die Entwicklung eines schnellen und qualitativ hoch wertigen Fehleranalysesystems von zentraler Bedeutung. Ein Forschungsschwerpunkt in diesem Zusammenhang ist die Entwicklung von geeigneten bildgebenden und berührungslosen Verfahren, welche bei den Inspektionen eingesetzt werden können. Beispielsweise erlaubt der Einsatz thermographischer Sensoren eine Analyse nicht nur der Rotorblattoberfläche, sondern auch ihrer inneren Struktur. Weiterhin ist aufgrund des schnell wachsenden Marktes bei unbemannten Luftfahrzeugen, wie beispielsweise positionsstabiler Quatrocoptersysteme, eine zusätzliche Möglichkeit gegeben, die Inspektion von Windenergieanlagen mit Hilfe mobiler, kompakter und fliegender Analysesysteme zu unterstützen.
In recent times, a lot of attacks against central server infrastructures have been recognized. Those infrastructures have seen attacks ranging from attacks against Internt of Things (IoT) infrastructures, via attacks against public infrastructure to attacks against cryptocurrency exchanges and blockchain based infrastructures themselves, e.g., the already almost legendary Decentralized Autonomous Organization (DAO) hack. Measured by press coverage, attacks against cryptocurrency exchanges and infrastructures seem to be among the most prominently reported attacks, probably due to the large amount of money that is stolen during those attacks and the great (but obviously still quite risky) potential (and financial involvement) of the blockchain technology. Naturally, attacks like the ones we have seen recently in crease the notion of uncertainty of blockchain technologies among the people,mreflected in lower values of cryptocurrencies in general. Obviously, this demands for an overall increase of security of cryptocurrency based technologies. Therefore, this paper provides an architectural approach, based on a proxy,to increase security of publicly available nodes of a blockchain based technology. Furthermore, it provides a first evaluation of the approach based on the results of an extensive community test of a new cryptocurrency.
Increasing economic viability and safety through structural health monitoring of wind turbines
(2017)
Serious accidents with property damage or even human casualties, result from structural flaws in wind turbine rotor blades. Common maintenance practices result in long downtimes and do not lead to the required results. Therefore, the Ruhr West University of Applied Sciences and the iQbis Consulting GmbH, currently research a new structural health monitoring method for wind turbine rotor blades. The goal of this project is to build a sensor system that can detect structural weaknesses inside of rotor blades without the need of downtime for industrial climbers. This technology has the potential to prevent accidents, save lives, extend the useful life of wind turbines and optimize the production of green energy.
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.
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.
Editorial
Jörg Himmel, Olfa Kanoun, Thomas Seeger, Klaus Thelen IEEE Workshop on Industrial and Medical Measurement and Sensor Technology – SENSORICA 2016 1
Beiträge Jan Taro Svejda, Andreas Rennings, Daniel Erni A metamaterial based dual-resonant coil element for combined sodium/hydrogen MRI at 7 Tesla 2
Fabian Feldhaus, Ingo Schmitz, Thomas Seeger Emission spectroscopy based sensor developed for engine testing 13
Anne-Sophie Rother, Thomas Dietz, Peter Kohns, Georg Ankerhold Molecular laser-induced breakdown spectroscopy for elemental analysis 23
Johannes Kiefer, Andreas Bösmann, Peter Wasserscheid Quantitative measurement of complex substances dissolved in an ionic liquid using IR spectroscopy and chemometrics 32
Oliver Gieseler, Hubert Roth, Jürgen Wahrburg Methods to determine the scaling factor in X-ray images for exact preoperative planning in hip surgery 38
Erwin Gerz, Matthias Mende, Hubert Roth Development of an optical tracking system for a novel flexible and soft manipulator with controllable stiffness for minimal invasive surgery (MIS) 47
Jens Weidenmüller, Christian Walk, Özgü Dogan, Pierre Gembaczka, Alexander Stanitzki, Michael Görtz Telemetric multi-sensor system for medical applications – The approach 53
Inga-Maria Eichentopf, Martin Reufer Measurement and analysis of wavefront structures of diode lasers 59
Group-centered framework towards a positive design of digital collaboration in global settings
(2017)
Globally distributed groups require collaborative systems to support their work. Besides being able to support the teamwork, these systems also should promote well-being and maximize the human potential that leads to an engaging system and joyful experience. Designing such system is a significant challenge and requires a thorough understanding of group work. We used the field theory as a lens to view the essential aspects of group motivation and then utilized collaboration personas to analyze the elements of group work. We integrated well-being determinants as engagement factors to develop a group-centered framework for digital collaboration in a global setting. Based on the outcomes, we proposed a conceptual framework to design an engaging collaborative system and recommend system values that can be used to evaluate the system further.
Autonomous driving is one of the future visions in which many vehicle manufacturers are working with high pressure.
Nowadays, it is already supported partially by high-class vehicles. A completely autonomous journey is indeed the goal, but in cars for
the public road traffic still not available. Automatic lane keeping assistants, speed regulators as well as shield and obstacle detections
are parts or precursors on the way to completely autonomous driving.
The American vehicle manufacturer Tesla is not only known for its electric drive, but also for the fact that high-pressure work is carried out on the autonomous drive. Tesla is thus the only vehicle manufacturer to use its users as so-called beta testers for its assistance systems. The progress and the function of the currently available Model S in the field of assistance systems and autonomic driving is documented and described in this paper. It is shown how good or bad the test vehicle manages scenarios in normal road traffic situations
with the assistance systems, e.g. lane keeping assistant, speed control, lane change and distance assistant, and which scenarios can
not be managed by the vehicle itself.
In this contribution we present a novel approach to transform data from time-of-flight (ToF) sensors to be interpretable by Convolutional Neural Networks (CNNs). As ToF data tends to be overly noisy depending on various factors such as illumination, reflection coefficient and distance, the need for a robust algorithmic approach becomes evident. By spanning a three-dimensional grid of fixed size around each point cloud we are able to transform three-dimensional input to become processable by CNNs. This simple and effective neighborhood-preserving methodology demonstrates that CNNs are indeed able to extract the relevant information and learn a set of filters, enabling them to differentiate a complex set of ten different gestures obtained from 20 different individuals and containing 600.000 samples overall. Our 20-fold cross-validation shows the generalization performance of the network, achieving an accuracy of up to 98.5% on validation sets comprising 20.000 data samples. The real-time applicability of our system is demonstrated via an interactive validation on an infotainment system running with up to 40fps on an iPad in the vehicle interior.
This experimental study demonstrates for the first time a solid-state circuitry and design for a simple compact copper coil (without an additional bulky permanent magnet or bulky electromagnet) as a contactless electromagnetic acoustic transducer (EMAT) for pulse echo operation at MHz frequencies. A pulsed ultrasound emission into a metallic test object is electromagnetically excited by
an intense MHz burst at up to 500 A through the 0.15 mm filaments of the transducer. Immediately thereafter, a smoother and quasi “DC-like” current of 100 A is applied for about 1 ms and allows an
echo detection. The ultrasonic pulse echo operation for a simple, compact, non-contacting copper coil is new. Application scenarios for compact transducer techniques include very narrow and
hostile environments, in which, e.g., quickly moving metal parts must be tested with only one, non-contacting ultrasound shot. The small transducer coil can be operated remotely with a cable
connection, separate from the much bulkier supply circuitry. Several options for more technical and fundamental progress are discussed.