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Die Hersteller von Cochlea-Implantat (CI)-Systemen sehen für klinische Audiologen die Möglichkeit vor, die Mikrofonleistung der meisten aktuellen CI-Sprachprozessoren mittels anschließbarer Monitorkopfhörer zu prüfen. Nähere Angaben dazu, nach welchem Prozedere diese Prüfung stattfinden soll, z. B. welche Stimuli mit welchen Pegeln verwendet werden sollen, sind nach Wissen der Autoren seitens der CI-Hersteller nicht verfügbar. Auf der Basis dieser subjektiven Prüfung entscheidet dann der Audiologe, ob der betreffende Sprachprozessor an den Hersteller eingeschickt wird oder nicht. Wir haben eine Messbox entwickelt, mit der die Mikrofonleistung aller abhörbaren CI-Sprachprozessoren der Hersteller Advanced Bionics, Cochlear und MED-EL objektiv geprüft werden kann. Die Box wurde im 3-D-Druckverfahren hergestellt. Der zu prüfende Sprachprozessor wird in die Messbox eingehängt und über einen verbauten Lautsprecher mit definierten Prüfsignalen (Sinustönen unterschiedlicher Frequenz) beschallt. Das Signal des Mikronfons bzw. der Mikrofone wird über das in der Audio-/Abhörbuchse des Prozessors eingesteckte Kabel der Monitorkopfhörer herausgeführt und mit einer Shifting and Scaling-Schaltung in einen Spannungsbereich transformiert, der für die A/D-Wandlung mit einem Mikrokontroller (ATmega1280 verbaut auf einem Arduino Mega) geeignet ist. Derselbe Mikrokontroller übernimmt über einen eigens gebauten D/AWandler die Ausgabe der Prüfsignale über den Lautsprecher. Signalaufnahme und –wiedergabe erfolgt jeweils mit einer Samplingrate von 38,5 kHz. Der frequenzspezifische Effektivwert des abgegriffenen Mikrofonsignals wird mit einem Referenzwert verglichen. Die (frequenzspezifischen) Referenzwerte wurden mit einem neuwertigen Sprachprozessor gleichen Typs ermittelt und im Speicher des Mikrokontrollers abgelegt. Das Ergebnis wird nach Abschluss der Messung grafisch auf einem Touchscreen ausgegeben. Derzeit läuft eine erste Datenerhebung mit in der Klinik subjektiv auffällig gewordenen CI-Sprachprozessoren, die anschließend in der Messbox untersucht werden. Längerfristiges Ziel ist es, die hit und false alarm Raten der subjektiven Prüfung zu ermitteln.
Uncontrollable manufacturing variations in electrical hardware circuits can be exploited as Physical Unclonable Functions (PUFs). Herein, we present a Printed Electronics (PE)-based PUF system architecture. Our proposed Differential Circuit PUF (DiffC-PUF) is a hybrid system, combining silicon-based and PE-based electronic circuits. The novel approach of the DiffC-PUF architecture is to provide a specially designed real hardware system architecture, that enables the automatic readout of interchangeable printed DiffC-PUF core circuits. The silicon-based addressing and evaluation circuit supplies and controls the printed PUF core and ensures seamless integration into silicon-based smart systems. Major objectives of our work are interconnected applications for the Internet of Things (IoT).
The CAN bus still is an important fieldbus in various domains, e.g. for in-car communication or automation applications. To counter security threats and concerns in such scenarios we design, implement, and evaluate the use of an end-to-end security concept based on the Transport Layer Security protocol. It is used to establish authenticated, integrity-checked, and confidential communication channels between field devices connected via CAN. Our performance measurements show that it is possible to use TLS at least for non time-critical applications, as well as for generic embedded networks.
The Transport Layer Security (TLS) protocol is a cornerstone of secure network communication, not only for online banking, e-commerce, and social media, but also for industrial communication and cyber-physical systems. Unfortunately, implementing TLS correctly is very challenging, as becomes evident by considering the high frequency of bugfixes filed for many TLS implementations. Given the high significance of TLS, advancing the quality of implementations is a sustained pursuit. We strive to support these efforts by presenting a novel, response-distribution guided fuzzing algorithm for differential testing of black-box TLS implementations. Our algorithm generates highly diverse and mostly-valid TLS stimulation messages, which evoke more behavioral discrepancies in TLS server implementations than other algorithms. We evaluate our algorithm using 37 different TLS implementations and discuss―by means of a case study―how the resulting data allows to assess and improve not only implementations of TLS but also to identify underspecified corner cases. We introduce suspiciousness as a per-implementation metric of anomalous implementation behavior and find that more recent or bug-fixed implementations tend to have a lower suspiciousness score. Our contribution is complementary to existing tools and approaches in the area, and can help reveal implementation flaws and avoid regression. While being presented for TLS, we expect our algorithm's guidance scheme to be applicable and useful also in other contexts. Source code and data is made available for fellow researchers in order to stimulate discussions and invite others to benefit from and advance our work.
The Datagram Transport Layer Security (DTLS) protocol has been designed to provide end-to-end security over unreliable communication links. Where its connection establishment is concerned, DTLS copes with potential loss of protocol messages by implementing its own loss detection and retransmission scheme. However, the default scheme turns out to be suboptimal for links with high transmission error rates and low data rates, such as wireless links in electromagnetically harsh industrial environments. Therefore, in this paper, as a first step we provide an analysis of the standard DTLS handshake's performance under such adverse transmission conditions. Our studies are based on simulations that model message loss as the result of bit transmission errors. We consider several handshake variants, including endpoint authentication via pre-shared keys or certificates. As a second step, we propose and evaluate modifications to the way message loss is dealt with during the handshake, making DTLS deployable in situations which are prohibitive for default DTLS.
In public transportation, the motor pool often consists of various different vehicles bought over a duration of many years. Sometimes, they even differ within one batch bought at the same time. This poses a considerable challenge in the storage and allocation of spare parts, especially in the event of damage to a vehicle. Correctly assigning these parts before the vehicle reaches the workshop could significantly reduce both the downtime and, therefore, the actual costs for companies. In order to achieve this, the current software uses a simple probability calculation. To improve the performance, the data of specific companies was analysed, preprocessed and used with several modelling techniques to classify and, therefore, predict the spare parts to be used in the event of a faulty vehicle. We summarize our experience running through the steps of the Cross Industry Standard Process for Data Mining and compare the performance to the previously used probability. Gradient Boosting Trees turned out to be the best modeling technique for this special case.
This paper describes the use of the single-linkage hierarchical clustering method in outlier detection for manufactured metal work pieces. The main goal of the study is to group defects that occur 5 mm into a work piece from the edge, i.e., the border of the metal work piece. The goal is to remove defects outside the area of interest as outliers. According to the assumptions made for the performance criteria, the single-linkage method has achieved better results compared to other agglomeration methods.
Data Science gilt als eine der wichtigsten Entwicklungen der letzten
Jahre und viele Unternehmen sehen in Data Science die Möglichkeit,
ihre Daten zusätzlich wertschöpfend zu nutzen. Dabei kann es sich um
die Optimierung von Maintenance-Prozessen handeln, um eine bessere
Steuerung der eigenen Preis- und Lagerhaltungsstrategie oder auch
um völlig neue Services und Produkte, die durch Data Science möglich
werden. Die im Unternehmen vorliegenden Daten, an die so hohe Erwartungen
geknüpft wurden, sollen dazu genutzt werden, um Services
und Prozesse effizienter und passgenauer gestalten zu können. Vielfach
gilt Data Science dabei als Allheilmittel: Daten, die über Jahre hinweg
gesammelt wurden und mit zunehmender Geschwindigkeit und Heterogenität
anfallen, sollen endlich nutzbar gemacht werden. Zwar sind die
eingesetzten Techniken und Algorithmen teilweise schon zehn Jahre und
mehr alt, doch erst jetzt entfalten sie im Zusammenspiel mit Big Data
ihr Potenzial im Unternehmensumfeld. Die Erwartungen sind hoch, doch
der Weg zu den neuen Erkenntnissen ist mit hohem Aufwand verbunden
und wird von einigen Unternehmen noch immer unterschätzt.
Für Unternehmen mit einem traditionellen BI-Ansatz stellt Data Science
ein ergänzendes Set von Methoden und Werkzeugen dar, mit deren Hilfe
die Informationsversorgung der Entscheider auf den verschiedenen
hierarchischen Ebenen noch besser gestaltet werden kann. So zum Beispiel,
wenn man mit Data Science feststellt, dass die Wahrscheinlichkeit
für einen Versicherungsabschluss steigt, wenn bei der Auswahl der
anzusprechenden Kunden zusätzliche Daten herangezogen werden, die
zwar bereits vorliegen, aber noch nicht berücksichtigt worden sind. Im
Extremfall werden auch Entscheidungen vollständig automatisiert, die
bisher von Mitarbeiterinnen und Mitarbeitern getroffen wurden. Ein Algorithmus
legt dann fest, wann Ware nachbestellt oder welcher Preis für
den Endkunden festgesetzt wird.
Im vorliegenden E-Book soll ein Überblick über das Gebiet Data Science
gegeben werden. Dabei wird ein besonderes Augenmerk auf das Zusammenspiel
sowie das Mit- und Nebeneinander von Data Science und vorhandenen
BI-Systemen gelegt.
Optische Navigationssysteme weisen bisher eine eindeutige Trennung zwischen nachverfolgendem Gerät (Tool Tracker) und nachverfolgten Geräten (Tracked Tools) auf. In dieser Arbeit wird ein neues Konzept vorgestellt, dass diese Trennung aufhebt: Jedes Tracked Tool ist gleichzeitig auch Tool Tracker und besteht aus Marker-LEDs sowie mindestens einer Kamera, mit deren Hilfe andere Tracker in Lage und Orientierung nachverfolgt werden können. Bei Verwendung von nur einer Kamera geschieht dies mittels Pose Estimation, ab zwei Kameras werden die Marker-LEDs trianguliert. Diese Arbeit beinhaltet die Vorstellung des neuen Peer-To-Peer-Tracking-Konzepts, einen sehr schnellen Pose-Estimation-Algorithmus für beliebig viele Marker sowie die Klärung der Frage, ob die mit Pose Estimation erreichbare Genauigkeit vergleichbar mit der eines Stereo-Kamera-Systems ist und den Anforderungen an die chirurgische Navigation gerecht wird.
A method for determining properties of a pipeline includes feeding a sound wave signal at a predetermined feed point into the pipeline so that the sound wave signal propagates in an axial direction of the pipeline. The frequency spectrum of the transmitted sound wave signal has a frequency component or a spectral range with a maximum frequency that is smaller than the lower limit frequency for the first upper mode. Reflected portions of the transmitted sound wave signal are detected as received sound wave signal and are evaluated with regard to the transmitted sound wave signal to determine at least the distance of each reflection site from the feed point.
Cardiac contractility modulation (CCM) is a device-based therapy for the treatment of systolic left ventricular chronic heart failure. Unlike other device-based therapies for heart failure, CCM delivers non-excitatory pacing signals to the myocardium. This leads to an extension of the action potential and to an improved contractility of the heart. The modeling and simulation was done with the electromagnetic simulation software CST. Three CCM electrodes were inserted into the Offenburg heart rhythm model and subsequently simulated the electric field propagation in CCM therapy.
In addition, simulations of CCM have been performed with electrodes from other device-based therapies, such as cardiac resynchronization therapy (CRT) and implantable cardioverter / defibrillator (ICD) therapy. At the same distance to the simulation electrode, the electric field is slightly stronger in CCM therapy than in CCM therapy with additionally implanted CRT or ICD electrodes. In addition, there is a change in the electric field propagation at the electrodes of the CRT and the shock electrode of the ICD.
By simulating several different therapy procedures on the heart, it is possible to check how they affect their behavior during normal operation. CCM heart rhythm model simulation allows the evaluation the individual electrical pacing and sensing field during CCM.
The paper describes the methodology and experimental results for revealing similarities in thermal dependencies of biases of accelerometers and gyroscopes from 250 inertial MEMS chips (MPU-9250). Temperature profiles were measured on an experimental setup with a Peltier element for temperature control. Classification of temperature curves was carried out with machine learning approach.
A perfect sensor should not have thermal dependency at all. Thus, only sensors inside the clusters with smaller dependency (smaller total temperature slopes) might be pre-selected for production of high accuracy inertial navigation modules. It was found that no unified thermal profile (“family” curve) exists for all sensors in a production batch. However, obviously, sensors might be grouped according to their parameters. Therefore, the temperature compensation profiles might be regressed for each group. 12 slope coefficients on 5 degrees temperature intervals from 0°C to +60°C were used as the features for the k-means++ clustering algorithm.
The minimum number of clusters for all sensors to be well separated from each other by bias thermal profiles in our case is 6. It was found by applying the elbow method. For each cluster a regression curve can be obtained.
A printed electronics technology has the advantage of additive and extremely low-cost fabrication compared with the conventional silicon technology. Specifically, printed electrolyte-gated field-effect transistors (EGFETs) are attractive for low-cost applications in the Internet-of-Things domain as they can operate at low supply voltages. In this paper, we propose an empirical dc model for EGFETs, which can describe the behavior of the EGFETs smoothly and accurately over all regimes. The proposed model, built by extending the Enz-Krummenacher-Vittoz model, can also be used to model process variations, which was not possible previously due to fixed parameters for near threshold regime. It offers a single model for all the operating regions of the transistors with only one equation for the drain current. Additionally, it models the transistors with a less number of parameters but higher accuracy compared with existing techniques. Measurement results from several fabricated EGFETs confirm that the proposed model can predict the I-V more accurately compared with the state-of-the-art models in all operating regions. Additionally, the measurements on the frequency of a fabricated ring oscillator are only 4.7% different from the simulation results based on the proposed model using values for the switching capacitances extracted from measurement data, which shows more than 2× improvement compared with the state-of-the-art model.
In this paper, we establish a simple model for the exchange of messages in a vehicular network and we consider fundamental limits on the achievable data rate. For a vehicular network, the exchange of data with other nearby vehicles is particularly important for traffic safety, e.g. for collision avoidance, but also for cooperative applications like platooning. These use cases are currently addressed by standards building on IEEE 802.11p, namely ITS-G5 and DSRC (dedicated short range communication), which encounter saturation problems at high vehicle densities. For this reason, we take a step back and ask for the fundamental limits for the common data rate in a vehicular network. After defining a simple single-lane model and the corresponding capacity limits for some basic multiple- access schemes, we present results for a more realistic setting. For both scenarios, non-orthogonal multiple-access (NOMA) yields the best results.
In this paper, we present a frame synchronization method which consists of the non-orthogonal superposition of a synchronization sequence and the data. We derive the optimum detection criterion and compare it to the classical sequential concatenation of synchronization and data sequences. Computer simulations confirm the benefits of the non-orthogonal allocation for the case of short frames, which makes this technique particularly suited for the increasingly important regime of low latency and ultra- reliable communication.
Online comment on: "Printing ferromagnetic domains for untethered fast-transforming soft materials"
(2018)
eLetter zu "Illusory movement perception improves motor control for prosthetic hands" von Paul D. Marasco et al., veröffentlicht in Science Translational Medicine, Vol. 10, No. 432 (DOI: 10.1126/scitranslmed.aao6990)
This paper evaluates the implementation of Medium Access Control (MAC) protocols suitable for massive access connectivity in 5G multi-service networks. The access protocol extends multi-packet detection receivers based on Physical Layer Network Coding (PLNC) decoding and Coded Random Access protocols considering practical aspects to implement one-stage MAC protocols for short packet communications in mMTC services. Extensions to enhance data delivery phase in two- stage protocols are also proposed. The assessment of the access protocols is extended under system level simulations where a suitable link to system interface characterization has been taken into account.
Recently, the demand for scalable, efficient and accurate Indoor Positioning Systems (IPS) has seen a rising trend due to their utility in providing Location Based Services (LBS). Visible Light Communication (VLC) based IPS designs, VLC-IPS, leverage Light Emitting Diodes (LEDs) in indoor environments for localization. Among VLC-based designs, Time Difference of Arrival (TDOA) based techniques are shown to provide very low errors in the relative position of receivers. Our considered system consists of five LEDs that act as transmitters and a single receiver (photodiode or image sensor in smart phone) whose position coordinates in an indoor environment are to be determined. As a performance criterion, Cramer Rao Lower Bound (CRLB) is derived for range estimations and the impact of various factors, such as, LED transmission frequency, position of reference LED light, and the number of LED lights, on localization accuracy has been studied. Simulation results show that depending on the optimal values of these factors, location estimation on the order of few centimeters can be realistically achieved.
Pulmonary vein isolation (PVI) is a common therapy in atrial fibrillation (AF). The cryoballoon was invented to isolate the pulmonary vein in one step and in a shorter time than a point-by-point radiofrequency (RF) ablation. The aim of the study was to model two cryoballoon catheters, one RF catheter and to integrate them into a heart rhythm model for the static and dynamic simulation of PVI by cryoablation and RF ablation in AF. The modeling and simulation were carried out using the electromagnetic and thermal simulation software CST (CST, Darmstadt). Two cryoballons and one RF ablation catheter were modeled based on the technical manuals of the manufacturers Medtronic and Osypka. The PVI especially the isolation of the left inferior pulmonary vein using a cryoballoon catheter was performed with a -50 °C heatsource and an exponential signal. The temperature at the balloon surface was -50 °C after 20 s ablation time, -24 °C from the balloon 0,5 mm in the myocardium, at a distance of 1 mm -3 °C, at 2 mm 18 °C and at a distance of 3mm 29 °C. PVI with RF energy was simulated with an applied power of 5 W at 420 kHz at the distal 8 mm ablation electrode. The temperature at the tip electrode was 110 °C after 15 s ablation time, 75 °C from the balloon at 0,5 mm in the myocardium, at a distance of 1 mm 58 °C, at 2 mm 45 °C and at a distance of 3 mm 38 °C. Virtual heart rhythm and catheter models as well as the simulation of the temperature allow the simulation of PVI in AF by cryo ablation and RF ablation. The 3D simulation of the temperature profile may be used to optimize RF and cryo ablation.
Real-Time Ethernet has become the major communication technology for modern automation and industrial control systems. On the one hand, this trend increases the need for an automation-friendly security solution, as such networks can no longer be considered sufficiently isolated. On the other hand, it shows that, despite diverging requirements, the domain of Operational Technology (OT) can derive advantage from high-volume technology of the Information Technology (IT) domain. Based on these two sides of the same coin, we study the challenges and prospects of approaches to communication security in real-time Ethernet automation systems. In order to capitalize the expertise aggregated in decades of research and development, we put a special focus on the reuse of well-established security technology from the IT domain. We argue that enhancing such technology to become automation-friendly is likely to result in more robust and secure designs than greenfield designs. Because of its widespread deployment and the (to this date) nonexistence of a consistent security architecture, we use PROFINET as a showcase of our considerations. Security requirements for this technology are defined and different well-known solutions are examined according their suitability for PROFINET. Based on these findings, we elaborate the necessary adaptions for the deployment on PROFINET.
This paper is discussing the development of a wireless Indoor Smart Gardening System with the focus on energy autonomous working. The Smart Gardening System, which is presented in this paper consists of a network of energy autonomous wireless sensor nodes which are used for monitoring important plant parameters like air temperature, soil moisture, pressure or humidity and in future to control an actuator for the plant irrigation and to measure further parameter as light and fertilizer level. Solar energy harvesting is used for powering the wireless nodes without the usage of a battery. Comparable Smart Gardening Systems are usually battery-powered. Furthermore, the overall Smart Gardening System consists of a battery powered gateway based on a Raspberry Pi 3 system, which controls the wireless nodes and collects their sensor data. The gateway is able to send the information to an internet server application and via Wi-Fi to mobile devices. Particularly the architecture of the energy autonomous wireless nodes will be considered because fully energy autonomous wireless networks could not be implemented without special concepts for the energy supply and architecture of the wireless nodes.
Nowadays, robotic systems are an integral part of many orthopedic interventions. Stationary robots improve the accuracy but also require adapted surgical workflows. Handheld robotic devices (HHRDs), however, are easily integrated into existing workflows and represent a more economical solution. Their limited range of motion is compensated by the dexterity of the surgeon. This work presents control algorithms for HHRDs with multiple degrees of freedom (DOF). These algorithms protect pre- or intraoperatively defined regions from being penetrated by the end effector (e.g., a burr) by controlling the joints as well as the device’s power. Accuracy tests on a stationary prototype with three DOF show that the presented control algorithms produce results similar to those of stationary robots and much better results than conventional techniques. This work presents novel and innovative algorithms, which work robustly, accurately, and open up new opportunities for orthopedic interventions.
This paper deals with the detection and segmentation of clouds on high-dynamic-range (HDR) images of the sky as well as the calculation of the position of the sun at any time of the year. In order to predict the movement of clouds and the radiation of the sun for a short period of time, the clouds thickness and position have to be known as precisely as possible. Consequently, the segmentation algorithm has to provide satisfactory results regardless of different weather, illumination and climatic conditions. The principle of the segmentation is based on the classification of each pixel as a cloud or as a sky. This classification is usually based on threshold methods, since these are relatively fast to implement and show a low computational burden. In order to predict if and when the sun will be covered by clouds, the position of the sun on the images has to be determined. For this purpose, the zenith and azimuth angles of the sun are determined and converted into XY coordinates.
The fisheye camera has been widely studied in the field of ground based sky imagery and robot vision since it can capture a wide view of the scene at one time. However, serious image distortion is a major drawback hindering its wider use. To remedy this, this paperproposes a lens calibration and distortion correction method for detecting clouds and forecasting solar radiation. Finally, the radial distortion of the fisheye image can be corrected by incorporating the estimated calibration parameters. Experimental results validate the effectiveness of the proposed method.
Solar irradiance prediction is vital for the power management and the cost reduction when integrating solar energy. The study is towards a ground image based solar irradiance prediction which is highly dependent on the cloud coverage. The sky images are collected by using ground based sky imager (fisheye lens). In this work, different algorithms for cloud detection being a preparation step for their segmentation are compared.