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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.
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).
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.
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.
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.
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.
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.
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.
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.
Printed Electronics (PE) is a promising technology that provides mechanical flexibility and low-cost fabrication. These features make PE the key enabler for emerging applications, such as smart sensors, wearables, and Internet of Things (IoTs). Since these applications need secure communication and/or authentication, it is vital to utilize security primitives for cryptographic key and identification. Physical Unclonable Functions (PUF) have been adopted widely to provide the secure keys. In this work, we present a weak PUF based on Electrolyte-gated FETs using inorganic inkjet printed electronics. A comprehensive analysis framework including Monte Carlo simulations based on real device measurements is developed to evaluate the proposed PE-PUF. Moreover, a multi-bit PE-PUF design is proposed to optimize area usage. The analysis results show that the PE-PUF has ideal uniqueness, good reliability, and can operates at low voltage which is critical for low-power PE applications. In addition, the proposed multi-bit PE-PUF reduces the area usage around 30%.
Cardiac resynchronization therapy (CRT) with hemodynamic optimized biventricular pacing is an established therapy for heart failure patients with sinus rhythm, reduced left ventricular ejection fraction and wide QRS complex. The aim of the study was to evaluate electrical right and left cardiac atrioventricular delay and left atrial delay in CRT responder and non-responder with sinus rhythm.
Methods: Heart failure patients with New York Heart Association class 3.0 ± 0.3, sinus rhythm and 27.7 ± 6.1% left ventricular ejection fraction were measured by surface ECG and transesophageal bipolar left atrial and left ventricular ECG before implantation of CRT devices. Electrical right cardiac atrioventricular delay was measured between onset of P wave and onset of QRS complex in the surface ECG, left cardiac atrioventricular delay between onset of left atrial signal and onset of left ventricular signal in the transesophageal ECG and left atrial delay between onset and offset of left atrial signal in the transesophageal ECG.
Results: Electrical atrioventricular and left atrial delay were 196.9 ± 38.7 ms right and 194.5 ± 44.9 ms left cardiac atrioventricular delay, and 47.7 ± 13.9 ms left atrial delay. There were positive correlation between right and left cardiac atrioventricular delay (r = 0.803 P < 0.001) and negative correlation between left atrial delay and left ventricular ejection fraction (r = −0.694 P = 0.026) with 67% CRT responder.
Conclusions: Transesophageal electrical left cardiac atrioventricular delay and left atrial delay may be useful preoperative atrial desynchronization parameters to improve CRT optimization.
The high frequency (HF) catheter ablation is the gold standard for the therapy of many cardiac tachyarrhythmias, such as atrioventricular node re-entry tachycardia (AVNRT), atrioventricular re-entry tachycardia (AVRT) or atrial flutter (AFL). The aim of the study was to simulate the HF ablation of AVNRT, AVRT, AFL and its heat propagation in reference to the supplied power with different electrode material and electrode size. The modeling and simulation were performed with the thermal and electromagnetic simulation software CST® (Computer Simulation Technology, Darmstadt). The modeling and simulation were carried out using ablation catheters with 4 mm tip electrode and 8 mm tip electrode with different electrode materials. Both electrode types were made of platinum and gold respectively. For the measurement of the heat propagation in the heart tissue, the catheters were integrated in the Offenburg heart rhythm model. The HF ablation procedures were performed with the 4 mm platinum tip electrode, with an application duration of 45 seconds and a power output of 40 watts. The HF ablation of the atrioventricular node slow pathway produced a maximum temperature of 66.33 °C. The Kent bundle HF ablation in the left atrium achieved a maximum temperature of 67.14 °C. The HF ablation of the right atrial isthmus resulted 65.96 °C. The 8 mm distal platinum tip electrode and a power output of 60 watts reached 72.85 °C. The 8 mm distal gold tip electrode and a power output of 60 watt reached 64.66 °C, due to the improved thermal conductivity of gold. Virtual heart and ablation electrode models allow the static and dynamic simulation of HF ablation with different electrode material and electrode size. The 3D simulation of the temperature profile may be used to optimize the AVNRT, AVRT and AFL HF ablation.