Exposed faces of semidefinitely representable sets

A linear matrix inequality (LMI) is a condition stating that a symmetric matrix whose entries are affine linear combinations of variables is positive semidefinite. Motivated by the fact that diagonal LMIs define polyhedra, the solution set of an LMI is called a spectrahedron. Linear images of spectrahedra are called semidefinite representable sets. Part of the interest in spectrahedra and semidefinite representable sets arises from the fact that one can efficiently optimize linear functions on them by semidefinite programming, like one can do on polyhedra by linear programming. It is known that every face of a spectrahedron is exposed. This is also true in the general context of rigidly convex sets. We study the same question for semidefinite representable sets. Lasserre proposed a moment matrix method to construct semidefinite representations for certain sets. Our main result is that this method can only work if all faces of the considered set are exposed. This necessary condition complements sufficient conditions recently proved by Lasserre, Helton and Nie

Intelligent Anomaly Detection of Machine Tools based on Mean Shift Clustering

For a fault detection of machine tools, fixed intervention thresholds are usually necessary. In order to provide an autonomous anomaly detection without the need for fixed limits, recurring patterns must be detected in the signal data. This paper presents an approach for online pattern recognition on NC Code based on mean shift clustering that will be matched with drive signals. The intelligent fault detection system learns individual intervention thresholds based on the prevailing machining patterns. Using a self-organizing map, data captured during the machine’s operation are assigned to a normal or malfunction state

Intelligente Anomalieerkennung für hochflexible Produktionsmaschinen : Prozessüberwachung in der Brownfield Produktion

Unter dem Begriff "Industrie 4.0" wurden im letzten Jahrzehnt Ansätze der Dateninfra-struktur in Produktionen entwickelt und in großem Umfang angewendet. Dennoch kann das volle Potenzial datengetriebener Analysen kaum ausgeschöpft werden, da viele Produktionsanlagen durch eine hohe Komplexität und Prozessvielfalt gekennzeichnet sind. Zudem ist die Datenmenge in der Praxis meist zu gering, um selbstlernende Me-thoden anzuwenden. Die Integration von Anwenderwissen in datengetriebenen Metho-den ist bisher nicht ganzheitlich erforscht. In dieser Dissertation werden Ansätze zur Anomalieerkennung in verschiedenen hochflexiblen Produktionsmaschinen und die In-tegration von Domänenwissen eines Anwenders vorgestellt. Während sich bestehende Methoden auf das Modelltraining von sich wiederholenden gleichen Prozessen kon-zentrieren, besteht der neuartige Ansatz dieser Arbeit darin, ein Konzept zur Fehlerer-kennung mit einer sehr geringen Datenmenge zu entwickeln. Eingriffsgrenzen sind va-riabel und lassen sich durch selbstlernende Algorithmen im Falle einer Prozess- oder Produktänderung anpassen. Die Prozessdifferenzierung basiert auf einer Prozessseg-mentierung mit Methoden der Mustererkennung. Nach der Segmentierung historischer Datenströme und der Bestimmung repräsentativer Muster werden die Segmente in On-line-Signalen wiedererkannt. Nachdem ein ähnliches Segment erkannt wurde, wird eine unüberwachte Anomalieerkennung durchgeführt. Eine Anomalie-Klassifikation mit Hilfe selbstlernender Methoden und des formalisierten Domänenwissens ermöglicht die Ausgabe von Handlungsempfehlungen für den Benutzer oder Maschinenbediener. Alle entwickelten Methoden werden an drei ausgewählten industriell relevanten Anwen-dungsbeispielen validiert. Die Methoden werden in einer App implementiert

Functional Integration of Subcomponents for Hybridization of Fused Filament Fabrication

One of the main advantages of additive manufacturing by Fused Filament Fabrication is its wide variety of materials and cost-effective production systems. However, the resolution and tightness of the produced structures are limited. The following article describes a novel approach of the functional integration of stereolithographic produced subcomponents into the Fused Filament Fabrication process and the challenges during integration in terms of adhesion, taking into account different surface pretreatments. Furthermore, it is investigated how conductive polymer composites could be used successfully for conducting mechatronic subcomponents automatically. With the help of these investigations it is aimed to extend the field of application of additive manufactured plastic components

Single-Beat Noninvasive Imaging of Ventricular Endocardial and Epicardial Activation in Patients Undergoing CRT

BACKGROUND: Little is known about the effect of cardiac resynchronization therapy (CRT) on endo- and epicardial ventricular activation. Noninvasive imaging of cardiac electrophysiology (NICE) is a novel imaging tool for visualization of both epi- and endocardial ventricular electrical activation. METHODOLOGY/PRINCIPAL FINDINGS: NICE was performed in ten patients with congestive heart failure (CHF) undergoing CRT and in ten patients without structural heart disease (control group). NICE is a fusion of data from high-resolution ECG mapping with a model of the patient's individual cardiothoracic anatomy created from magnetic resonance imaging. Beat-to-beat endocardial and epicardial ventricular activation sequences were computed during native rhythm as well as during ventricular pacing using a bidomain theory-based heart model to solve the related inverse problem. During right ventricular (RV) pacing control patients showed a deterioration of the ventricular activation sequence similar to the intrinsic activation pattern of CHF patients. Left ventricular propagation velocities were significantly decreased in CHF patients as compared to the control group (1.6±0.4 versus 2.1±0.5 m/sec; p<0.05). CHF patients showed right-to-left septal activation with the latest activation epicardially in the lateral wall of the left ventricle. Biventricular pacing resulted in a resynchronization of the ventricular activation sequence and in a marked decrease of total LV activation duration as compared to intrinsic conduction and RV pacing (129±16 versus 157±28 and 173±25 ms; both p<0.05). CONCLUSIONS/SIGNIFICANCE: Endocardial and epicardial ventricular activation can be visualized noninvasively by NICE. Identification of individual ventricular activation properties may help identify responders to CRT and to further improve response to CRT by facilitating a patient-specific lead placement and device programming

Tick-borne Encephalitis from Eating Goat Cheese in a Mountain Region of Austria

We report transmission of tick-borne encephalitis virus (TBEV) in July 2008 through nonpasteurized goat milk to 6 humans and 4 domestic pigs in an alpine pasture 1,500 m above sea level. This outbreak indicates the emergence of ticks and TBEV at increasing altitudes in central Europe and the efficiency of oral transmission of TBEV