The 20 most recently published documents
Data analytics tasks on large datasets are computationally intensive and often demand the compute power of cluster environments. Yet, data cleansing, preparation, dataset characterization and statistics or metrics computation steps are frequent. These are mostly performed ad hoc, in an explorative manner and mandate low response times. But, such steps are I/O intensive and typically very slow due to low data locality, inadequate interfaces and abstractions along the stack. These typically result in prohibitively expensive scans of the full dataset and transformations on interface boundaries.
In this paper, we examine R as analytical tool, managing large persistent datasets in Ceph, a wide-spread cluster file-system. We propose nativeNDP – a framework for Near Data Processing that pushes down primitive R tasks and executes them in-situ, directly within the storage device of a cluster-node. Across a range of data sizes, we show that nativeNDP is more than an order of magnitude faster than other pushdown alternatives.
Die Förderung der Kraft-Wärme-Kopplung (KWK) in kleinen und mittleren Unternehmen der Galvanotechnik stellt ein erklärtes Ziel des Landes Baden-Württemberg und des Forschungsprojekts GalvanoFlex_BW dar. Als komplexe Energieeffizienzmaßnahme stellt die Kraft-Wärme-Kopplung erhöhte Anforderungen an die Unternehmen und das professionelle Umfeld (Beratung, Service, Handwerk, Contracting). Hemmnisse zur Umsetzung der Technologie finden sich daher sowohl innerhalb der Unternehmen als auch außerhalb. Die Hemmnisse bei der Umsetzung der Kraft-Wärme-Kopplung in der Galvanotechnik sind auf unterschiedliche Ursachen zurückzuführen, wie hohe Komplexität der KWK-Technologie, schwierige Bewertung des Gesamtnutzens im Unternehmen, mangelnde personelle Ausstattung oder auch fehlende Unternehmerentscheidungen. Empfehlungen der Forschungspartner zu deren Überwindung können aus den Ergebnisses der sozial-wissenschaftlichen Begleitforschung gewonnen werden.
Ganz gleich, ob im privaten oder beruflichen Alltag, begleiten uns digitale Medien heute nahezu überall. Dabei dienen sie nicht nur zur Unterhaltung, sondern helfen uns, Arbeitsabläufe effizienter und produktiver durchzuführen. Doch die Arbeit des Menschen ist bei Weitem nicht überflüssig geworden. Durch die steigenden Anforderungen ist die Nachfrage nach qualifiziertem Fachpersonal heute höher denn je. Währenddessen müssen Mitarbeiter in der Lage sein, mit der rasanten Entwicklung neuer Produkte und Technologien Schritt zu halten. Dabei ist eine qualitative Aus- und Weiterbildung unumgänglich. Beginnend mit der Bildung von Medienkompetenz in Schulen bis hin zur Fach- und Berufsbildung sowie beruflichen Weiterbildung, muss der Umgang mit digitalen Technologien gelehrt sein. Darüber hinaus bieten diese Technologien neue Potenziale zur Verbesserung von Bildungskonzepten und können zudem dabei helfen, den Lernerfolg zu steigern.
Diese Arbeit beschäftigt sich mit der Evaluation einer VR-basierten Lernumgebung und untersucht mögliche Auswirkungen auf den Lernerfolg durch die verkörperte Darstellung eines virtuellen Instruktors. Dazu wurde die technische Implementierung einer kollaborativen Lernumgebung vorgenommen, mit welcher anschließend eine Versuchsreihe mit 16 Probanden durchgeführt wurde. Im Hinblick auf eine mögliche Steigerung der Effizienz in der eigenständigen Bewältigung von Montageaufgaben nach unterschiedlichen Instruktionsarten, wurden keine signifikanten Leistungsverbesserungen festgestellt.
Abreinigbare Schlauchfilter kommen zur Abscheidung von Stäuben sowie staubförmigen Substanzen zum Einsatz. Aufgrund typischer Prozessbedingungen unterliegen sie während ihres Einsatzes thermischer, chemischer und mechanischer Beanspruchung. Das IGF-Projekt Nr. 18307 "Untersuchung der chemischen und thermischen Degradation von abreinigbaren Filtermedien und Verbesserung deren Beständigkeit durch Oberflächenmodifikation" hat mehrere Prüfmethoden verglichen.
In den letzten Jahren hat das Gebiet der additiven Fertigung einen unglaublichen Schub erfahren. Es haben sich kostengünstige Endkonsumerdrucker in der sogenannten "Makerszene" verbreitet, die vielfältige neue Fertigungsmöglichkeiten bieten. Überzogene Berichterstattungen über diese Möglichkeiten haben einen wahren Hype ausgelöst. Trotz der entstandenen neuen Chancen zur Fertigung von Produkten bleiben die realisierbaren Möglichkeiten oft hinter den Erwartungen zurück. Einerseits liegt das an der Teilequalität und an den zur Verfügung stehenden Materialien. Andererseits kommen im Endkonsumerbereich überwiegend Drucker auf der Basis des FDM- oder DLP-Verfahrens zum Einsatz, damit ergibt sich folglich eine sehr eingeschränkte Verfahrenspalette.
Bei der spanenden Bearbeitung metallischer Werkstücke ist Verschleiß der Werkzeuge entscheidend für die Qualität der erzeugten Bauteiloberflächen und die Kosten der eingesetzten Werkzeuge. Damit ist der Werkzeugverschleiß und dessen Ursachen maßgebliches Auflegungskriterium für die Zerspanprozesse. Verschleiß wird dabei durch eine Vielzahl unterschiedlicher Parameter beeinflusst. Neben dem Werkstückwerkstoff, dem Schneidstoff und der Beschichtung sowie der Werkzeuggeometrie, sind die Schnittgeschwindigkeit, der Vorschub, die radiale und axiale Zustellung und die Prozessmedien ausschlaggebend für die Standzeit der Werkzeuge. Weitere Effekte gehen von den Eigenschaften des Werkstücks, Werkzeugs und der Maschinen aus. diese sind verantwortlich für die Entstehung von durch Instabilitäten verursachten Verschleiß. Im Folgenden wird die Systematik der Untersuchung unterschiedlich additivierter Kühlschmierstoffe auf den Verschleiß untersucht.
Die vorliegende Erfindung betrifft ein Verfahren zum Bestimmen einer Fehlspannung eines Stromrichters, an den eine Last, insbesondere in Form einer Drehfeldmaschine wie Asynchronmaschine, angeschlossen ist, bestimmt und ggf. kompensiert wird, wobei eine Ausgangsspannung an dem Stromrichter stufen- oder schrittweise erhöht und der sich hierbei als Sprungantwort einstellende Strom gemessen wird. Die Erfindung betrifft weiterhin eine Drehfeldmaschine beispielsweise in Form einer Asynchronmaschine, mit einer Leistungselektronik umfassend einen tromrichter sowie einer Kompensationseinrichtung zum Kompensieren der Fehlspannung des Stromrichters, sowie weiterhin ein Verfahren zum Betreiben und/oder Steuern einer solchen Drehfeldmaschine, bei dem die Fehlspannung des Stromrichters bestimmt und kompensiert wird.
After more than three decades of electronic design automation, most layouts for analog integrated circuits are still handcrafted in a laborious manual fashion today. Obverse to the highly automated synthesis tools in the digital domain (coping with the quantitative difficulty of packing more and more components onto a single chip – a desire well known as More Moore), analog layout automation struggles with the many diverse and heavily correlated functional requirements that turn the analog design problem into a More than Moore challenge. Facing this qualitative complexity, seasoned layout engineers rely on their comprehensive expert knowledge to consider all design constraints that uncompromisingly need to be satisfied. This usually involves both formally specified and nonformally communicated pieces of expert knowledge, which entails an explicit and implicit consideration of design constraints, respectively.
Existing automation approaches can be basically divided into optimization algorithms (where constraint consideration occurs explicitly) and procedural generators (where constraints can only be taken into account implicitly). As investigated in this thesis, these two automation strategies follow two fundamentally different paradigms denoted as top-down automation and bottom-up automation. The major trait of top-down automation is that it requires a thorough formalization of the problem to enable a self-intelligent solution finding, whereas a bottom-up automatism –controlled by parameters– merely reproduces solutions that have been preconceived by a layout expert in advance. Since the strengths of one paradigm may compensate the weaknesses of the other, it is assumed that a combination of both paradigms –called bottom-up meets top-down– has much more potential to tackle the analog design problem in its entirety than either optimization-based or generator-based approaches alone.
Against this background, the thesis at hand presents Self-organized Wiring and Arrangement of Responsive Modules (SWARM), an interdisciplinary methodology addressing the design problem with a decentralized multi-agent system. Its basic principle, similar to the roundup of a sheep herd, is to let responsive mobile layout modules (implemented as context-aware procedural generators) interact with each other inside a user-defined layout zone. Each module is allowed to autonomously move, rotate and deform itself, while a supervising control organ successively tightens the layout zone to steer the interaction towards increasingly compact (and constraint compliant) layout arrangements. Considering various principles of self-organization and incorporating ideas from existing decentralized systems, SWARM is able to evoke the phenomenon of emergence: although each module only has a limited viewpoint and selfishly pursues its personal objectives, remarkable overall solutions can emerge on the global scale.
Several examples exhibit this emergent behavior in SWARM, and it is particularly interesting that even optimal solutions can arise from the module interaction. Further examples demonstrate SWARM’s suitability for floorplanning purposes and its application to practical place-and-route problems. The latter illustrates how the interacting modules take care of their respective design requirements implicitly (i.e., bottom-up) while simultaneously paying respect to high level constraints (such as the layout outline imposed top-down by the supervising control organ). Experimental results show that SWARM can outperform optimization algorithms and procedural generators both in terms of layout quality and design productivity. From an academic point of view, SWARM’s grand achievement is to tap fertile virgin soil for future works on novel bottom-up meets top-down automatisms. These may one day be the key to close the automation gap in analog layout design.
Type 1 diabetes is a chronic and a life threatening disease: an adjusted treatment and a proper management of the disease are crucial to prevent or delay the complications of diabetes. Although during the last decade the development of the artificial pancreas has presented great advances in diabetes care, the multiple daily injections therapy still represents the most widely used treatment option for type 1 diabetes. This work presents the proposal and first development stages of an application focused on guiding patients using the continuous glucose monitors and smart pens together with insulin and carbohydrates recommendations. Our proposal aims to develop a platform to integrate a series of innovative machine learning models and tools rigorously tested together with the use of the latest IoT devices to manage type 1 diabetes. The resulting system actually closes the loop, like the artificial pancreas, but in an intermittent way.
Due to the rising need for palliative care in Russia, it is crucial to provide timely and high-quality solutions for patients, relatives, and caregivers. A methodology for remote monitoring of patients in need of palliative care and the requirements will be developed for a hardware-software complex for remote monitoring of patients' health at home.
The potentials and opportunities created by digitized healthcare can be further customized through smart data processing and analysis using accurate patient information. This development and the associated new treatment concepts basing on digital smart sensors can lead to an increase in motivation by applying gamification approaches. This effect can also be used in the field of medical treatment, e.g. with the help of a digital spirometer combined with an app. In one of our exemplary applications, we show how to control an airplane within an app by breathing respectively inhaling and exhaling. Using this biofeedback within a game allows us to increase the motivation and fun for children that need to perform necessary exercises.
This paper investigates the possibility to effectively monitor and control the respiratory action using a very simple and non invasive technique based on a single lightweight reduced-size wireless surface electromyography (sEMG) sensor placed below the sternum. The captured sEMG signal, due to the critical sensor position, is characterized by a low energy level and it is affected by motion artifacts and cardiac noise. In this work we present a preliminary study performed on adults for assessing the correlation of the spirometry signal and the sEMG signal after the removal of the superimposed heart signal. This study and the related findings could be useful in respiratory monitoring of preterm infants.
During two researches the influence of technologies on sleep were analyzed. The first one is about the effect of light on the circadian rhythm and as consequence on sleep quality of persons in a vegetative state. The second one, which is still running, surveys the influence of several technical tools on the sleep of elderly people living in a nursing home.
In summary, we believe that current “sleep monitoring” consumer devices on the market must undergo a more robust validation process before being made available and distributed in the general public. This is especially noteworthy as there have been first reports in the literature that inaccurate feedback of such consumer devices can worry subjects and may even lead to compromised well-being of the user.
The cloud evolved into an attractive execution environment for parallel applications from the High Performance Computing (HPC) domain. Existing research recognized that parallel applications require architectural refactoring to benefit from cloud-specific properties (most importantly elasticity). However, architectural refactoring comes with many challenges and cannot be applied to all applications due to fundamental performance issues. Thus, during the last years, different cloud migration strategies have been considered for different classes of parallel applications. In this paper, we provide a survey on HPC cloud migration research. We investigate on the approaches applied and the parallel applications considered. Based on our findings, we identify and describe three cloud migration strategies.
Parallel applications are the computational backbone of major industry trends and grand challenges in science. Whereas these applications are typically constructed for dedicated High Performance Computing clusters and supercomputers, the cloud emerges as attractive execution environment, which provides on-demand resource provisioning and a pay-per-use model. However, cloud environments require specific application properties that may restrict parallel application design. As a result, design trade-offs are required to simultaneously maximize parallel performance and benefit from cloud-specific characteristics.
In this paper, we present a novel approach to assess the cloud readiness of parallel applications based on the design decisions made. By discovering and understanding the implications of these parallel design decisions on an application’s cloud readiness, our approach supports the migration of parallel applications to the cloud.We introduce an assessment procedure, its underlying meta model, and a corresponding instantiation to structure this multi-dimensional design space. For evaluation purposes, we present an extensive case study comprising three parallel applications and discuss their cloud readiness based on our approach.
In this paper, we deal with optimizing the monetary costs of executing parallel applications in cloud-based environments. Specifically, we investigate on how scalability characteristics of parallel applications impact the total costs of computations. We focus on a specific class of irregularly structured problems, where the scalability typically depends on the input data. Consequently, dynamic optimization methods are required for minimizing the costs of computation. For quantifying the total monetary costs of individual parallel computations, the paper presents a cost model that considers the costs for the parallel infrastructure employed as well as the costs caused by delayed results. We discuss a method for dynamically finding the number of processors for which the total costs based on our cost model are minimal. Our extensive experimental evaluation gives detailed insights into the performance characteristics of our approach.
Assistive environments are entering our homes faster than ever. However, there are still various barriers to be broken. One of the crucial points is a personalization of offered services and integration of assistive technologies in common objects and therefore in a regular daily routine. Recognition of sleep patterns for the preliminary sleep study is one of the Health services that could be performed in an undisturbing way. This article proposes the hardware system for the measurement of bio-vital signals necessary for initial sleep study in a nonobtrusive way. The first results confirm the potential of measurement of breathing and movement signals with the proposed system.
A clinically useful system for individual continuous health data monitoring needs an architecture that takes into account all relevant medical and technical conditions. The requirements for a health app to support such a system are collected, and a vendor independent architecture is designed that allows the collection of vital data from arbitrary wearables using a smartphone. A prototypical implementation for the main scenario shows the feasibility of the approach.
