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Boost converters suffer from a bandwidth limitation caused by the right-half plane zero (RHPZ), which occurs in the control-to-output transfer function. In contrast, there are many applications that require superior dynamic behavior. Further, size and cost of boost converter systems can be minimized by reduced voltage deviations and fast transient responses in case of large signal load transients. The key idea of the proposed ΔV/Δt-intervention control concept is to adapt the controller output to its new steady state value immediately after a load transient by prediction from known parameters. The concept is implemented in a digital control circuit, consisting of an ASIC in a 110 nm-technology and a Xilinx Spartan-6 field programmable gate array (FPGA). In a boost converter with 3.5V input voltage, 6.3V output voltage, 1.2A load, and 500 kHz switching frequency, the output voltage deviations are 2.8x smaller, scaling down the output capacitor value by the same factor. The recovery times are 2.4x shorter in case of large signal load transients with the proposed concept. The control is widely applicable, as it supports constant switching frequencies and allows for duty cycle and inductor current limitations. It also shows various advantages compared to conventional control and to selected adaptive control concepts.
This article proposes several modified quasi Z-source dc/dc boost converters. These can achieve soft-switching by using a clamp-switch network comprised of an active switch and a diode in parallel with a capacitor connected across one of the inductors of the Z-source network. In this way, ringing at the transistor switching node is mitigated, and the voltage at the turn-on of the transistor is reduced. Even a zero voltage switching (ZVS) of the main transistor is possible if the capacitor in the clamp-switch network is adequately chosen. The proposed circuit structure and operating mode are described and validated through simulations and measurements on a low-power prototype.
Diese Arbeit beschäftigt sich mit dem neuen elektronischen Personalausweis. Zum einen werden in diesem Paper die Sicherheitsziele des Personalausweises und die technische Umsetzung der Architektur und Protokolle erklärt. Es wird der Ablauf einer Online-Identifizierung für einen Nutzer mithilfe des Ausweises aufgezeigt. Risiken und Schwachstellen der Technologie im Software- und Hardwarebereich werden diskutiert und die bereits erfolgten Hack-Angriffe aufgezeigt. Die Arbeit legt Möglichkeiten dar, wie sich der Nutzer vor Angriffen schützen kann. Es werden die Gründe genannt, warum der neue Personalausweis online nur schwar Anklang findet und warum die Aufklärung über die zur Verfügung stehenden Anwendungen, eine Preisreduzierung der Lesegeräte sowie die vom Europa-Parlament und Europarat erlassene eIDAS-Verordnung nicht helfen werden, um die Nutzung voranzutreiben. Ergebnisse hierfür liefert eine Nutzerstudie. Zum anderen werden Ideen genannt, wie die Nutzung der elektronischen Funktionen des Ausweises stattdessen zu fördern ist.
In dieser Ausarbeitung wird eine zeitliche Vorhersage von Erdbeben getroffen. Hierfür werden mit einem Datensatz aus Labor-Erdbeben Convolutional Neural Networks (CNN) trainiert. Die trainierten Netzwerke geben Vorhersagen, indem sie einen Input an seismischen Daten klassifizieren. Durch das Klassifizieren kann das CNN die zeitliche Entfernung zum nächsten Erdbeben vorhersagen. Es werden hierfür zwei Ansätze miteinander verglichen. Beim ersten Ansatz werden die Originaldaten in ein CNN gegeben. Beim zweiten Ansatz wird vor dem CNN eine Vorverarbeitung der Daten mit den Mel Frequency Cepstral Coefficients (MFCC) durchgeführt. Es zeigt sich, dass mit beiden Ansätzen eine gute Klassifikation möglich ist. Die Kombination aus MFCC und CNN liefert die besseren quantitativen Ergebnisse. Hierbei konnte eine Genauigkeit von 65 % erreicht werden.
Database management systems (DBMS) are critical performance components in large scale applications under modern update intensive workloads. Additional access paths accelerate look-up performance in DBMS for frequently queried attributes, but the required maintenance slows down update performance. The ubiquitous B+ tree is a commonly used key-indexed access path that is able to support many required functionalities with logarithmic access time to requested records. Modern processing and storage technologies and their characteristics require reconsideration of matured indexing approaches for today's workloads. Partitioned B-trees (PBT) leverage characteristics of modern hardware technologies and complex memory hierarchies as well as high update rates and changes in workloads by maintaining partitions within one single B+-Tree. This paper includes an experimental evaluation of PBTs optimized write pattern and performance improvements. With PBT transactional throughput under TPC-C increases 30%; PBT results in beneficial sequential write patterns even in presence of updates and maintenance operations.
Workshops and tutorials
(2018)
The 19th International Conference on Product-Focused Software Process Improvement (PROFES 2018) hosted two workshops and three tutorials. The workshops and tutorials complemented and enhanced the main conference program, offering a wider knowledge perspective around the conference topics. The topics of the two workshops were Hybrid Development Approaches in Software Systems Development (HELENA) and Managing Quality in Agile & Rapid Software Development Processes (QUaSD). The topics of the tutorials were The human factor in agile transitions – using the personas concept in agile oaching, Process Management 4.0 – Best Practices, and Domain-specific languages for specification, development, and testing of autonomous systems.
Introduction: Even if there is a standard procedure of CI surgery, especially in pediatric surgery surgical steps often differ individually due to anatomical variations, malformations or unforseen events. This is why every surgical report should be created individually, which takes time and relies on the correct memory of the surgeon. A standardized recording of intraoperative data and subsequent storage as well as text processing would therefore be desirable and provides the basis for subsequent data processing, e.g. in the context of research or quality assurance.
Method: In cooperation with Reutlingen University, we conducted a workflow analysis of the prototype of a semi-automatic checklist tool. Based on automatically generated checklists generated from BPMN models a prototype user interface was developed for an android tablet. Functions such as uploading photos and files, manual user entries, the interception of foreseeable deviations from the normal course of operations and the automatic creation of OP documentation could be implemented. The system was tested in a remote usability test on a petrous bone model.
Result: The user interface allows a simple intuitive handling, which can be well implemented in the intraoperative setting. Clinical data as well as surgical steps could be individually recorded and saved via DICOM. An automatic surgery report could be created and saved.
Summary: The use of a dynamic checklist tool facilitates the capture, storage and processing of surgical data. Further applications in clinical practice are pending.
Der elektrische Wirkungsgrad stellt eines der wichtigsten Bewertungskriterien für BHKW dar, da über diese Größe ausgedrückt wird, wie viel des Wertproduktes „elektrische Energie“ bezogen auf die eingesetzte oder aufzuwendende Brennstoffenergie produziert werden kann. Ein hoher elektrischer Wirkungsgrad ist somit gleichbedeutend mit hohen Erlösen aus dem Verkauf der erzeugten elektrischen Energie und damit eine grundlegende Voraussetzung für einen wirtschaftlichen Betrieb eines BHKWs. Folglich sind die Hersteller von BHKW bestrebt, den elektrischen Wirkungsgrad ihrer Geräte kontinuierlich zu verbessern und nach oben zu treiben. Dieses Bemühen zeigt sich eindrucksvoll an der Entwicklung der mechanischen Effizienz von Gasmotoren der Firma GE Jenbacher. Während mit Motoren der Baureihe 6 im Leistungsbereich 1,8 – 4,4 MWel im Jahr 1988 eine mechanische Effizienz von 34% erreichbar war, liegt dieser Wert mittlerweile bei etwa 47,5%. Diese enorme Steigerung konnte im Wesentlichen durch eine Erhöhung des mittleren effektiven Zylinderarbeitsdrucks von etwa 10 bar im Jahr 1988 auf derzeit 24 bar erzielt werden. Dabei hilft der Magerbetrieb, der gleichzeitig ein Zurückdrängen der NOx-Emissionen bewirkt, die Klopfgrenze zu höheren Drücken hin zu verschieben. Eine sichere Zündung des Gas-Luft-Gemisches wird durch die Vorkammerzündung erreicht.
Context: Companies that operate in the software-intensive business are confronted with high market dynamics, rapidly evolving technologies as well as fast-changing customer behavior. Traditional product roadmapping practices, such as fixed-time-based charts including detailed planned features, products, or services typically fail in such environments. Until now, the underlying reasons for the failure of product roadmaps in a dynamic and uncertain market environment are not widely analyzed and understood.
Objective: This paper aims to identify current challenges and pitfalls practitioners face when developing and handling product roadmaps in a dynamic and uncertain market environment.
Method: To reach our objective we conducted a grey literature review (GLR).
Results: Overall, we identified 40 relevant papers, from which we could extract 11 challenges of the application of product roadmapping in a dynamic and uncertain market environment. The analysis of the articles showed that the major challenges for practitioners originate from overcoming a feature-driven mindset, not including a lot of details in the product roadmap, and ensuring that the content of the roadmap is not driven by management or expert opinion.
Objective: This paper aims at getting an understanding of current problems and challenges with roadmapping processes in companies that are facing volatile markets with innovative products. It also aims at gathering ideas and attempts on how to react to those challenges.
Method: As an initial step towards the objectice a semi-structured expert interview study with a case company in the Smart Home domain was conducted. Four employees from the case company with different roles around product roadmaps have been interviewed and a content analysis of the data has been performed.
Results: The study shows a significant consensus among the interviewees about several major challenges and the necessity to change the traditional roadmapping process and format. The interviewees stated that based on their experience traditional feature-based product roadmaps are increasingly losing their benefits (such as good planning certainty) in volatile environments. Furthermore, the ability to understand customer needs and behaviors has become highly important for creating and adjusting product roadmaps. The interviewees see the need for both, sufficiently stable goals on the roadmap and flexibility with respect to products or features to be developed. To reach this target the interviewees proposed to create roadmaps based on outcome goals instead of product features. In addition, it was proposed to decrease the level of detail of the roadmaps and to emphasize the long-term view. Decisions about which feature to develop should be open as long as possible. Expected benefits of such a new way of product roadmapping are higher user centricity, a stable overall direction, more flexibility with respect to development decisions, and less breaking of commitments.
”I have never seen one who loves virtue as much as he loves beauty,” Confucius once said. If beauty is more important as goodness, it becomes clear why people invest so much effort in their first impression. The aesthetic of faces has many aspects and there is a strong correlation to all characteristics of humans, like age and gender. Often, research on aesthetics by social and ethic scientists lacks sufficient labelled data and the support of machine vision tools. In this position paper we propose the Aesthetic-Faces dataset, containing training data which is labelled by Chinese and German annotators. As a combination of three image subsets, the AF-dataset consists of European, Asian and African people. The research communities in machine learning, aesthetics and social ethics can benefit from our dataset and our toolbox. The toolbox provides many functions for machine learning with state-of-the-art CNNs and an Extreme-Gradient-Boosting regressor, but also 3D Morphable Model technolo gies for face shape evaluation and we discuss how to train an aesthetic estimator considering culture and ethics.
Several studies analyzed existing Web APIs against the constraints of REST to estimate the degree of REST compliance among state-of-the-art APIs. These studies revealed that only a small number of Web APIs are truly RESTful. Moreover, identified mismatches between theoretical REST concepts and practical implementations lead us to believe that practitioners perceive many rules and best practices aligned with these REST concepts differently in terms of their importance and impact on software quality. We therefore conducted a Delphi study in which we confronted eight Web API experts from industry with a catalog of 82 REST API design rules. For each rule, we let them rate its importance and software quality impact. As consensus, our experts rated 28 rules with high, 17 with medium, and 37 with low importance. Moreover, they perceived usability, maintainability, and compatibility as the most impacted quality attributes. The detailed analysis revealed that the experts saw rules for reaching Richardson maturity level 2 as critical, while reaching level 3 was less important. As the acquired consensus data may serve as valuable input for designing a tool-supported approach for the automatic quality evaluation of RESTful APIs, we briefly discuss requirements for such an approach and comment on the applicability of the most important rules.
In order to explore an image, the human eye functions like a spotlight, scanning the content from one object to the next. This visual search behavior is implemented with the help of attention control. The following work surveys the visual search behavior in "Wimmelpictures", a special type of busy pictures. The research objective is to analyze different search strategies and to work out possible differences concerning age and gender. The university experiment is carried out by an eye tracker that records the fixations and saccades of the test persons. The results indicate three forms of search strategy: based on a pattern, based on feature selection, or a mixture of both. Our data shows the search for special features of the target is the most successful. Furthermore there are no differences concerning gender but some concerning age. All age groups need more time to locate the target with an increasing number of distractors in the image. The size of the target is also relevant as a larger target is found more quickly than the smaller one.
Software development consists to a large extend of humanbased processes with continuously increasing demands regarding interdisciplinary team work. Understanding the dynamics of software teams can be seen as highly important to successful project execution. Hence, for future project managers, knowledge about non-technical processes in teams is significant. In this paper, we present a course unit that provides an environment in which students can learn and experience the impact of group dynamics on project performance and quality. The course unit uses the Tuckman model as theoretical framework, and borrows from controlled experiments to organize and implement its practical parts in which students then experience the effects of, e.g., time pressure, resource bottlenecks, staff turnover, loss of key personnel, and other stress factors. We provide a detailed design of the course unit to allow for implementation in further software project management courses. Furthermore, we provide experiences obtained from two instances of this unit conducted in Munich and Karlskrona with 36 graduate students. We observed students building awareness of stress factors and developing counter measures to reduce impact of those factors. Moreover, students experienced what problems occur when teams work under stress and how to form a performing team despite exceptional situations.