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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.
Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach. Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts. The study focuses on mid-sized and large companies developing software-intensive products in dynamic and technical market environments. Method: We conducted semi structured expert interviews with 15 experts from 13 German companies and conducted a thematic data analysis. Results: The analysis showed that a significant number of companies is still struggling with traditional feature based product-roadmapping and opinion based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and the establishing discovery activities.
Context: Organizations are increasingly challenged by dynamic and technical market environments. Traditional product roadmapping practices such as detailed and fixed long-term planning typically fail in such environments. Therefore, companies are actively seeking ways to improve their product roadmapping approach.
Goal: This paper aims at identifying problems and challenges with respect to product roadmapping. In addition, it aims at understanding how companies succeed in improving their roadmapping practices in their respective company contexts.
Method: We conducted semi-structured expert interviews with 15 experts from 13 German companies and conducted athematic data analysis.
Results: The analysis showed that a significant number of companies is still struggling with traditional feature-based product-roadmapping and opinion-based prioritization of features. The most promising areas for improvement are stating the outcomes a company is trying to achieve and making them part of the roadmap, sharing or co-developing the roadmap with stakeholders, and establishing discovery activities.
Among the multitude of software development processes available, hardly any is used by the book. Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods— so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. In this paper, we make a first step towards devising such guidelines. Grounded in 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods. Using an 85% agreement level in the participants’ selections, we provide two examples illustrating how hybrid development methods are characterized by the practices they are made of. Our evidence-based analysis approach lays the foundation for devising hybrid development methods.
Regardless of company size or industry sector, a majority of project teams and companies use customized processes that combine different development methods-so-called hybrid development methods. Even though such hybrid development methods are highly individualized, a common understanding of how to systematically construct synergetic practices is missing. Based on 1,467 data points from a large-scale online survey among practitioners, we study the current state of practice in process use to answer the question: What are hybrid development methods made of? Our findings reveal that only eight methods and few practices build the core of modern software development. This small set allows for statistically constructing hybrid development methods.
Rapid prototyping platforms reduce development time by allowing quick prototyping of a prototype idea and achieve more time for actual application development with user interfaces. This approach has long been followed in technical platforms, such as the Arduino. To transfer this form of prototyping to wearables, WearIT is presented in this paper.WearIT consists of four components as a wearable prototyping platform: (1) a vest, (2) sensor and actuator shields, (3) its own library and (4) a motherboard consisting of Arduino, Raspberry Pi, a board and a GPS module. As a result, a wearable prototype can be quickly developed by attaching sensor and actuator shields to the WearIT vest. These sensor and actuator shields can then be programmed through the WearIT library. Via Virtual Network Computing (VNC) with a remote computer, the screen contents of the Raspberry Pi can be accessed and the Arduino be programmed.
Der folgende Artikel befasst sich mit Wearables für Pferde. Ziel ist es, die Sicherheit der Tiere bei einem Ausbruch von einer Weide zu erhöhen und damit Personen- und Sachschäden zu minimieren. Hierzu wird der Stand der Technik zur Standortbestimmung im Freien zusammengetragen und durch eine Klassifizierung der unterschiedlichen Ansätze ermittelt, welche Standortbestimmung pferdegerecht erscheint. Zudem soll ein Fragebogen konzipiert werden, um Charakteristiken und Funktionalitäten für einen Prototypen festzustellen.
Wasted paradise – imagining the Maldives without the garbage island of Thilafushi : Version 1.2
(2016)
To address the high level of waste production in the Maldives, the local government decided to transform the coral island of Thilafushi into an immense waste dumb in 1992. Meanwhile, each day, 330 tons of waste is ferried to Thilafushi. The policy had the positive consequence of relieving the garbage burden in Malé, the main island, and surrounding tourist atolls. However, it can also lead to serious environmental and economic damage in the long range. First, the garbage is in visual range of one of the most prominent tourist destinations. Second, if the wind blows a certain way, unfiltered fumes from burning waste travels to tourist atolls. Third, water quality can erode as hazardous waste from batteries and other toxic waste is floating in the ocean. Over time, these effects can accumulate to significantly hamper the number of tourists that travel to the Maldives – one of the state’s main sources of financial income. In our paper, we lay out the situation in more detail and translate it into a simulation model. We test different policies to propose the Maldives government how to better solve the waste problem.
Digital Enterprise Architecture allows multiple viewpoints on a company’s IT landscape. To gain valuable information out of huge amounts of operational data, it is indispensable to have both an understanding of the operations architecture and an engine capable of managing Big Data. The mechanism of understanding huge amounts of data is based on three main steps: collect, process and use. The main idea is focused on extracting valuable information out of Big Data to make better design decisions. The Elastic Stack is an open-source solution to comfortably and quickly handle Big Data scenarios.
In dieser Ausarbeitung wird auf Visualisierungsmöglichkeiten von neuronalen Netzen eingegangen. Ein neuronales Netz scheint zuerst nicht von außen einsehbar und ist somit für viele eine Blackbox. Häufig genutzte Python-Bibliotheken, zum Beispiel TensorFlow, werden vorgestellt und deren Stärken wie auch Schwächen präsentiert. Anhand dieser werden bereits bestehende Visualisierungen gezeigt und ihr derzeitiger Einsatz wird erläutert. Durch einen Vergleich soll ersichtlich werden, welche Bibliothek am meisten Daten während des Trainings liefert, damit diese Informationen weiter verarbeitet werden. Diese Daten sollen so visualisiert werden, dass sie bei der Entwicklung eines neuronalen Netzes unterstützend sind. Ziel ist es, auf die Möglichkeiten einzugehen, welche geboten werden können. Durch eine Vereinfachung des Debuggings neuronaler Netze sollen weiterführende Entwicklungen in diese Richtung unterstützt werden.
In times of dynamic markets, enterprises have to be agile to be able to quickly react to market influences. Due to the increasing digitization of products, the enterprise IT often is affected when business models change. Enterprise Architecture Management (EAM) targets a holistic view of the enterprise’ IT and their relations to the business. However, Enterprise Architectures (EA) are complex structures consisting of many layers, artifacts and relationships between them. Thus, analyzing EA is a very complex task for stakeholders. Visualizations are common vehicles to support analysis. However, in practice visualization capabilities lack flexibility and interactivity. A solution to improve the support of stakeholders in analyzing EAs might be the application of visual analytics. Starting from a systematic literature review, this article investigates the features of visual analytics relevant for the context of EAM.
In this paper we describe an interactive web-based visual analysis tool for Formula one races. It first provides an overview about all races on a yearly basis in a calendar-like representation. From this starting point, races can be selected and visually inspected in detail. We support a dynamic race position diagram as well as a more detailed lap times line plot for showing the drivers’ lap times in comparison. Many interaction techniques are supported like selections, filtering, highlighting, color coding, or details-on demand. We illustrate the usefulness of our visualization tool by applying it to a Formula one dataset while we describe the different dynamic visual racing patterns for a number of selected races and drivers.
Based on well-established robotic concepts of autonomous localization and navigation we present a system prototype to assist camera-based indoor navigation for human utilization implemented in the Robot Operating System (ROS). Our prototype takes advantage of state-of-the-art computer vision and robotic methods. Our system is designed for assistive indoor guidance. We employ a vibro tactile belt to serve as a guiding device to render derived motion suggestions to the user via vibration patterns. We evaluated the effectiveness of a variety of vibro-tactile feedback patterns for guidance of blindfolded users. Our prototype demonstrates that a vision-based system can support human navigation, and may also assist the visually impaired in a human-centered way.
Today the optimization of metal forming processes is done using advanced simulation tools in a virtual process, e.g. FEM-studies. The modification of the free parameters represents the different variants to be analysed. So experienced engineers may derive useful proposals in an acceptable time if good initial proposals are available. As soon as the number of free parameters growths or the total process takes long times and uses different succeeding forming steps it might be quite difficult to find promising initial ideas. In metal forming another problem has to be considered. The optimization using a series of local improvements, often called a gradient approach may find a local optimum, but this could be far away from a satisfactory solution. Therefore non-deterministic approaches, e.g. Bionic Optimization have to be used. These approaches like Evolutionary Optimization or Particle Swarm Optimization are capable to cover a large range of high dimensional optimization spaces and discover many local optima. So the chance to include the global optimum increases when using such non-deterministic methods. Unfortunately these bionic methods require large numbers of studies of different variants of the process to be optimized. The number of studies tends to increase exponentially with the number of free parameters of the forming process. As the time for one single study might be not too small as well, the total time demand will be inacceptable, taking weeks to months even if high performance computing will be used. Therefore the optimization process needs to be accelerated. Among the many ideas to reduce the time and computer power requirement Meta- and Hybrid Optimization seem to produce the most efficient results. Hybrid Optimization often consists of global searches of promising regions within the parameter space. As soon as the studies indicate that there could be a local optimum, a deterministic study tries to identify this local region. If it shows better performance than other optima found until now, it is preserved for a more detailed analysis. If it performs worse than other optima the region is excluded from further search. Meta-Optimization is often understood as the derivation of Response Surfaces of the functions of free parameters. Once there are enough studies performed, the optimization is done using the Response Surfaces as representatives e.g. for the goal and the restrictions of the optimization problem. Having found regions where interesting solutions are to be expected, the studies available up to now are used to define the Response Surfaces. In many cases low degree polynomials are used, defining their coefficients by least square methods. Both proposals Hybrid Optimization and Meta-Optimization, sometimes used in combination often help to reduce the total optimization processes by large numbers of variants to be studied. In consequence they are highly recommended when dealing with time consuming optimization studies.
In diesem Beitrag wird ein neuer Ansatz vorgestellt, welcher eine schwerkraftreduzierte Navigation innerhalb einer VR-Umgebung erlaubt, wie beispielsweise ein simulierter Mondspaziergang. Zur Navigation in der VR-Umgebung wird der Cyberith Virtualizer ein-gesetzt. Die Schwerkraftsimulation erfolgt mittels eines einstellbaren Gurtsystems, das anelastischen Seilen aufgehängt wird und abgestufte Schwerkraftkompensationen erlaubt. Als Umgebung wurde ein Raumschiffszenario sowie eine Mondoberfläche generiert. Hier sind in der aktuellen Anwendung einfache Interaktionen möglich. In Anlehnung an existierende Gravity Offload Systeme wird die Lösung ViRGOS bezeichnet. ViRGOS wurde bereits bei verschiedenen Besuchsterminen und Hochschulevents eingesetzt, so dass erste Rückmeldungen von Nutzern eingeholt werden konnten.
Verification of an active time constant tuning technique for continuous-time delta-sigma modulators
(2022)
In this work we present a technique to compensate the effects of R-C / g m -C time-constant (TC) errors due to process variation in continuous-time delta-sigma modulators. Local TC error compensation factors are shifted around in the modulator loop to positions where they can be implemented efficiently with finely tunable circuit structures, such as current-steering digital-to-analog converters (DAC). We apply our technique to a third-order, single-bit, low-pass continuous-time delta-sigma modulator in cascaded integrator feedback structure, implemented in a 0.35-μm CMOS process. A tuning scheme for the reference currents of the feedback DACs is derived as a function of the individual TC errors and verified by circuit simulations. We confirm the tuning technique experimentally on the fabricated circuit over a TC parameter variation range of ±20%. Stable modulator operation is achieved for all parameter sets. The measured performances satisfy the expectations from our theoretical calculations and circuit-level simulations.
Vergleichende Analyse des YouTube-Auftritts von privat- und öffentlich-rechtlichen Sendegruppen
(2020)
Lange wurde das Internet als Antagonismus zum Fernsehen gesehen. Es wurde dementsprechend zur Zuschauerrück- bzw. -gewinnung genutzt, was sich allerdings als ineffizient erwies. Inzwischen haben die einzelnen Sendegruppen das Internet jedoch als mediale Erweiterung erkannt und genutzt. Durch diese späte Akzeptanz zeigen sich starke Unterschiede im Umfang und der Vorgehensweise hinsichtlich der Nutzung des Internets als zusätzliches Medium. Am besten lässt sich dies in einem Vergleich in Bezug auf die wichtigste videotechnische Social Media Plattform YouTube darstellen.
In diesem Vergleich sollen die einzelnen Sendegruppen hinsichtlich ihrer wahrgenommenen Vorteile, Nachteile und Attraktivität bezogen auf das Nutzerverhalten und die Nutzermeinung bewertet werden. Die zielgruppenorientierte Optimierung des YouTube-Auftrittes ist von außerordentlich hoher Bedeutung für die zukünftige Marktdurchdringung.
Artificial Intelligence enables innovative applications, and applications based on Artificial Intelligence are increasingly important for all aspects of the Digital Economy. However, the question of how AI resources such as tools and data can be linked to provide an AI-capability and create business value is still open. Therefore, this paper identifies the value-creating mechanisms of connectionist artificial intelligence using a capability-oriented view and points out the connections to different kinds of business value. The analysis supports an agenda that identifies areas that need further research to understand the mechanism of value creation in connectionist artificial intelligence.
Product engineering and subsequent phases of product lifecycles are predominantly managed in isolation. Companies therefore do not fully exploit potentials through using data from smart factories and product usage. The novel intelligent and integrated Product Lifecycle Management (i²PLM) describes an approach that uses these data for product engineering. This paper describes the i²PLM, shows the cause-and-effect relationships in this context and presents in detail the validation of the approach. The i²PLM is applied and validated on a smart product in an industrial research environment. Here, the subsequent generation of a smart lunchbox is developed based on production and sensor data. The results of the validation give indications for further improvements of the i²PLM. This paper describes how to integrate the i²PLM into a learning factory.
Applications often need to be deployed in different variants due to different customer requirements. However, since modern applications often need to be deployed using multiple deployment technologies in combination, such as Ansible and Terraform, the deployment variability must be considered in a holistic way. To tackle this, we previously developed Variability4TOSCA and the prototype OpenTOSCA Vintner, which is a TOSCA preprocessing and management layer that implements Variability4TOSCA. In this demonstration, we present a detailed case study that shows how to model a deployment using Variability4TOSCA, how to resolve the variability using Vintner, and how the result can be deployed.
Recognizing actions of humans, reliably inferring their meaning and being able to potentially exchange mutual social information are core challenges for autonomous systems when they directly share the same space with humans. Today’s technical perception solutions have been developed and tested mostly on standard vision benchmark datasets where manual labeling of sensory ground truth is a tedious but necessary task. Furthermore, rarely occurring human activities are underrepresented in such data leading to algorithms not recognizing such activities. For this purpose, we introduce a modular simulation framework which offers to train and validate algorithms on various environmental conditions. For this paper we created a dataset, containing rare human activities in urban areas, on which a current state of the art algorithm for pose estimation fails and demonstrate how to train such rare poses with simulated data only.
Engineers of the research project “Digital Product Life-Cycle” are using a graph-based design language to model all aspects of the product they are working on. This abstract model is the base for all further investigations, developments and implementations. In particular at early stages of development, collaborative decision making is very important. We propose a semantic augmented knowledge space by means of mixed reality technology, to support engineering teams. Therefore we present an interaction prototype consisting of a pico projector and a camera. In our usage scenario engineers are augmenting different artefacts in a virtual working environment. The concept of our prototype contains both an interaction and a technical concept. To realise implicit and natural interactions, we conducted two prototype tests: (1) A test with a low-fidelity prototype and (2) a test by using the method Wizard of Oz. As a result, we present a prototype with interaction selection using augmentation spotlighting and an interaction zoom as a semantic zoom.
Using measurement and simulation for understanding distributed development processes in the Cloud
(2017)
Organizations increasingly develop software in a distributed manner. The Cloud provides an environment to create and maintain software-based products and services. Currently, it is widely unknown which software processes are suited for Cloud-based development and what their effects in specific contexts are. This paper presents a process simulation to study distributed development in the Cloud. We contribute a simulation model, which helps analyzing different project parameters and their impact on projects carried out in the Cloud. The simulator helps reproducing activities, developers, issues and events in the project, and it generates statistics, e.g., on throughput, total time, and lead and cycle time. The aim of this simulation model is thus to analyze the tradeoffs regarding throughput, total time, project size, and team size. Furthermore, the modified simulation model aims to help project managers select the most suitable planning alternative. Based on observed projects in Finland and Spain, we simulated a distributed project using artificial and real data. Particularly, we studied the variables project size, team size, throughput, and total project duration. A comparison of the real project data with the results obtained from the simulation shows the simulation producing results close to the real data, and we could successfully replicate a distributed software project. By improving the understanding of distributed development processes, our simulation model thus supports project managers in their decision-making.
A sequence of transactions represents a complex and multi dimensional type of data. Feature construction can be used to reduce the data´s dimensionality to find behavioural patterns within such sequences. The patterns can be expressed using the blue prints of the constructed relevant features. These blue prints can then be used for real time classification on other sequences.
The coupling of the heat and power sector is required as supply and demand in the German electricity mix drift further and further apart with a high percentage of renewable energy. Heat pumps in combination with thermal energy storage systems can be a useful way to couple the heat and power sectors. This paper presents a hardware-in the-loop test bench for experimental investigation of optimized control strategies for heat pumps. 24-hour experiments are carried out to test whether the heat pump is able to serve optimized schedules generated by a MATLAB algorithm. The results show that the heat pump is capable of following the generated schedules, and the maximum deviation of the operational time between schedule and experiment is only 3%. Additionally, the system can serve the demand for space heating and DHW at any time.
Avatars are in use when interacting in virtual environments in different contexts, in collaborative work, as well as in gaming and also in virtual meetings with friends. Therefore it is important to understand how the relationship between user and avatar works. In this study, an online survey is used to determine how the perception of an avatar changes in different contexts by relating it to existing avatar relationship typologies. Additionally, it is determined whether in each context a realistic, abstract or comic-like representation is preferred by the participants. One result was a preference of low poly representations in the work context, which are associated with the perception of the avatar as a tool. In the context of meeting friends, a realistic representation is perceived as more appropriate, which is perceived as an accurate self-representation. In the gaming context, the results are less clear, which can be attributed to different gaming preferences. Here, unlike in the other contexts, a comic-like representation is also perceived as appropriate, which is associated with the perception of the avatar as a friend. A symbiotic user-avatar relationship is not directly related to any form of representation, but always lies in the midfield, which is attributed to the fact that it represents a whole spectrum between other categories.
Going forward with the requirements of missions to the Moon and further into deep space, the European Space Agency is investigating new methods of astronaut training that can help accelerate learning, increase availability and reduce complexity and cost in comparison to currently used methods. To achieve this, technologies such as virtual reality may be utilized. In this paper, an investigation into the benefits of using virtual reality as a means for extravehicular activity training in comparison to conventional training methods, such as neutral buoyancy pools is given. To help determine the requirements and current uses of virtual reality for extravehicular activity training first hand tests of currently available software as well as expert interviews are utilized. With this knowledge a concept is developed that may be used to further advance training methods in virtual reality. The resulting concept is used as a basis for development of a prototype to showcase user interactions and locomotion in microgravity simulations.
The stimulation of user engagement has received significant attention in extant research. However, the theory of antecedents for user engagement with an initial electronic word-of-mouth (eWoM) communication is relatively less developed. In an investigation of 576 unique user postings across independent Facebook (FB) communities for two German firms, we contribute to the extant knowledge on user engagement in two different ways. First, we explicate senders’ prior usage experience and the extent of their acquaintance with other community members as the two key drivers of user engagement across a product and a service community. Second, we reveal that these main effects differ according to the type of community. In service communities, experience has a stronger impact on user engagement; whereas, in product communities, acquaintance is more important.
This paper examines the efficacy of social media systems in customer complaint handling. The emergence of social media, as a useful complement and (possibly) a viable alternative to the traditional channels of service delivery, motivates this research. The theoretical framework, developed from literature on social media and complaint handling, is tested against data collected from two different channels (hotline and social media) of a German telecommunication services provider, in order to gain insights into channel efficacy in complaint handling. We contribute to the understanding of firm’s technology usage for complaint handling in two ways:
(a) by conceptualizing and evaluating complaint handling quality across traditional and social media channels and (b) by comparing the impact of complaint handling quality on key performance outcomes such as customer loyalty, positive word-of-mouth, and crosspurchase intentions across traditional and social media channels.