Informatik
Refine
Year of publication
- 2017 (88) (remove)
Document Type
- Conference proceeding (72)
- Journal article (12)
- Working Paper (2)
- Book chapter (1)
- Patent / Standard / Guidelines (1)
Is part of the Bibliography
- yes (88) (remove)
Institute
- Informatik (88)
Publisher
Smart meter based business models for the electricity sector : a systematical literature research
(2017)
The Act on the Digitization of the Energy Transition forces German industries and households to introduce smart meters in order to save engery, to gain individual based electricity tariffs and to digitize the energy data flow. Smart meter can be regarded as the advancement of the traditional meter. Utilizing this new technology enables a wide range of innovative business models that provide additional value for the electricity suppliers as well as for their customers. In this study, we followed a two-step approach. At first, we provide a state-of-the-art comparison of these business models found in the literature and identify structural differences in the way they add value to the offered products and services. Secondly, the business models are grouped into categories with respect to customer segmetns and the added value to the smart grid. Findings indicate that most business models focus on the end-costumer as their main customer.
Towards a practical maintainability quality model for service- and microservice-based systems
(2017)
Although current literature mentions a lot of different metrics related to the maintainability of service-based systems (SBSs), there is no comprehensive quality model (QM) with automatic evaluation and practical focus. To fill this gap, we propose a Maintainability Model for Services (MM4S), a layered maintainability QM consisting of service properties (SPs) related with automatically collectable Service Metrics (SMs). This research artifact created within an ongoing Design Science Research (DSR) project is the first version ready for detailed evaluation and critical feedback. The goal of MM4S is to serve as a simple and practical tool for basic maintainability estimation and control in the context of BSs and their specialization
microservice-based systems (μSBSs).
In a time of digital transformation, the ability to quickly and efficiently adapt software systems to changed business requirements becomes more important than ever. Measuring the maintainability of software is therefore crucial for the long-term management of such products. With service-based systems (SBSs) being a very important form of enterprise software, we present a holistic overview of such metrics specifically designed for this type of system, since traditional metrics – e.g. object oriented ones – are not fully applicable in this case. The selected metric candidates from the literature review were mapped to 4 dominant design properties: size, complexity, coupling, and cohesion. Microservice-based systems (μSBSs) emerge as an agile and fine grained variant of SBSs. While the majority of identified metrics are also applicable to this specialization (with some limitations), the large number of services in combination with technological heterogeneity and decentralization of control significantly impacts automatic metric collection in such a system. Our research therefore suggests that specialized tool support is required to guarantee the practical applicability of the presented metrics to μSBSs.
Anforderungen an die Mensch-Maschine-Schnittstelle im Automobil auf dem Weg zum autonomen Fahren
(2017)
In den letzten Jahrzehnten haben immer mehr Fahrerassistenzsysteme Einzug in das Automobil gefunden und bereiten damit den Weg zu vollautonomen Fahrzeugen der Zukunft vor. So bieten bereits viele Hersteller Ausstattungsvarianten ihrer Fahrzeuge an, die für den Umstieg in die vollautonome Zukunft gewappnet sind. Um den Menschen mit auf den Weg zu nehmen, werden einige Anforderungen an die Mensch-Maschine-Schnittstelle (MMS) des Automobils gestellt. Für die teilautonomen Fahrzeuge der nächsten Generation gilt es, den Fahrerwechsel zwischen manuellem und autonomen Fahren für die Menschen bestmöglich zu gestalten. Die Arbeit wirft einen Blick auf ausgewählte Ansätze für zukünftige MMS-Systeme und bewertet diese anhand der Übergabezeiten zwischen Mensch und Maschine. Ein Wandel der MMS im Automobil wird empfohlen, um den Menschen mit den neuen Technologien vertraut zu machen.
Painting galleries typically provide a wealth of data composed of several data types. Those multivariate data are too complex for laymen like museum visitors to first, get an overview about all paintings and to look for specific categories. Finally, the goal is to guide the visitor to a specific painting that he wishes to have a more closer look on. In this paper we describe an interactive visualization tool that first provides such an overview and lets people experiment with the more than 41,000 paintings collected in the web gallery of art. To generate such an interactive tool, our technique is composed of different steps like data handling, algorithmic transformations, visualizations, interactions, and the human user working with the tool with the goal to detect insights in the provided data. We illustrate the usefulness of the visualization tool by applying it to such characteristic data and show how one can get from an overview about all paintings to specific paintings.
Clinical reading centers provide expertise for consistent, centralized analysis of medical data gathered in a distributed context. Accordingly, appropriate software solutions are required for the involved communication and data management processes. In this work, an analysis of general requirements and essential architectural and software design considerations for reading center information systems is provided. The identified patterns have been applied to the implementation of the reading center platform which is currently operated at the Center of Ophthalmology of the University Hospital of Tübingen.
Data Integration of heterogeneous data sources relies either on periodically transferring large amounts of data to a physical Data Warehouse or retrieving data from the sources on request only. The latter results in the creation of what is referred to as a virtual Data Warehouse, which is preferable when the use of the latest data is paramount. However, the downside is that it adds network traffic and suffers from performance degradation when the amount of data is high. In this paper, we propose the use of a readCheck validator to ensure the timeliness of the queried data and reduced data traffic. It is further shown that the readCheck allows transactions to update data in the data sources obeying full Atomicity, Consistency, Isolation, and Durability (ACID) properties.
Integrierte Schaltkreise (IC) sind ein integraler Bestandteil vieler Geräte wie zum Beispiel Smartphones, Computer oder Fernseher. Auf den Schaltkreisen werden immer mehr Funktionen integriert. Um die Arbeit auch zukünftig in gegebener Zeit bewältigen zu können, bedarf es daher einer Möglichkeit für die gleichzeitige Zusammenarbeit der Entwickler. Unter dem Arbeitstitel eCEDA (eCollaboration for Electronic Design Automation) wird ein Konzept für eine Webanwendung entwickelt, die die Echtzeitkollaboration von Entwicklern im Chipentwurf ermöglichen soll. Dieses Konzept sowie verschiedene Aspekte der Kollaboration werden in dieser Arbeit behandelt.
The increasing number of connected mobile devices such as fitness trackers and smartphones define new data for health insurances, enabling them to gain deeper insights into the health of their customers. These additional data sources plus the trend towards an interconnected health community, including doctors, hospitals and insurers, lead to challenges regarding data filtering, organization and dissemination. First, we analyze what kind of information is relevant for a digital health insurance. Second, functional and non-functional requirements for storing and managing health data in an interconnected environment are defined. Third, we propose a data architecture for a digitized health insurance, consisting of a data model and an application architecture.
Steady growing research material in a variety of databases, repositories and clouds make academic content more than ever hard to discover. Finding adequate material for the own research however is essential for every researcher. Based on recent developments in the field of artificial intelligence and the identified digital capabilities of future universities a change in the basic work of academic research is predicted. This study defines the idea of how artificial intelligence could simplifiy academic research at a digital university. Today's studies in the field of AI spectacle the true potential and its commanding impact on academic research.
Software engineering education is under constant pressure to provide students with industry-relevant knowledge and skills. Educators must address issues beyond exercises and theories that can be directly rehearsed in small settings. Industry training has similar requirements of relevance as companies seek to keep their workforce up to date with technological advances. Real-life software development often deals with large, software-intensive systems and is influenced by the complex effects of teamwork and distributed software development, which are hard to demonstrate in an educational environment. A way to experience such effects and to increase the relevance of software engineering education is to apply empirical studies in teaching. In this paper, we show how different types of empirical studies can be used for educational purposes in software engineering. We give examples illustrating how to utilize empirical studies, discuss challenges, and derive an initial guideline that supports teachers to include empirical studies in software engineering courses. Furthermore, we give examples that show how empirical studies contribute to high-quality learning outcomes, to student motivation, and to the awareness of the advantages of applying software engineering principles. Having awareness, experience, and understanding of the actions required, students are more likely to apply such principles under real-life constraints in their working life.
Context: Development of software intensive products and services increasingly occurs by continuously deploying product or service increments, such as new features and enhancements, to customers. Product and service developers must continuously find out what customers want by direct customer feedback and usage behaviour observation. Objective: This paper examines the preconditions for setting up an experimentation system for continuous customer experiments. It describes the RIGHT model for Continuous Experimentation (Rapid Iterative value creation Gained through High-frequency Testing), illustrating the building blocks required for such a system. Method: An initial model for continuous experimentation is analytically derived from prior work. The model is matched against empirical case study findings from two startup companies and further developed. Results: Building blocks for a continuous experimentation system and infrastructure are presented. Conclusions: A suitable experimentation system requires at least the ability to release minimum viable products or features with suitable instrumentation, design and manage experiment plans, link experiment results with a product roadmap, and manage a flexible business strategy. The main challenges are proper, rapid design of experiments, advanced instrumentation of software to collect, analyse, and store relevant data, and the integration of experiment results in both the product development cycle and the software development process.
Thematic issue on human-centred ambient intelligence: cognitive approaches, reasoning and learning
(2017)
This editorial presents advances on human-centred Ambient Intelligence applications which take into account cognitive issues when modelling users (i.e. stress, attention disorders), and learn users’ activities/preferences and adapt to them (i.e. at home, driving a car). These papers also show AmI applications in health and education, which make them even more valuable for the general society.
Ein stark erforschtes Gebiet der Computer Vision ist die Detektion von markanten Punkten des Gesichtszuges (englisch: facial feature detection), wie der Mundwinkel oder des Kinns. Daher lassen sich eine Vielzahl von veröffentlichten Verfahren finden, die sich jedoch teils deutlich hinsichtlich der Detektionsgenauigkeit, Robustheit und Geschwindigkeit unterscheiden. So sind viele Verfahren nur bedingt echtzeitfähig oder liefern nur mit hochaufgelösten Bildquellen ein zufriedenstellendes Ergebnis. In den letzten Jahren wurden daher Verfahren entwickelt, die versuchen, diese Problematiken zu lösen. In dieser Arbeit erfolgt eine Betrachtung dreier dieser State-of-the-Art Verfahren: Constrained Local Neural Fields (CLNF), Discriminative Response Map Fitting (DRMF) und Structured Output SVM (SO SVM), sowie deren Implementierungen. Dazu erfolgt ein empirischer Vergleich hinsichtlich der Detektionsgenauigkeit.
Mittlerweile ist der Einsatz von technischen Hilfsmitteln zu Analysezwecken im Sport fester Bestandteil im Trainingsalltag von Trainern und Athleten. In nahezu jeder Sportart werden Videoaufzeichnungen genutzt, um die Bewegungsausführung zu dokumentieren und zu analysieren. Allerdings reichen Aufnahmen von einem statischen Standort oftmals nicht mehr aus. An dieser Stelle kann Virtual Reality (VR) eine Lösung dieses Problems bieten. Durch VR kann der aufgezeichneten Szene eine weitere Ebene hinzugefügt und die Bewegungsabläufe neu und detaillierter bewertet werden. Um Bewegungen in einer virtuellen Umgebung abzubilden, müssen diese mittels Motion Capturing (MoCap) aufgezeichnet werden. Ziel dieser Arbeit ist es, herauszufinden, ob das MoCap System Perception Neuron in der Lage ist, Bewegungen in hoher Geschwindigkeit zu erfassen.
Sleep quality and in general, behavior in bed can be detected using a sleep state analysis. These results can help a subject to regulate sleep and recognize different sleeping disorders. In this work, a sensor grid for pressure and movement detection supporting sleep phase analysis is proposed. In comparison to the leading standard measuring system, which is Polysomnography (PSG), the system proposed in this project is a non invasive sleep monitoring device. For continuous analysis or home use, the PSG or wearable actigraphy devices tends to be uncomfortable. Besides this fact, they are also very expensive. The system represented in this work classifies respiration and body movement with only one type of sensor and also in a non invasive way. The sensor used is a pressure sensor. This sensor is low cost and can be used for commercial proposes. The system was tested by carrying out an experiment that recorded the sleep process of a subject. These recordings showed the potential for classification of breathing rate and body movements. Although previous researches show the use of pressure sensors in recognizing posture and breathing, they have been mostly used by positioning the sensors between the mattress and bedsheet. This project however, shows an innovative way to position the sensors under the mattress.
To analyze the humans’ sleep it is necessary as to identify the sleep stages, occurring during the sleep, their durations and sleep cycles. The gold standard procedure for this approach is polysomnography (PSG), which classify the sleep stages based on Rechtschaffen and Kales (R-K) method. This method aside the advantages as high accuracy has however some disadvantages, among others time-consuming and uncomfortable for the patient procedure. Therefore, the development of further methods for the sleep classification in addition to PSG is a promising topic for the investigation and this work has as its aim the presentation of possible ways and goals for this development.
Asymmetric read/write storage technologies such as Flash are becoming
a dominant trend in modern database systems. They introduce
hardware characteristics and properties which are fundamentally
different from those of traditional storage technologies such
as HDDs.
Multi-Versioning Database Management Systems (MV-DBMSs)
and Log-based Storage Managers (LbSMs) are concepts that can
effectively address the properties of these storage technologies but
are designed for the characteristics of legacy hardware. A critical
component of MV-DBMSs is the invalidation model: commonly,
transactional timestamps are assigned to the old and the new version,
resulting in two independent (physical) update operations.
Those entail multiple random writes as well as in-place updates,
sub-optimal for new storage technologies both in terms of performance
and endurance. Traditional page-append LbSM approaches
alleviate random writes and immediate in-place updates, hence reducing
the negative impact of Flash read/write asymmetry. Nevertheless,
they entail significant mapping overhead, leading to write
amplification.
In this work we present an approach called Snapshot Isolation
Append Storage Chains (SIAS-Chains) that employs a combination
of multi-versioning, append storage management in tuple granularity
and novel singly-linked (chain-like) version organization.
SIAS-Chains features: simplified buffer management, multi-version
indexing and introduces read/write optimizations to data placement
on modern storage media. SIAS-Chains algorithmically avoids
small in-place updates, caused by in-place invalidation and converts
them into appends. Every modification operation is executed
as an append and recently inserted tuple versions are co-located.
Software startups often make assumptions about the problems and customers they are addressing as well as the market and the solutions they are developing. Testing the right assumptions early is a means to mitigate risks. Approaches such as Lean Startup foster this kind of testing by applying experimentation as part of a constant build-measure-learn feedback loop. The existing research on how software startups approach experimentation is very limited. In this study, we focus on understanding how software startups approach experimentation and identify challenges and advantages with respect to conducting experiments. To achieve this, we conducted a qualitative interview study. The initial results show that startups often spent a disproportionate amount of time focusing on creating solutions without testing critical assumptions. Main reasons are the lack of awareness, that these assumptions can be tested early and a lack of knowledge and support on how to identify, prioritize and test these assumptions. However, startups understand the need for testing risky assumptions and are open to conducting experiments.