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In einigen Bereichen der Informatiklehre ist es möglich, die persönlichen Erfahrungen der Studierenden im Umgang mit Informationstechnik aufzugreifen und vor dem Hintergrund theoretischer Konzepte aus der Literatur gemeinsam mit ihnen zu reflektieren. Das hier vorgestellte Lehrkonzept des Reflexionsdialogs erstreckt sich über drei Seminartermine und vorbereitende Selbstlernphasen. Unterstützt wird das Konzept durch DialogueMaps, eine Software zur Visualisierung komplexer Sachverhalte und zur Unterstützung interaktiver Dialoge. Dieser Beitrag beschreibt die Hintergründe des Lehrkonzeptes, das Lehrkonzept selbst sowie die inhaltliche Ausgestaltung im Rahmen eines Mastermoduls „Computergestützte Kooperation“.
Due to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.
We introduce hierarchical kFOIL as a simple extension of the multitask kFOIL learning algorithm. The algorithm first learns a core logic representation common to all tasks, and then refines it by specialization on a per-task basis. The approach can be easily generalized to a deeper hierarchy of tasks. A task clustering algorithm is also proposed in order to automatically generate the task hierarchy. The approach is validated on problems of drug-resistance mutation prediction and protein structural classification. Experimental results show the advantage of the hierarchical version over both single and multi task alternatives and its potential usefulness in providing explanatory features for the domain. Task clustering allows to further improve performance when a deeper hierarchy is considered.
In recent years, named entity linking (NEL) tools were primarily developed in terms of a general approach, whereas today numerous tools are focusing on specific domains such as e.g. the mapping of persons and organizations only, or the annotation of locations or events in microposts. However, the available benchmark datasets necessary for the evaluation of NEL tools do not reflect this focalizing trend. We have analyzed the evaluation process applied in the NEL benchmarking framework GERBIL [in: Proceedings of the 24th International Conference on World Wide Web (WWW’15), International World Wide Web Conferences Steering Committee, Republic and Canton of Geneva, Switzerland, 2015, pp. 1133–1143, Semantic Web 9(5) (2018), 605–625] and all its benchmark datasets. Based on these insights we have extended the GERBIL framework to enable a more fine grained evaluation and in depth analysis of the available benchmark datasets with respect to different emphases. This paper presents the implementation of an adaptive filter for arbitrary entities and customized benchmark creation as well as the automated determination of typical NEL benchmark dataset properties, such as the extent of content-related ambiguity and diversity. These properties are integrated on different levels, which also enables to tailor customized new datasets out of the existing ones by remixing documents based on desired emphases. Besides a new system library to enrich provided NIF [in: International Semantic Web Conference (ISWC’13), Lecture Notes in Computer Science, Vol. 8219, Springer, Berlin, Heidelberg, 2013, pp. 98–113] datasets with statistical information, best practices for dataset remixing are presented, and an in depth analysis of the performance of entity linking systems on special focus datasets is presented.
We study a novel representation of semiautomata, which is motivated by the method of trace-assertion specifications of software modules. Each state of the semiautomaton is represented by an arbitrary word leading to that state, the canonical word. The transitions of the semiautomaton give rise to a right congruence, the state-equivalence, on the set of input words of the semiautomaton: two words are state-equivalent if and only if they lead to the same state. We present a simple algorithm for finding a set of generators for state-equivalence. Directly from this set of generators, we construct a confluent prefix-rewriting system which permits us to transform any word to its canonical representative. In general, the rewriting system may allow infinite derivations. To address this issue, we impose the condition of prefix-continuity on the set of canonical words. A set is prefix-continuous if, whenever a word w and a prefix u of w axe in the set, then all the prefixes of w longer than u are also in the set. Prefix-continuous sets include prefix-free and prefix-closed sets as special cases. We prove that the rewriting system is Noetherian if and only if the set of canonical words is prefix-continuous. Furthermore, if the set of canonical words is prefix- continuous, then the set of rewriting rules is irredundant. We show that each prefix-continuous canonical set corresponds to a spanning forest of the semiautomaton
THIS INSTALLMENT OF Research for Practice provides curated reading guides to technology for underserved communities and to new developments in personal fabrication. First, Tawanna Dillahunt describes design considerations and technology for underserved and impoverished communities. Designing for the more than 1.6 billion impoverished individuals worldwide requires special consideration of community needs, constraints, and context. Her selections span protocols for poor-quality communication networks, community-driven content generation, and resource and public service discovery. Second, Stefanie Mueller and Patrick Baudisch provide an overview of recent advances in personal fabrication (for example, 3D printers).
In this paper we present the design and implementation of the Migol brokering framework. Migol is a Grid middleware, which addresses the fault-tolerance of long-running and compute-intensive applications. The framework supports e. g. the automatic and transparent recovery respectively the migration of applications. Another core feature of Migol is the discovery, selection, and allocation of resources using advance reservation. Grid broker systems can significantly benefit from advance reservation. With advance reservation brokers and users can obtain execution guarantees from local resource management systems (LRM) without requiring detailed knowledge of current and future workloads or of the resource owner's policies. Migol's Advance Reservation Service (ARS) provides an adapter layer for reservation capabilities of different LRMs, which is currently not provided by existing Grid middleware platforms. Further, we propose a shortest expected delay (SED) strategy for scheduling of advance reservations within the Job Broker Service. SED needs information about the earliest start time of an application. This is currently not supported by LRMs. We added this feature for PBSPro. Migol depends on Globus and its security infrastructure. Our performance experiments show the substantial overhead of this serviceoriented approach.
We study the concept of reversibility in connection with parallel communicating systems of finite automata (PCFA in short). We define the notion of reversibility in the case of PCFA (also covering the non-deterministic case) and discuss the relationship of the reversibility of the systems and the reversibility of its components. We show that a system can be reversible with non-reversible components, and the other way around, the reversibility of the components does not necessarily imply the reversibility of the system as a whole. We also investigate the computational power of deterministic centralized reversible PCFA. We show that these very simple types of PCFA (returning or non-returning) can recognize regular languages which cannot be accepted by reversible (deterministic) finite automata, and that they can even accept languages that are not context-free. We also separate the deterministic and non-deterministic variants in the case of systems with non-returning communication. We show that there are languages accepted by non-deterministic centralized PCFA, which cannot be recognized by any deterministic variant of the same type.
Robust ensemble learning
(2000)
Pervasive educational games have the potential to transfer learning content to real-life experiences beyond lecture rooms, through realizing field trips in an augmented or virtual manner. This article introduces the pervasive educational game "RouteMe" that brings the rather abstract topic of routing in ad hoc networks to real-world environments. The game is designed for university-level courses and supports these courses in a motivating manner to deepen the learning experience. Students slip into the role of either routing nodes or applications with routing demands. On three consecutive levels of difficulty, they get introduced with the game concept, learn the basic routing mechanisms and become aware of the general limitations and functionality of routing nodes. This paper presents the pedagogical and technical game concept as well as findings from an evaluation in a university setting.
Automated storage and retrieval systems are principal components of modern production and warehouse facilities. In particular, automated guided vehicles nowadays substitute human-operated pallet trucks in transporting production materials between storage locations and assembly stations. While low-level control systems take care of navigating such driverless vehicles along programmed routes and avoid collisions even under unforeseen circumstances, in the common case of multiple vehicles sharing the same operation area, the problem remains how to set up routes such that a collection of transport tasks is accomplished most effectively. We address this prevalent problem in the context of car assembly at Mercedes-Benz Ludwigsfelde GmbH, a large-scale producer of commercial vehicles, where routes for automated guided vehicles used in the production process have traditionally been hand-coded by human engineers. Such adhoc methods may suffice as long as a running production process remains in place, while any change in the factory layout or production targets necessitates tedious manual reconfiguration, not to mention the missing portability between different production plants. Unlike this, we propose a declarative approach based on Answer Set Programming to optimize the routes taken by automated guided vehicles for accomplishing transport tasks. The advantages include a transparent and executable problem formalization, provable optimality of routes relative to objective criteria, as well as elaboration tolerance towards particular factory layouts and production targets. Moreover, we demonstrate that our approach is efficient enough to deal with the transport tasks evolving in realistic production processes at the car factory of Mercedes-Benz Ludwigsfelde GmbH.
Die vorliegende Arbeit erörtert die Frage, wie Nachwuchs für das Informatikstudium nachhaltig gesichert werden kann. Dazu werden Befragungen unter Schülerinnen und Schülern (13-16 Jahre), sowie aktuelle Informatik-Schnupperangebote für Schülerinnen und Schüler an deutschsprachigen Hochschulen vorgestellt und untersucht. Diese Gegenüberstellung zeigt deutlich, dass die Angebote nur bedingt eine breite Zielgruppe ansprechen und dass weitere Formate und Inhalte notwendig sind, um Schülerinnen und Schüler frühzeitig und in voller Breite zu erreichen und für das Informatikstudium zu begeistern. Daraus wird abgeleitet, dass Missverständnisse und Probleme mit der Informatik im Schulkontext aufgegriffen werden müssen. Das vorgestellte Programm Schulbotschafter Informatik stellt einen möglichen Weg dar, um dies zu erreichen und übliche Schnupperangebote zu ergänzen.
A major part of the scientific experiments that are carried out today requires thorough computational support. While database and algorithm providers face the problem of bundling resources to create and sustain powerful computation nodes, the users have to deal with combining sets of (remote) services into specific data analysis and transformation processes. Today’s attention to “big data” amplifies the issues of size, heterogeneity, and process-level diversity/integration. In the last decade, especially workflow-based approaches to deal with these processes have enjoyed great popularity. This book concerns a particularly agile and model-driven approach to manage scientific workflows that is based on the XMDD paradigm. In this chapter we explain the scope and purpose of the book, briefly describe the concepts and technologies of the XMDD paradigm, explain the principal differences to related approaches, and outline the structure of the book.
fundamental challenge for product-lifecycle management in collaborative value networks is to utilize the vast amount of product information available from heterogeneous sources in order to improve business analytics, decision support, and processes. This becomes even more challenging if those sources are distributed across multiple organizations. Federations of semantic information services, combining service-orientation and semantic technologies, provide a promising solution for this problem. However, without proper measures to establish information security, companies will be reluctant to join an information federation, which could lead to serious adoption barriers.
Following the design science paradigm, this paper presents general objectives and a process for designing a secure federation of semantic information services. Furthermore, new as well as established security measures are discussed. Here, our contributions include an access-control enforcement system for semantic information services and a process for modeling access-control policies across organizations. In addition, a comprehensive security architecture is presented. An implementation of the architecture in the context of an application scenario and several performance experiments demonstrate the practical viability of our approach.
Time-series data from multicomponent systems capture the dynamics of the ongoing processes and reflect the interactions between the components. The progression of processes in such systems usually involves check-points and events at which the relationships between the components are altered in response to stimuli. Detecting these events together with the implicated components can help understand the temporal aspects of complex biological systems. Here we propose a regularized regression-based approach for identifying breakpoints and corresponding segments from multivariate time-series data. In combination with techniques from clustering, the approach also allows estimating the significance of the determined breakpoints as well as the key components implicated in the emergence of the breakpoints. Comparative analysis with the existing alternatives demonstrates the power of the approach to identify biologically meaningful breakpoints in diverse time-resolved transcriptomics data sets from the yeast Saccharomyces cerevisiae and the diatom Thalassiosira pseudonana.
The Domain Name System belongs to the core services of the Internet infrastructure. Hence, DNS availability and performance is essential for the operation of the Internet and replication as well as load balancing are used for the root and top level name servers.
This paper proposes an architecture for credit based server load balancing (SLB) for DNS. Compared to traditional load balancing algorithms like round robin or least connection, the benefit of credit based SLB is that the load balancer can adapt more easily to heterogeneous load requests and back end server capacities. The challenge of this approach is the definition of a suited credit metric. While this was done before for TCP based services like HTTP, the problem was not solved for UDP based services like DNS.
In the following an approach is presented to define credits also for UDP based services. This UDP/DNS approach is implemented within the credit based SLB implementation salbnet. The presented measurements confirm the benefit of the self-adapting credit based SLB approach. In our experiments, the mean (first) response time dropped significantly compared to weighted round robin (WRR) (from over 4 ms to about 0.6 ms for dynamic pressure relieve (DPR)).
Existing telecommunication networks and classical roles of operators are subject to fundamental change. Many network operators are currently seeking for new sources to generate revenue by exposing network capabilities to 3rd party service providers. At the same time we can observe that services on the World Wide Web (WWW) are becoming mature in terms of the definition of APIs that are offered towards other services. The combinations of those services are commonly referred to as Web 2.0 mash-ups. Rapid service design and creation becomes therefore important to meet the requirements in a changing technology and competitive market environment. This report describes our approach to include Next Generation Networks (NGN)-based telecommunications application enabler into complex services by defining a service broker that mediates between 3rd party applications and NGN service enablers. It provides policy-driven orchestration mechanisms for service enablers, a service authorization functionality, and a service discovery interface for Service Creation Environments. The work has been implemented as part of the Open SOA Telco Playground testbed at Fraunhofer FOKUS.
Significant inferences
(2000)
In this article, we present our experience with over a decade of strict simplicity orientation in the development and evolution of plug-ins. The point of our approach is to enable our graphical modeling framework jABC to capture plug-in development in a domain-specific setting. The typically quite tedious and technical plug-in development is shifted this way from a programming task to the modeling level, where it can be mastered also by application experts without programming expertise. We show how the classical plug-in development profits from a systematic domain-specific API design and how the level of abstraction achieved this way can be further enhanced by defining adequate building blocks for high-level plug-in modeling. As the resulting plug-in models can be compiled and deployed automatically, our approach decomposes plug-in development into three phases where only the realization phase requires plug-in-specific effort. By using our modeling framework jABC, this effort boils down to graphical, tool-supported process modeling. Furthermore, we support the automatic completion of process sketches for executability. All this will be illustrated along the most recent plug-in-based evolution of the jABC framework, which witnessed quite some bootstrapping effects.
Durch den bundesweiten Rückgang der Schülerzahlen und einer steigenden Zahl von Bildungsangeboten geraten Universitäten und Hochschulen in den nächsten Jahren weiter in eine Wettbewerbssituation, weshalb sie effektive Marketingmaßnahmen entwickeln müssen, um Schülerinnen und Schüler möglichst frühzeitig für das jeweilige Angebot (z. B. Informatik- und informatiknahe Studiengänge) zu interessieren. Ein Medium, über das sich potenziell sehr viele Jugendliche erreichen lassen, sind dabei soziale Netzwerke. Diese Arbeit präsentiert Ergebnisse einer Studie unter Informatikstudienanfängerinnen und -anfängern zum Nutzungsverhalten sozialer Netzwerke und zieht Schlussfolgerungen zu deren Eignung als Werbe- und Informationskanal für die Zielgruppe der Informatikinteressierten.
Today, InfiniBand is an evolving high speed interconnect technology to build high performance computing clusters, that achieve top 10 rankings in the current top 500 of the worldwide fastest supercomputers. Network interfaces (called host channel adapters) provide transport layer services over connections and datagrams in reliable or unreliable manner. Additionally, InfiniBand supports remote direct memory access (RDMA) primitives that allow for one- sided communication. Using server load balancing together with a high performance cluster makes it possible to build a fast, scalable, and reliable service infrastructure. We have designed and implemented a scalable load balancer for InfiniBand clusters called SLIBNet. Our investigations show that the InfiniBand architecture offers features which perfectly support load balancing. We want to thank the Megware Computer GmbH for providing us an InfiniBand switch to realize a server load balancing testbed.
In this paper, we consider the computational power of a new variant of networks of splicing processors in which each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined (negative, neutral, positive), the polarization of data is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that networks of polarized splicing processors (NPSP) of size 2 are computationally complete, which immediately settles the question of designing computationally complete NPSPs of minimal size. With two more nodes we can simulate every nondeterministic Turing machine without increasing the time complexity. Particularly, we prove that NPSP of size 4 can accept all languages in NP in polynomial time. Furthermore, another computational model that is universal, namely the 2-tag system, can be simulated by NPSP of size 3 preserving the time complexity. All these results can be obtained with NPSPs with valuations in the set as well. We finally show that Turing machines can simulate a variant of NPSPs and discuss the time complexity of this simulation.
In this paper, an asynchronous design for soft error detection and correction in combinational and sequential circuits is presented. The proposed architecture is called Asynchronous Full Error Detection and Correction (AFEDC). A custom design flow with integrated commercial EDA tools generates the AFEDC using the asynchronous bundled-data design style. The AFEDC relies on an Error Detection Circuit (EDC) for protecting the combinational logic and fault-tolerant latches for protecting the sequential logic. The EDC can be implemented using different detection methods. For this work, two boundary variants are considered, the Full Duplication with Comparison (FDC) and the Partial Duplication with Parity Prediction (PDPP). The AFEDC architecture can handle single events and timing faults of arbitrarily long duration as well as the synchronous FEDC, but additionally can address known metastability issues of the FEDC and other similar synchronous architectures and provide a more practical solution for handling the error recovery process. Two case studies are developed, a carry look-ahead adder and a pipelined non-restoring array divider. Results show that the AFEDC provides equivalent fault coverage when compared to the FEDC while reducing area, ranging from 9.6% to 17.6%, and increasing energy efficiency, which can be up to 6.5%.
Software development plan
(1996)
The intensity of cosmic radiation may differ over five orders of magnitude within a few hours or days during the Solar Particle Events (SPEs), thus increasing for several orders of magnitude the probability of Single Event Upsets (SEUs) in space-borne electronic systems. Therefore, it is vital to enable the early detection of the SEU rate changes in order to ensure timely activation of dynamic radiation hardening measures. In this paper, an embedded approach for the prediction of SPEs and SRAM SEU rate is presented. The proposed solution combines the real-time SRAM-based SEU monitor, the offline-trained machine learning model and online learning algorithm for the prediction. With respect to the state-of-the-art, our solution brings the following benefits: (1) Use of existing on-chip data storage SRAM as a particle detector, thus minimizing the hardware and power overhead, (2) Prediction of SRAM SEU rate one hour in advance, with the fine-grained hourly tracking of SEU variations during SPEs as well as under normal conditions, (3) Online optimization of the prediction model for enhancing the prediction accuracy during run-time, (4) Negligible cost of hardware accelerator design for the implementation of selected machine learning model and online learning algorithm. The proposed design is intended for a highly dependable and self-adaptive multiprocessing system employed in space applications, allowing to trigger the radiation mitigation mechanisms before the onset of high radiation levels.
Data recorded in electroencephalogram (EEG)-based brain-computer interface experiments is generally very noisy, non-stationary, and contaminated with artifacts that can deteriorate discrimination/classification methods. In this paper, we extend the common spatial pattern (CSP) algorithm with the aim to alleviate these adverse effects. In particular, we suggest an extension of CSP to the state space, which utilizes the method of time delay embedding. As we will show, this allows for individually tuned frequency filters at each electrode position and, thus, yields an improved and more robust machine learning procedure. The advantages of the proposed method over the original CSP method are verified in terms of an improved information transfer rate (bits per trial) on a set of EEG-recordings from experiments of imagined limb movements
SPAM ist in den letzten Jahren zur großten Bedrohung der E-Mail-Kommunikation herangewachsen - jedoch nicht nur auf diesen Kommunikationsweg beschrankt. Mit steigender Anzahl von VoIP-Anschlüssen werden auch hier die teilnehmenden Benutzer mit SPAM-Anrufen (SPIT) konfrontiert werden. Neben derzeit diskutierten juristischen Maßnahmen müssen auch technische Abwehrmaßnahmen geschaffen werden, welche SPAM erkennen und vermeiden können. Dieser Beitrag stellt zwei Erweiterungen für das VoIP-Protokoll SIP vor, welche es erstens den Providern ermöglichen, SPIT-Einschätzungen über den Anrufer zum angerufenen Benutzer zu übermitteln und zweitens den Angerufenen die Möglichkeit geben, mit einer Kostenanforderung auf potentielle SPIT-Anrufe zu reagieren.
Spotlocator is a game wherein people have to guess the spots of where photos were taken. The photos of a defined area for each game are from panoramio.com. They are published at http://spotlocator. drupalgardens.com with an ID. Everyone can guess the photo spots by sending a special tweet via Twitter that contains the hashtag #spotlocator, the guessed coordinates and the ID of the photo. An evaluation is published for all tweets. The players are informed about the distance to the real photo spots and the positions are shown on a map.
This paper surveys the field of nonphotorealistic rendering (NPR), focusing on techniques for transforming 2D input (images and video) into artistically stylized renderings. We first present a taxonomy of the 2D NPR algorithms developed over the past two decades, structured according to the design characteristics and behavior of each technique. We then describe a chronology of development from the semiautomatic paint systems of the early nineties, through to the automated painterly rendering systems of the late nineties driven by image gradient analysis. Two complementary trends in the NPR literature are then addressed, with reference to our taxonomy. First, the fusion of higher level computer vision and NPR, illustrating the trends toward scene analysis to drive artistic abstraction and diversity of style. Second, the evolution of local processing approaches toward edge-aware filtering for real-time stylization of images and video. The survey then concludes with a discussion of open challenges for 2D NPR identified in recent NPR symposia, including topics such as user and aesthetic evaluation.
The standard assumption of identically distributed training and test data is violated when the test data are generated in response to the presence of a predictive model. This becomes apparent, for example, in the context of email spam filtering. Here, email service providers employ spam filters, and spam senders engineer campaign templates to achieve a high rate of successful deliveries despite the filters. We model the interaction between the learner and the data generator as a static game in which the cost functions of the learner and the data generator are not necessarily antagonistic. We identify conditions under which this prediction game has a unique Nash equilibrium and derive algorithms that find the equilibrial prediction model. We derive two instances, the Nash logistic regression and the Nash support vector machine, and empirically explore their properties in a case study on email spam filtering.
One of the goals of artificial intelligence is to develop agents that learn and act in complex environments. Realistic environments typically feature a variable number of objects, relations amongst them, and non-deterministic transition behavior. While standard probabilistic sequence models provide efficient inference and learning techniques for sequential data, they typically cannot fully capture the relational complexity. On the other hand, statistical relational learning techniques are often too inefficient to cope with complex sequential data. In this paper, we introduce a simple model that occupies an intermediate position in this expressiveness/efficiency trade-off. It is based on CP-logic (Causal Probabilistic Logic), an expressive probabilistic logic for modeling causality. However, by specializing CP-logic to represent a probability distribution over sequences of relational state descriptions and employing a Markov assumption, inference and learning become more tractable and effective. Specifically, we show how to solve part of the inference and learning problems directly at the first-order level, while transforming the remaining part into the problem of computing all satisfying assignments for a Boolean formula in a binary decision diagram. We experimentally validate that the resulting technique is able to handle probabilistic relational domains with a substantial number of objects and relations.
Die Setzung strategischer Ziele sowie die Zuordnung und Umsetzung dazugehörender Maßnahmen sind ein wesentliches Element, um die Innovationsfähigkeit von Organisationen zu erhalten. In den vergangenen Jahren ist auch an Hochschulen die Strategiebildung deutlich vorangetrieben worden. Dies betrifft verschiedene Handlungsfelder, und es werden verschiedene Ansätze verfolgt. Der vorliegende Beitrag greift am Beispiel der Universität Potsdam drei in den vergangenen Jahren adressierte Strategiebereiche heraus: IT, E-Learning und Forschungsdaten. Die damit verbundenen Prozesse waren in unterschiedlichem Maß von Partizipation geprägt. Die gesammelten Erfahrungen werden reflektiert, und es werden Empfehlungen für Strategieentwicklungsprozesse abgeleitet.
Social networks are currently at the forefront of tools that
lend to Personal Learning Environments (PLEs). This study aimed to
observe how students perceived PLEs, what they believed were the
integral components of social presence when using Facebook as part
of a PLE, and to describe student’s preferences for types of interactions
when using Facebook as part of their PLE. This study used mixed
methods to analyze the perceptions of graduate and undergraduate
students on the use of social networks, more specifically Facebook as a
learning tool. Fifty surveys were returned representing a 65 % response
rate. Survey questions included both closed and open-ended questions.
Findings suggested that even though students rated themselves relatively
well in having requisite technology skills, and 94 % of students used
Facebook primarily for social use, they were hesitant to migrate these
skills to academic use because of concerns of privacy, believing that
other platforms could fulfil the same purpose, and by not seeing the
validity to use Facebook in establishing social presence. What lies
at odds with these beliefs is that when asked to identify strategies in
Facebook that enabled social presence to occur in academic work, the
majority of students identified strategies in five categories that lead to
social presence establishment on Facebook during their coursework.
Der vorliegende Beitrag beschäftigt sich mit der Frage, wie der eLearning-Support in großen Institutionen effizient gestaltet werden kann. Vorgestellt wird ein experimentelles Beratungsprojekt, das Lehrende bei der Gestaltung von eLearning-Maßnahmen mithilfe der Lernplattform ILIAS1 unterstützt. Neben der Zielsetzung des Projekts werden dessen Aufbau und erste Praxiserfahrungen erörtert. Außerdem werden Potenziale des Beratungsformats, die insbesondere mit der individuellen Vor-Ort-Beratung der Lehrenden durch hochschuldidaktisch geschulte Studierende einhergehen, erläutert. Abschließend werden Grenzen und Weiterentwicklungsperspektiven des Projekts dargestellt. Am Beispiel der ILIAS-Beratung soll gezeigt werden, dass es sich einer nachhaltigen Organisationsentwicklung als zuträglich erweist, Kooperationen erschiedenartiger Organisationseinheiten zu fördern und die entstehenden Synergieeffekte zu nutzen.
Es wird ein umfassendes Mentoring Konzept im Studiengang Informatik an der RWTH Aachen vorgestellt, das den Übergang von der Schule zur Universität unterstützt und gleichzeitig beim Auftreten von Schwierigkeiten im Verlauf des Studiums effiziente und kompetente Beratung bietet. Das Programm erreicht durchgängig hohe Akzeptanzwerte bei den Studierenden trotz verpflichtender Teilnahme im ersten Semester. Die Wirksamkeit des Programms ist durch die zahlreichen einflussgebenden Variablen zwar rein quantitativ kaum messbar, die Möglichkeit auf organisatorische und fachliche Probleme eines Jahrgangs reagieren zu können sowie einen Einblick auf die Gründe für einen Studienabbruch zu bekommen, bestätigt aber die Notwendigkeit der Maßnahme.
Supervised machine learning to assess methane emissions of a dairy building with natural ventilation
(2020)
A reliable quantification of greenhouse gas emissions is a basis for the development of adequate mitigation measures. Protocols for emission measurements and data analysis approaches to extrapolate to accurate annual emission values are a substantial prerequisite in this context. We systematically analyzed the benefit of supervised machine learning methods to project methane emissions from a naturally ventilated cattle building with a concrete solid floor and manure scraper located in Northern Germany. We took into account approximately 40 weeks of hourly emission measurements and compared model predictions using eight regression approaches, 27 different sampling scenarios and four measures of model accuracy. Data normalization was applied based on median and quartile range. A correlation analysis was performed to evaluate the influence of individual features. This indicated only a very weak linear relation between the methane emission and features that are typically used to predict methane emission values of naturally ventilated barns. It further highlighted the added value of including day-time and squared ambient temperature as features. The error of the predicted emission values was in general below 10%. The results from Gaussian processes, ordinary multilinear regression and neural networks were least robust. More robust results were obtained with multilinear regression with regularization, support vector machines and particularly the ensemble methods gradient boosting and random forest. The latter had the added value to be rather insensitive against the normalization procedure. In the case of multilinear regression, also the removal of not significantly linearly related variables (i.e., keeping only the day-time component) led to robust modeling results. We concluded that measurement protocols with 7 days and six measurement periods can be considered sufficient to model methane emissions from the dairy barn with solid floor with manure scraper, particularly when periods are distributed over the year with a preference for transition periods. Features should be normalized according to median and quartile range and must be carefully selected depending on the modeling approach.
The growing impact of globalisation and the development of
a ‘knowledge society’ have led many to argue that 21st century skills are
essential for life in twenty-first century society and that ICT is central
to their development. This paper describes how 21st century skills, in
particular digital literacy, critical thinking, creativity, communication
and collaboration skills, have been conceptualised and embedded in the
resources developed for teachers in iTEC, a four-year, European project.
The effectiveness of this approach is considered in light of the data
collected through the evaluation of the pilots, which considers both the
potential benefits of using technology to support the development of
21st century skills, but also the challenges of doing so. Finally, the paper
discusses the learning support systems required in order to transform
pedagogies and embed 21st century skills. It is argued that support is
required in standards and assessment; curriculum and instruction; professional
development; and learning environments.
Multi-sided platforms (MSP) strongly affect markets and play a crucial part within the digital and networked economy. Although empirical evidence indicates their occurrence in many industries, research has not investigated the game-changing impact of MSP on traditional markets to a sufficient extent. More specifically, we have little knowledge of how MSP affect value creation and customer interaction in entire markets, exploiting the potential of digital technologies to offer new value propositions. Our paper addresses this research gap and provides an initial systematic approach to analyze the impact of MSP on the insurance industry. For this purpose, we analyze the state of the art in research and practice in order to develop a reference model of the value network for the insurance industry. On this basis, we conduct a case-study analysis to discover and analyze roles which are occupied or even newly created by MSP. As a final step, we categorize MSP with regard to their relation to traditional insurance companies, resulting in a classification scheme with four MSP standard types: Competition, Coordination, Cooperation, Collaboration.
Dieser Beitrag diskutiert die Konzeption eines Software-Projektpraktikums im Bereich E-Learning, welches Lehramts- und Fachstudierenden der Informatik ermöglicht, voneinander zu profitieren und praxisrelevante Ergebnisse generiert. Vorbereitungen, Organisation und Durchführung werden vorgestellt und diskutiert. Den Abschluss bildet ein Ausblick auf die Fortführung des Konzepts und den Ausbau des Forschungsgebietes.
We introduce formal proof systems based on tableau methods for analyzing computations in Answer Set Programming (ASP). Our approach furnishes fine-grained instruments for characterizing operations as well as strategies of ASP solvers. The granularity is detailed enough to capture a variety of propagation and choice methods of algorithms used for ASP solving, also incorporating SAT-based and conflict-driven learning approaches to some extent. This provides us with a uniform setting for identifying and comparing fundamental properties of ASP solving approaches. In particular, we investigate their proof complexities and show that the run-times of best-case computations can vary exponentially between different existing ASP solvers. Apart from providing a framework for comparing ASP solving approaches, our characterizations also contribute to their understanding by pinning down the constitutive atomic operations. Furthermore, our framework is flexible enough to integrate new inference patterns, and so to study their relation to existing ones. To this end, we generalize our approach and provide an extensible basis aiming at a modular incorporation of additional language constructs. This is exemplified by augmenting our basic tableau methods with cardinality constraints and disjunctions.
Regardless of what is intended by government curriculum
specifications and advised by educational experts, the competencies
taught and learned in and out of classrooms can vary considerably.
In this paper, we discuss in particular how we can investigate the
perceptions that individual teachers have of competencies in ICT,
and how these and other factors may influence students’ learning. We
report case study research which identifies contradictions within the
teaching of ICT competencies as an activity system, highlighting issues
concerning the object of the curriculum, the roles of the participants and
the school cultures. In a particular case, contradictions in the learning
objectives between higher order skills and the use of application tools
have been resolved by a change in the teacher’s perceptions which
have not led to changes in other aspects of the activity system. We look
forward to further investigation of the effects of these contradictions in
other case studies and on forthcoming curriculum change.
Teaching Data Management
(2015)
Data management is a central topic in computer science as
well as in computer science education. Within the last years, this topic is
changing tremendously, as its impact on daily life becomes increasingly
visible. Nowadays, everyone not only needs to manage data of various
kinds, but also continuously generates large amounts of data. In
addition, Big Data and data analysis are intensively discussed in public
dialogue because of their influences on society. For the understanding of
such discussions and for being able to participate in them, fundamental
knowledge on data management is necessary. Especially, being aware
of the threats accompanying the ability to analyze large amounts of
data in nearly real-time becomes increasingly important. This raises the
question, which key competencies are necessary for daily dealings with
data and data management.
In this paper, we will first point out the importance of data management
and of Big Data in daily life. On this basis, we will analyze which are
the key competencies everyone needs concerning data management to
be able to handle data in a proper way in daily life. Afterwards, we will
discuss the impact of these changes in data management on computer
science education and in particular database education.
The poster and abstract describe the importance of teaching
information security in school. After a short description of information
security and important aspects, I will show, how information security
fits into different guidelines or models for computer science educations
and that it is therefore on of the key competencies. Afterwards I will
present you a rough insight of teaching information security in Austria.
teaspoon
(2018)
Answer Set Programming (ASP) is an approach to declarative problem solving, combining a rich yet simple modeling language with high performance solving capacities. We here develop an ASP-based approach to curriculum-based course timetabling (CB-CTT), one of the most widely studied course timetabling problems. The resulting teaspoon system reads a CB-CTT instance of a standard input format and converts it into a set of ASP facts. In turn, these facts are combined with a first-order encoding for CB-CTT solving, which can subsequently be solved by any off-the-shelf ASP systems. We establish the competitiveness of our approach by empirically contrasting it to the best known bounds obtained so far via dedicated implementations. Furthermore, we extend the teaspoon system to multi-objective course timetabling and consider minimal perturbation problems.
Tele-board : enabling efficient collaboration in digital design spaces across time and distance
(2011)
Research publications and data nowadays should be publicly available on the internet and, theoretically, usable for everyone to develop further research, products, or services. The long-term accessibility of research data is, therefore, fundamental in the economy of the research production process. However, the availability of data is not sufficient by itself, but also their quality must be verifiable. Measures to ensure reuse and reproducibility need to include the entire research life cycle, from the experimental design to the generation of data, quality control, statistical analysis, interpretation, and validation of the results. Hence, high-quality records, particularly for providing a string of documents for the verifiable origin of data, are essential elements that can act as a certificate for potential users (customers). These records also improve the traceability and transparency of data and processes, therefore, improving the reliability of results. Standards for data acquisition, analysis, and documentation have been fostered in the last decade driven by grassroot initiatives of researchers and organizations such as the Research Data Alliance (RDA). Nevertheless, what is still largely missing in the life science academic research are agreed procedures for complex routine research workflows. Here, well-crafted documentation like standard operating procedures (SOPs) offer clear direction and instructions specifically designed to avoid deviations as an absolute necessity for reproducibility. Therefore, this paper provides a standardized workflow that explains step by step how to write an SOP to be used as a starting point for appropriate research documentation.
Testability evaluation of sequential designs incorporating the multi-mode scannable memory element
(1999)
Interest in developing a new method of man-to-machine communication-a brain-computer interface (BCI)-has grown steadily over the past few decades. BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways of nerves and muscles. These systems use signals recorded from the scalp, the surface of the cortex, or from inside the brain to enable users to control a variety of applications including simple word-processing software and orthotics. BCI technology could therefore provide a new communication and control option for individuals who cannot otherwise express their wishes to the outside world. Signal processing and classification methods are essential tools in the development of improved BCI technology. We organized the BCI Competition 2003 to evaluate the current state of the art of these tools. Four laboratories well versed in EEG-based BCI research provided six data sets in a documented format. We made these data sets (i.e., labeled training sets and unlabeled test sets) and their descriptions available on the Internet. The goal in the competition was to maximize the performance measure for the test labels. Researchers worldwide tested their algorithms and competed for the best classification results. This paper describes the six data sets and the results and function of the most successful algorithms
A brain-computer interface (BCI) is a system that allows its users to control external devices with brain activity. Although the proof-of-concept was given decades ago, the reliable translation of user intent into device control commands is still a major challenge. Success requires the effective interaction of two adaptive controllers: the user's brain, which produces brain activity that encodes intent, and the BCI system, which translates that activity into device control commands. In order to facilitate this interaction, many laboratories are exploring a variety of signal analysis techniques to improve the adaptation of the BCI system to the user. In the literature, many machine learning and pattern classification algorithms have been reported to give impressive results when applied to BCI data in offline analyses. However, it is more difficult to evaluate their relative value for actual online use. BCI data competitions have been organized to provide objective formal evaluations of alternative methods. Prompted by the great interest in the first two BCI Competitions, we organized the third BCI Competition to address several of the most difficult and important analysis problems in BCI research. The paper describes the data sets that were provided to the competitors and gives an overview of the results.
The Berlin Brain-Computer Interface (BBCI) project develops a noninvasive BCI system whose key features are 1) the use of well-established motor competences as control paradigms, 2) high-dimensional features from 128-channel electroencephalogram (EEG), and 3) advanced machine learning techniques. As reported earlier, our experiments demonstrate that very high information transfer rates can be achieved using the readiness potential (RP) when predicting the laterality of upcoming left-versus right-hand movements in healthy subjects. A more recent study showed that the RP similarily accompanies phantom movements in arm amputees, but the signal strength decreases with longer loss of the limb. In a complementary approach, oscillatory features are used to discriminate imagined movements (left hand versus right hand versus foot). In a recent feedback study with six healthy subjects with no or very little experience with BCI control, three subjects achieved an information transfer rate above 35 bits per minute (bpm), and further two subjects above 24 and 15 bpm, while one subject could not achieve any BCI control. These results are encouraging for an EEG-based BCI system in untrained subjects that is independent of peripheral nervous system activity and does not rely on evoked potentials even when compared to results with very well-trained subjects operating other BCI systems
Background:
Pruritus often accompanies chronic skin diseases, exerting considerable burden on many areas of patient functioning; this burden and the features of pruritus remain insufficiently characterized.
Objective:
To investigate characteristics, including localization patterns, and burden of pruritus in patients with chronic dermatoses.
Methods:
We recruited 800 patients with active chronic skin diseases. We assessed pruritus intensity, localization, and further characteristics. We used validated questionnaires to assess quality of life, work productivity and activity impairment, anxiety, depression, and sleep quality.
Results:
Nine out of every 10 patients had experienced pruritus throughout their disease and 73% in the last 7 days. Pruritus often affected the entire body and was not restricted to skin lesions. Patients with moderate to severe pruritus reported significantly more impairment to their sleep quality and work productivity, and they were more depressed and anxious than control individuals and patients with mild or no pruritus. Suicidal ideations were highly prevalent in patients with chronic pruritus (18.5%) and atopic dermatitis (11.8%).
Conclusions:
Pruritus prevalence and intensity are very high across all dermatoses studied; intensity is linked to impairment in many areas of daily functioning. Effective treatment strategies are urgently required to treat pruritus and the underlying skin disease. ( J Am Acad Dermatol 2021;84:691-700.)
We study the complexity of two-person constraint satisfaction games. An instance of such a game is given by a collection of constraints on overlapping sets of variables, and the two players alternately make moves assigning values from a finite domain to the variables, in a specified order. The first player tries to satisfy all constraints, while the other tries to break at least one constraint: the goal is to decide whether the first player has a winning strategy. We show that such games can be conveniently represented by a logical form of quantified constraint satisfaction, where an instance is given by a first-order sentence in which quantifiers alternate and the quantifier-free part is a conjunction of (positive) atomic formulas; the goal is to decide whether the sentence is true. While the problem of deciding such a game is PSPACE-complete in general, by restricting the set of allowed constraint predicates, one can obtain infinite classes of constraint satisfaction games of lower complexity. We use the quantified constraint satisfaction framework to study how the complexity of deciding such a game depends on the parameter set of allowed predicates. With every predicate. one can associate certain predicate-preserving operations, called polymorphisms. We show that the complexity of our games is determined by the surjective polymorphisms of the constraint predicates. We illustrate how this result can be used by identifying the complexity of a wide variety of constraint satisfaction games.
The Course's SIB Libraries
(2014)
This chapter gives a detailed description of the service framework underlying all the example projects that form the foundation of this book. It describes the different SIB libraries that we made available for the course “Process modeling in the natural sciences” to provide the functionality that was required for the envisaged applications. The students used these SIB libraries to realize their projects.
The family of default logics
(1998)
This article shows a discussion about the key competencies
in informatics and ICT viewed from a philosophical foundation presented
by Martha Nussbaum, which is known as ‘ten central capabilities’.
Firstly, the outline of ‘The Capability Approach’, which has been presented
by Amartya Sen and Nussbaum as a theoretical framework of
assessing the state of social welfare, will be explained. Secondly, the
body of Nussbaum’s ten central capabilities and the reason for being
applied as the basis of discussion will be shown. Thirdly, the relationship
between the concept of ‘capability’ and ‘competency’ is to be
discussed. After that, the author’s assumption of the key competencies
in informatics and ICT led from the examination of Nussbaum’s ten
capabilities will be presented.
The Potsdam answer set solving collection, or Potassco for short, bundles various tools implementing and/or applying answer set programming. The article at hand succeeds an earlier description of the Potassco project published in Gebser et al. (AI Commun 24(2):107-124, 2011). Hence, we concentrate in what follows on the major features of the most recent, fifth generation of the ASP system clingo and highlight some recent resulting application systems.
Answer Set Programming (ASP) is a prominent knowledge representation language with roots in logic programming and non-monotonic reasoning. Biennial ASP competitions are organized in order to furnish challenging benchmark collections and assess the advancement of the state of the art in ASP solving. In this paper, we report on the design and results of the Seventh ASP Competition, jointly organized by the University of Calabria (Italy), the University of Genova (Italy), and the University of Potsdam (Germany), in affiliation with the 14th International Conference on Logic Programming and Non-Monotonic Reasoning (LPNMR 2017).
Answer Set Programming (ASP) is a well-known paradigm of declarative programming with roots in logic programming and non-monotonic reasoning. Similar to other closely related problemsolving technologies, such as SAT/SMT, QBF, Planning and Scheduling, advancements in ASP solving are assessed in competition events. In this paper, we report about the design and results of the Sixth ASP Competition, which was jointly organized by the University of Calabria (Italy), Aalto University (Finland), and the University of Genoa (Italy), in affiliation with the 13th International Conference on Logic Programming and Non-Monotonic Reasoning. This edition maintained some of the design decisions introduced in 2014, e.g., the conception of sub-tracks, the scoring scheme,and the adherence to a fixed modeling language in order to push the adoption of the ASP-Core-2 standard. On the other hand, it featured also some novelties, like a benchmark selection stage classifying instances according to their empirical hardness, and a “Marathon” track where the topperforming systems are given more time for solving hard benchmarks.
The Student Learning Ecology
(2015)
Educational research on social media has showed that
students use it for socialisation, personal communication, and informal
learning. Recent studies have argued that students to some degree use
social media to carry out formal schoolwork. This article gives an
explorative account on how a small sample of Norwegian high school
students use social media to self-organise formal schoolwork. This
user pattern can be called a “student learning ecology”, which is a
user perspective on how participating students gain access to learning
resources.