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Information reliability and automatic computation are two important aspects that are continuously pushing the Web to be more semantic. Information uploaded to the Web should be reusable and extractable automatically to other applications, platforms, etc. Several tools exist to explicitly markup Web content. The Web services may also have a positive role on the automatic processing of Web contents, especially when they act as flexible and agile agents. However, Web services themselves should be developed with semantics in mind. They should include and provide structured information to facilitate their use, reuse, composition, query, etc. In this chapter, the authors focus on evaluating state-of-the-art semantic aspects and approaches in Web services. Ultimately, this contributes to the goal of Web knowledge management, execution, and transfer.
Updating a shared data structure in a parallel program is usually done with some sort of high-level synchronization operation to ensure correctness and consistency. However, underlying synchronization instructions in a processor architecture are costly and rather limited in their scalability on larger multi-core/multi-processors systems. In this paper, we examine work queue operations where such costly atomic update operations are replaced with non-atomic modifiers (simple read+write). In this approach, we trade the exact amount of work with atomic operations against doing more and redundant work but without atomic operations and without violating the correctness of the algorithm. We show results for the application of this idea to the concrete scenario of parallel Breadth First Search (BFS) algorithms for undirected graphs on two large NUMA shared memory system with up to 64 cores.
Although most individuals who gamble do so without any adverse consequences, some individuals develop a recurrent, maladaptive pattern of gambling behaviour, often called pathological gambling or gambling disorder, that is associated with financial losses, disruption of family and interpersonal relationships, and co-occurring psychiatric disorders. Identifying whether different types of gambling modalities vary in their ability to lead to maladaptive patterns of gambling behaviour is essential to develop public policies that seek to balance access to gambling opportunities with minimizing risk for the potential adverse consequences of gambling behaviour. Until recently, assessing the risk potential of different types of gambling products was nearly impossible. ASTERIG, initially developed in Germany in 2006-2010, is an assessment tool to measure and to evaluate the risk potential of any gambling product based on scores on ten dimensions. In doing so, it also allows a comparison to be drawn between the addictive potential of different gambling products. Furthermore, the tool highlights where the specific risk potential of each specific gambling product lies. This makes it a valuable tool at the legislative, case law, and administrative levels as it allows the risk potential of individual gambling products to be identified and to be compared globally and across 10 different dimensions of risk potential. We note that specific gambling products should always be evaluated rather than product groups (lotteries, slot machines) or providers, as there may be variations among those product groups that impact their risk potential. For example, slot machines may vary on the amount of jackpot, which may influence their risk potential.
Switched power electronic subsystems are widely used in various applications. A fault in one of their components may have a significant effect on the system’s load or may even cause a damage. Therefore, it is important to detect and isolate faults and to report true faults to a supervisory system in order to avoid malfunction of or damage to a load. If, in a model-based approach to fault detection and isolation of hybrid systems, switching devices are considered as ideal switches then some equations must be reformulated whenever some devices have switched. In this paper, a fixed causality bond graph representation of hybrid system models is used, i.e., computational causalities assigned according to the Standard Causality Assignment Procedure (SCAP) are independent of system modes of operation. The latter are taken into account by transformer moduli mi(t) ∈ {0, 1} ∀t ≥ 0 in a unique set of equations of motion. In a case study, this approach is used for fault diagnosis in a three-phase full-wave rectifier. Residuals of Analytical Redundancy Relations (ARRs) holding for all modes of operations and serving as fault indicators are computed in an offline simulation as part of a DAE system by using a bond graph model of the faulty system instead of the real one and by coupling it to a bond graph of the healthy system by means of residual sinks.
Increased endothelin-1 decreases PKC alpha (PKCα), resulting in high miRNA 15a levels in kidney tumors. Breast cancer cells treated with ET-1, β-estrogen, Tamoxifen, Tamoxifen + β-estrogen and Tamoxifen + ET-1 were analysed regarding miRNA 15a expression. Significantly increased miRNA 15a levels were found after ET-1, becoming further increased in Tamoxifen + ET-1 treated cells. Our group already showed that miRNA 15a induces MAPK p38 splicing resulting in a truncated product called Mxi-2, whose function has yet to be defined in tumors. We described for the first time in ET-1 induced tumor cells that Mxi-2 builds a complex with Ago2, a miRNA binding protein, which is important for the localization of miRNAs to the 3′UTR of target genes. Furthermore, we show that Mxi-2/Ago2 is important for the interaction with the miRNA 1285 which binds to the 3′end of the tumor suppressor gene p53, being responsible for the downregulation of p53. Tissue arrays from breast cancer patients were performed, analysing Mxi-2, p53 and PKCα. Since the Mxi-2 levels increase in Tamoxifen + ET-1 treated cells, we claim that increasing ET-1 levels in Tamoxifen treated breast cancer patients are responsible for decreasing p53 levels. In summary, ET-1 decreases nuclear PKCα levels, while increasing the amount of miRNA 15a. This causes high levels of Mxi-2, necessary for complex formation with Ago2. The newly identified Mxi-2/Ago2 complex interacting with miRNA 1285 leads to increased 3′UTR p53 interaction, resulting in decreased p53 levels and subsequent tumor progression. This newly identified mechanism is a possible explanation for the development of ET-1 induced tumors.
This paper examines how students learn to collaborate in English by participating in an intercultural project that focuses on teaching students to work together on a digital writing project using various online tools, and participated in this digital collaboration project. Mixed groups of students, two French and two German, used several synchronous and asynchronous tools to communicate with their counterparts (Facebook, WordPress blog, WIMS e-learning platform, email, videoconferencing). Students had to produce an article together, comparing French and German attitudes about a topic they negotiated freely in their groups. Before publishing their post, students were expected to peer-review the article written by their group. Once published, the stage consisted of voting for the best posts on the e-learning platform, WIMS. A videoconference was also organized to create cohesion between the participants. The result of the student evaluations, together with the administrative, technical vastly differing university setups is presented.
The BRICS component model: a model-based development paradigm for complex robotics software systems
(2013)
Earth’s nearest candidate supermassive black hole lies at the centre of the Milky Way1. Its electromagnetic emission is thought to be powered by radiatively inefficient accretion of gas from its environment2, which is a standard mode of energy supply for most galactic nuclei. X-ray measurements have already resolved a tenuous hot gas component from which the black hole can be fed3. The magnetization of the gas, however, which is a crucial parameter determining the structure of the accretion flow, remains unknown. Strong magnetic fields can influence the dynamics of accretion, remove angular momentum from the infalling gas4, expel matter through relativistic jets5 and lead to synchrotron emission such as that previously observed6, 7, 8. Here we report multi-frequency radio measurements of a newly discovered pulsar close to the Galactic Centre9, 10, 11, 12 and show that the pulsar’s unusually large Faraday rotation (the rotation of the plane of polarization of the emission in the presence of an external magnetic field) indicates that there is a dynamically important magnetic field near the black hole. If this field is accreted down to the event horizon it provides enough magnetic flux to explain the observed emission—from radio to X-ray wavelengths—from the black hole.
Radio pulsars in relativistic binary systems are unique tools to study the curved space-time around massive compact objects. The discovery of a pulsar closely orbiting the super-massive black hole at the centre of our Galaxy, Sgr A⋆, would provide a superb test-bed for gravitational physics. To date, the absence of any radio pulsar discoveries within a few arc minutes of Sgr A⋆ has been explained by one principal factor: extreme scattering of radio waves caused by inhomogeneities in the ionized component of the interstellar medium in the central 100 pc around Sgr A⋆. Scattering, which causes temporal broadening of pulses, can only be mitigated by observing at higher frequencies. Here we describe recent searches of the Galactic centre region performed at a frequency of 18.95 GHz with the Effelsberg radio telescope.
We derive rates of convergence for limit theorems that reveal the intricate structure of the phase transitions in a mean-field version of the Blume-Emery-Griffith model. The theorems consist of scaling limits for the total spin. The model depends on the inverse temperature β and the interaction strength K. The rates of convergence results are obtained as (β,K) converges along appropriate sequences (βn,Kn) to points belonging to various subsets of the phase diagram which include a curve of second-order points and a tricritical point. We apply Stein's method for normal and non-normal approximation avoiding the use of transforms and supplying bounds, such as those of Berry-Esseen quality, on approximation error. We observe an additional phase transition phenomenon in the sense that depending on how fast Kn and βn are converging to points in various subsets of the phase diagram, different rates of convergences to one and the same limiting distribution occur.
Power train models are required to simulate hence predict energy consumption of vehicles. Efficiencies for different components in power train are required. Common procedures use digitalised shell models (or maps) to model the efficiency of Internal Combustion Engines (ICE) and manual gearboxes (MG). Errors are connected with these models and affect the accuracy of the calculation. The accuracy depends on the configuration of the simulation, the digitalisation of the data and the data used. This paper evaluates these sources of error. The understanding of the source of error can improve the results of the modelling by more than eight percent.
Traffic simulations are generally used to forecast traffic behavior or to simulate non-player characters in computer games and virual environments. These systems are usually modeled in such a way that traffic rules are strictly followed. However, rule violations are a common part of real-life traffic and thus should be integrated into such models.
Real-Time Simulation of Camera Errors and Their Effect on Some Basic Robotic Vision Algorithms
(2013)
Computers will soon be powerful enough to simulate consciousness. The artificial life community should start to try to understand how consciousness could be simulated. The proposal is to build an artificial life system in which consciousness might be able to evolve. The idea is to develop internet-wide artificial universe in which the agents can evolve. Users play games by defining agents that form communities. The communities have to perform tasks, or compete, or whatever the specific game demands. The demands should be such that agents that are more aware of their universe are more likely to succeed. The agents reproduce and evolve within their user’s machine, but can also sometimes transfer to other machine across the internet. Users will be able to choose the capabilities of their agents from a fixed list, but may also write their own powers for their agents.
This work extends the affordance-inspired robot control architecture introduced in the MACS project [35] and especially its approach to integrate symbolic planning systems given in [24] by providing methods to automated abstraction of affordances to high-level operators. It discusses how symbolic planning instances can be generated automatically based on these operators and introduces an instantiation method to execute the resulting plans. Preconditions and effects of agent behaviour are learned and represented in Gärdenfors conceptual spaces framework. Its notion of similarity is used to group behaviours to abstract operators based on the affordance-inspired, function-centred view on the environment. Ways on how the capabilities of conceptual spaces to map subsymbolic to symbolic representations to generate PDDL planning domains including affordance-based operators are discussed. During plan execution, affordance-based operators are instantiated by agent behaviour based on the situation directly before its execution. The current situation is compared to past ones and the behaviour that has been most successful in the past is applied. Execution failures can be repaired by action substitution. The concept of using contexts to dynamically change dimension salience as introduced by Gärdenfors is realized by using techniques from the field of feature selection. The approach is evaluated using a 3D simulation environment and implementations of several object manipulation behaviours.
Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of microscopic on macroscopic phenomena. Accurate molecular models are indispensable for such simulations in order to predict physical target observables, like density, pressure, diffusion coefficients or energetic properties, quantitatively over a wide range of temperatures. Thereby, molecular interactions are described mathematically by force fields. The mathematical description includes parameters for both intramolecular and intermolecular interactions. While intramolecular force field parameters can be determined by quantum mechanics, the parameterization of the intermolecular part is often tedious. Recently, an empirical procedure, based on the minimization of a loss function between simulated and experimental physical properties, was published by the authors. Thereby, efficient gradient-based numerical optimization algorithms were used. However, empirical force field optimization is inhibited by the two following central issues appearing in molecular simulations: firstly, they are extremely time-consuming, even on modern and high-performance computer clusters, and secondly, simulation data is affected by statistical noise. The latter provokes the fact that an accurate computation of gradients or Hessians is nearly impossible close to a local or global minimum, mainly because the loss function is flat. Therefore, the question arises of whether to apply a derivative-free method approximating the loss function by an appropriate model function. In this paper, a new Sparse Grid-based Optimization Workflow (SpaGrOW) is presented, which accomplishes this task robustly and, at the same time, keeps the number of time-consuming simulations relatively small. This is achieved by an efficient sampling procedure for the approximation based on sparse grids, which is described in full detail: in order to counteract the fact that sparse grids are fully occupied on their boundaries, a mathematical transformation is applied to generate homogeneous Dirichlet boundary conditions. As the main drawback of sparse grids methods is the assumption that the function to be modeled exhibits certain smoothness properties, it has to be approximated by smooth functions first. Radial basis functions turned out to be very suitable to solve this task. The smoothing procedure and the subsequent interpolation on sparse grids are performed within sufficiently large compact trust regions of the parameter space. It is shown and explained how the combination of the three ingredients leads to a new efficient derivative-free algorithm, which has the additional advantage that it is capable of reducing the overall number of simulations by a factor of about two in comparison to gradient-based optimization methods. At the same time, the robustness with respect to statistical noise is maintained. This assertion is proven by both theoretical considerations and practical evaluations for molecular simulations on chemical example substances.
The device (10) has a handrail (18) provided with an optical contactless monitoring device formed as an active sensor system, where the monitoring device is arranged in a region of a guide (14) of the handrail at a front base (16) of an escalator (12) or a moving pavement. The monitoring device has two transmission paths (28, 30) with wavelength bands that are different from each other, where one of the paths includes the handrail. Ratio or difference between signals of the paths is used for recognizing foreign bodies e.g. hands of adults and children.
The simulation of fluid flows is of importance to many fields of application, especially in industry and infrastructure. The modelling equations applied describe a coupled system of non-linear, hyperbolic partial differential equations given by one-dimensional shallow water equations that enable the consistent implementation of free surface flows in open channels as well as pressurised flows in closed pipes. The numerical realisation of these equations is complicated and challenging to date due to their characteristic properties that are able to cause discontinuous solutions.
Application performance improvements through VM parameter modification after runtime analysis
(2013)
Grailog embodies a systematics to visualize knowledge sources by graphical elements. Its main benefit is that the resulting visual presentations are easier to read for humans than the original symbolic source code. In this paper we introduce a methodology to handle the mapping from Datalog RuleML, serialized in XML, to an SVG representation of Grailog, also serialized in XML, via eXtensible Stylesheet Language Transformations (XSLT) 2.0/XML; the SVG is then rendered visually by modern Web browsers. This initial mapping is realized to target Grailog's "fully node copied" normal form. Elements can thus be translated one at a time, separating the fundamental Datalog-to-SVG translation concern from the concern of merging node copies for optimal (hyper)graph layout and avoiding its high computational complexity in this online tool. The resulting open source Grailog Knowledge-Source Visualizer (Grailog KS Viz) supports Datalog RuleML with positional relations of arity n>1. The on-the-fly transformation was shown to run on all recent major Web browsers and should be easy to understand, use, and extend.
Distributed systems comprise distributed computing systems, distributed information systems, and distributed pervasive systems. They are often very complex and their implementation is challenging. Intensive and continuous testing is indispensable to ensure reliability and high quality of a distributed system. The testing process should have a high degree of automation, not only on lower levels (i.e. unit and module testing), but also on higher testing levels (e.g. system, integration, and acceptance tests). To achieve automation on higher testing levels virtual infrastructure components (e.g. virtual machines, virtual networks) that are offered as a Service (IaaS) can be employed. The elasticity of on-demand computation resources fits well together with the varying resource demands of automated test execution.
A methodology for automated acceptance testing of distributed systems that uses virtual infrastructure is presented. It is founded on a task-oriented model that is used to abstract concurrency and asynchronous, remote communication in distributed systems. The model is used as groundwork for a domain-specific language that allows expressing tests for distributed systems in the form of scenarios. On the one hand, test scenarios are executable and, therefore, fully automated. On the other hand, test scenarios represent requirements to the system under test making an automated, example-based verification possible.
A prototypical implementation is used to apply the developed methodology in the context of two different case studies. The first case study uses RCE as an example of a distributed, workflow-driven integration environment for scientific computing. The second one uses MongoDB as an example of a document-oriented database system that offers distributed data storage through master-slave replication. The results of the experimental evaluation indicate that the developed acceptance testing methodology is a useful approach to design, build, and execute tests for distributed systems with high quality and a high degree of automation.