Adding XMP support to Firefox

XMP (Extensible Metadata Platform) is an RDF-based framework of Adobe Systems Incorporated that supports the embedding of metadata in application files. If it becomes widely used on the web, it will provide a rich source of metadata to semantic web applications, too. This paper presents a solution to add a unique feature to the popular Firefox web browser, the capability to extract XMP metadata from web resources. The solution is based on the Piggy Bank Firefox extension that turns Firefox into a "semantic web browser"

Reduction of Survey Sites in Dialectology: A New Methodology Based on Clustering

Many language change studies aim for a partial revisitation, i.e., selecting survey sites from previous dialect studies. The central issue of survey site reduction, however, has often been addressed only qualitatively. Cluster analysis offers an innovative means of identifying the most representative survey sites among a set of original survey sites. In this paper, we present a general methodology for finding representative sites for an intended study, potentially applicable to any collection of data about dialects or linguistic variation. We elaborate the quantitative steps of the proposedmethodology in the context of the “Linguistic Atlas of Japan” (LAJ). Next, we demonstrate the full application of the methodology on the “Linguistic Atlas of German-speaking Switzerland” (Germ.: “Sprachatlas der Deutschen Schweiz”—SDS), with the explicit aim of selecting survey sites corresponding to the aims of the current project “Swiss German Dialects Across Time and Space” (SDATS), which revisits SDS 70 years later. We find that depending on the circumstances and requirements of a study, the proposed methodology, introducing cluster analysis into the survey site reduction process, allows for a greater objectivity in comparison to traditional approaches. We suggest, however, that the suitability of any set of candidate survey sites resulting from the proposed methodology be rigorously revised by experts due to potential incongruences, such as the overlap of objectives and variables across the original and intended studies and ongoing dialect change

Large-scale Analysis and Simulation of Traffic Flow using Markov Models

Modeling and simulating movement of vehicles in established transportation infrastructures, especially in large urban road networks is an important task. It helps with understanding and handling traffic problems, optimizing traffic regulations and adapting the traffic management in real time for unexpected disaster events. A mathematically rigorous stochastic model that can be used for traffic analysis was proposed earlier by other researchers which is based on an interplay between graph and Markov chain theories. This model provides a transition probability matrix which describes the traffic's dynamic with its unique stationary distribution of the vehicles on the road network. In this paper, a new parametrization is presented for this model by introducing the concept of two-dimensional stationary distribution which can handle the traffic's dynamic together with the vehicles' distribution. In addition, the weighted least squares estimation method is applied for estimating this new parameter matrix using trajectory data. In a case study, we apply our method on the Taxi Trajectory Prediction dataset and road network data from the OpenStreetMap project, both available publicly. To test our approach, we have implemented the proposed model in software. We have run simulations in medium and large scales and both the model and estimation procedure, based on artificial and real datasets, have been proved satisfactory. In a real application, we have unfolded a stationary distribution on the map graph of Porto, based on the dataset. The approach described here combines techniques whose use together to analyze traffic on large road networks has not previously been reported

Borok szorbinsav tartalmának meghatározása

Die in der Weinkunde üblichen spektrophotometrischen Methoden, die Rebeleinsche Methode und die gaschromatographischen Methoden wurden untersucht bzw. ihre Anwendungsgebiete und verschiedene Methoden zur Beseitigung der störenden Substanzen beschrieben. Die letztgenannten zwei Methoden sind zur Bestimmung von Sorbinsäurespuren sowie auch zur uFeststellung der Abwesenheit von Sorbinsäure gleichfalls geeignet. Of the methods used in oenology, the spectrophotometric method, the Rebelein method and gaschromatographic methods were studied, their fields of application and ways of eliminating the effect of interfering substances are described. Both latter methods are suitable for the determination of trace amounts of sorbic acid and for confirming the absence of sorbic acid

Markov modeling of traffic flow in Smart Cities

Modeling and simulating the traffic flow in large urban road networks are important tasks. A mathematically rigorous stochastic model proposed in [8] is based on the synthesis of the graph and Markov chain theories. In this model, the transition probability matrix describes the traffic dynamics and its unique stationary distribution approximates the proportion of the vehicles at the segments of the road network. In this paper various Markov models are studied and a simulation method is presented for generating random traffic trajectories on a road network based on the two-dimensional stationary distribution of the models. In a case study we apply our method to the central region of the city of Debrecen by using the road network data from the OpenStreetMap project which is available publicly

Markov modeling of traffic flow in Smart Cities

Modeling and simulating the traffic flow in large urban road networks are important tasks. A mathematically rigorous stochastic model proposed in [8] is based on the synthesis of the graph and Markov chain theories. In this model, the transition probability matrix describes the traffic dynamics and its unique stationary distribution approximates the proportion of the vehicles at the segments of the road network. In this paper various Markov models are studied and a simulation method is presented for generating random traffic trajectories on a road network based on the two-dimensional stationary distribution of the models. In a case study we apply our method to the central region of the city of Debrecen by using the road network data from the OpenStreetMap project which is available publicly