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This paper proposes a novel framework for fusing multi-temporal, multispectral satellite images and OpenStreetMap (OSM) data for the classification of local climate zones (LCZs). Feature stacking is the most commonly used method of data fusion but does not consider the heterogeneity of multimodal optical images and OSM data, which becomes its main drawback. The proposed framework processes two data sources separately and then combines them at the model level through two fusion models (the landuse fusion model and building fusion model) that aim to fuse optical images with landuse and buildings layers of OSM data, respectively. In addition, a new approach to detecting building incompleteness of OSM data is proposed. The proposed framework was trained and tested using the data from the 2017 IEEE GRSS Data Fusion Contest and further validated on one additional test (AT) set containing test samples that are manually labeled in Munich and New York. The experimental results have indicated that compared with the feature stacking-based baseline framework, the proposed framework is effective in fusing optical images with OSM data for the classification of LCZs with high generalization capability on a large scale. The classification accuracy of the proposed framework outperforms the baseline framework by more than 6% and 2% while testing on the test set of 2017 IEEE GRSS Data Fusion Contest and the AT set, respectively. In addition, the proposed framework is less sensitive to spectral diversities of optical satellite images and thus achieves more stable classification performance than the state-of-the-art frameworks. [ABSTRACT FROM AUTHOR]

Tomographic synthetic aperture radar (TomoSAR) inversion of urban areas is an inherently sparse reconstruction problem and, hence, can be solved using compressive sensing (CS) algorithms. This paper proposes solutions for two notorious problems in this field. First, TomoSAR requires a high number of data sets, which makes the technique expensive. However, it can be shown that the number of acquisitions and the signal-to-noise ratio (SNR) can be traded off against each other, because it is asymptotically only the product of the number of acquisitions and SNR that determines the reconstruction quality. We propose to increase SNR by integrating nonlocal (NL) estimation into the inversion and show that a reasonable reconstruction of buildings from only seven interferograms is feasible. Second, CS-based inversion is computationally expensive and therefore, barely suitable for large-scale applications. We introduce a new fast and accurate algorithm for solving the NL L1-L2-minimization problem, central to CS-based reconstruction algorithms. The applicability of the algorithm is demonstrated using simulated data and TerraSAR-X high-resolution spotlight images over an area in Munich, Germany. [ABSTRACT FROM AUTHOR]

This work presents eight demonstrators and one showcase developed within the 5G-Xcast project. They experimentally demonstrate and validate key technical enablers for the future of media delivery, associated with multicast and broadcast communication capabilities in 5th Generation (5G). In 5G-Xcast, three existing testbeds: IRT in Munich (Germany), 5GIC in Surrey (U.K.), and TUAS in Turku (Finland), have been developed into 5G broadcast and multicast testing networks, which enables us to demonstrate our vision of a converged 5G infrastructure with fixed and mobile accesses and terrestrial broadcast, delivering immersive audio-visual media content. Built upon the improved testing networks, the demonstrators and showcase developed in 5G-Xcast show the impact of the technology developed in the project. Our demonstrations predominantly cover use cases belonging to two verticals: Media & Entertainment and Public Warning, which are future 5G scenarios relevant to multicast and broadcast delivery. In this paper, we present the development of these demonstrators, the showcase, and the testbeds. We also provide key findings from the experiments and demonstrations, which not only validate the technical solutions developed in the project, but also illustrate the potential technical impact of these solutions for broadcasters, content providers, operators, and other industries interested in the future immersive media delivery. [ABSTRACT FROM AUTHOR]

This paper presents the results of a measurement campaign conducted in the winter of 2002 around the city of Munich in southern Germany. The primary goal was to evaluate the link performance of the land mobile satellite channel at Ku-band and to characterize the temporal behavior of the channel to help in the evaluation of different fade mitigation techniques for future mobile satellite systems that aim at employing this frequency band. To achieve this objective, first- and second-order channel statistics will be presented, the outage probability of the channel analyzed, and a Markov-chain-based narrowband channel model proposed. [ABSTRACT FROM AUTHOR]

Reducing traffic delay is of crucial importance for the development of sustainable transportation systems, which is a challenging task in the studies of stochastic shortest path (SSP) problem. Existing methods based on the probability tail model to solve the SSP problem, seek for the path that minimizes the probability of delay occurrence, which is equal to maximizing the probability of reaching the destination before a deadline (i.e., arriving on time). However, they suffer from low accuracy or high computational cost. Therefore, we design a novel and practical Q-learning approach where the converged Q-values have the practical meaning as the actual probabilities of arriving on time so as to improve the accuracy of finding the real optimal path. By further adopting dynamic neural networks to learn the value function, our approach can scale well to large road networks with arbitrary deadlines. Moreover, our approach is flexible to implement in a time dependent manner, which further improves the performance of returned path. Experimental results on some road networks with real mobility data, such as Beijing, Munich and Singapore, demonstrate the significant advantages of the proposed approach over other methods. [ABSTRACT FROM AUTHOR]

Highlights Europe's premier conference and exhibition for electronic design, automation and test in Munich, Germany. Estimated number of attendance; Topics discussed; Programs and activities.

During the 1950s, computer programming was a local practice. Programs from one computing center would not work on computers elsewhere. For example, programs written in Munich differed radically in style from programs written in Amsterdam. Similar problems were also encountered in the United States, leading American computer programmers in 1954 to combine the ideal of a machine-independent programming tool with the metaphor of language. European researchers eagerly embraced this idea and subsequently collaborated with their American colleagues in developing such a language, called Algol. Although it was meant to be universal in terms of machine-independence, in order to be a working technology, Algol by necessity had to be implemented on a specific type of machine. As a result, the aspired universal Algol language would be bound to a compiler, or translator, which depended on the specificities of the underlying machine. Local machinery, traditions of programming, and compilers would in turn give Algol a local appearance and, in more than one case, led to the decision of working with a restricted version of the language. Thus, in practice, Algol came with local dialects. This article elaborates on the tension between universality and locality by contrasting the Amsterdam and Munich styles of programming. In addition to the famous controversy on recursive procedures, it also highlights Edsger Dijkstra's concept of a machine-independent object language. [ABSTRACT FROM PUBLISHER]

In this article, we discuss a spectrum trading mechanism implemented by the spectrum broker in TV whitespaces. TVWS are spectrum frequency bands unused by DTV, interleaved in both frequency and space. Underutilization of these bands results from the fact that the DTV transmission systems now operational in the spectrum from 470 to 790 MHz are multifrequency systems employing high tower and high power network geometries, and must be managed for interference between transmitters. We motivate the use of a spectrum broker, an entity that manages the TVWS secondary spectrum market. Such a TVWS broker?s responsibilities include planning the possible broad uses of the available spectrum in the TVWS; packaging the spectrum for short-term disposal through trading mechanisms; serving the broker?s customers, with spectrum-leasing contracts; and acting as the port of call to handle interference caused by its customers to the primary DTV systems or between its customers themselves. We discuss the spectrum broker?s merchant and auction modes for spectrum trading. In the merchant mode, the base price is decided by the allocation procedure, which considers various factors influencing the value of TVWS in a given place. In the auction mode, the customers? demands and bids decide the final price of the spectrum. We discuss the auction design and show results of the spectrum trading mechanisms, which have been successfully applied in a real-world test scenario in the area of Munich, Germany. [ABSTRACT FROM PUBLISHER]

Presents an overview of the electric fields measured in cloud-to-ground lightning in Munich, Germany between 1984 and 1993. Reflection of a plane wave at the perfectly conducting earth; Block diagram of the measuring system used in the study; Duration of the multiple-stroke flashes; Negative cloud-to-ground flashes containing continuing currents.