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In large aircrafts the cabling is very complex and often causes reliability problems. This is specially true for modern In-flight Entertainment (IFE) systems, where every passenger can select a preferred movie, play computer games or be able to communicate with other travellers. Due to EMC problems, wireless communication systems (WiFi etc.) didn't succeed in solving these problems. In this paper an innovative communication system is proposed which perfectly supplements an aircraft IFE system. The key innovation of this system is to use structures that are essential parts of the airframe for data transfer, such as seat rails. Those rails consist of rectangular shapes and could easily be modified to fulfill the function of waveguides for microwaves. A waveguide as part of the seat rail would provide enormous benefits for aircrafts, such as a large bandwidth and consequently high data rates, no problems with EMC, unlimited flexibility of seat configuration, mechanical robustness with associated increase of reliability and a few additional advantages related to aircrafts such as reduction of weight and costs.
“Today’s network landscape consists of quite different network technologies, wide range of end-devices with large scale of capabilities and power, and immense quantity of information and data represented in different formats” [9]. A lot of efforts are being done in order to establish open, scalable and seamless integration of various technologies and content presentation for different devices including mobile considering individual situation of the end user. This is very difficult because various kinds of devices used by different users or in different times/parallel by the same user which is not predictable and have to be recognized by the system in order to know device capabilities. Not only the devices but also Content and User Interfaces are big issues because they could include different kinds of data format like text, image, audio, video, 3D Virtual Reality data and upcoming other formats. Language Learning Game (LLG) is such an example of a device independent application where different kinds of devices and data formats, as a content of a flashcard is used for a collaborative learning. The idea of this game is to create a short story in a foreign language by using mobile devices. The story is developed by a group of participants by exchanging sentences/data via a flashcard system. This way the participants can learn from each other by knowledge sharing without fear of making mistakes because the group members are anonymous. Moreover they do not need a constant support from a teacher.
The invention concerns a method for spectrum monitoring a given frequency band, in which the spectral power density (S(f)) within the given frequency band is determined for all noise and signal components in the frequency band and, in order to detect the presence of one or more signals within the given frequency band, it is evaluated whether the spectral power density (S(f)) exceeds a threshold value (&lgr;). According to the invention, the threshold value (&lgr;) is calculated in accordance with an estimation of a distribution density (hR(S)) for the noise component of the spectral power density (S(f)) within the given frequency band and in accordance with a predefined value for the false-alarm probability (Pfa).
The interaction between agents in multiagent-based control systems requires peer to peer communication between agents avoiding central control. The sensor nodes represent agents and produce measurement data every time step. The nodes exchange time series data by using the peer to peer network in order to calculate an aggregation function for solving a problem cooperatively. We investigate the aggregation process of averaging data for time series data of nodes in a peer to peer network by using the grouping algorithm of Cichon et al. 2018. Nodes communicate whether data is new and map data values according to their sizes into a histogram. This map message consists of the subintervals and vectors for estimating the node joining and leaving the subinterval. At each time step, the nodes communicate with each other in synchronous rounds to exchange map messages until the network converges to a common map message. The node calculates the average value of time series data produced by all nodes in the network by using the histogram algorithm. The relative error for comparing the output of averaging time series data, and the ground truth of the average value in the network will decrease as the size of the network increases. We perform simulations which show that the approximate histograms method provides a reasonable approximation of time series data.
In 2000 the iSign project started as a virtual web-based laboratory for students of study program electrical engineering. Continuous development in the last years led to a heterogeneous learning environment offering learning material, adaptive user settings and access to a simulation tool. Access is available via web and wireless devices such as PCs, Laptops, PDAs, smartphones and mobile phones. Our attempt to adapt the content to the user's needs and the currently used device led us to a XML based data structure. This report shows our research results about content adaptation based on XML data. The two main aspects for that process are: the device capabilities and the adaptation methods using XML data.
We propose secure multi-party computation techniques for the distributed computation of the average using a privacy-preserving extension of gossip algorithms. While recently there has been mainly research on the side of gossip algorithms (GA) for data aggregation itself, to the best of our knowledge, the aforementioned research line does not take into consideration the privacy of the entities involved. More concretely, it is our objective to not reveal a node's private input value to any other node in the network, while still computing the average in a fully-decentralized fashion. Not revealing in our setting means that an attacker gains only minor advantage when guessing a node's private input value. We precisely quantify an attacker's advantage when guessing - as a mean for the level of data privacy leakage of a node's contribution. Our results show that by perturbing the input values of each participating node with pseudo-random noise with appropriate statistical properties (i) only a minor and configurable leakage of private information is revealed, by at the same time (ii) providing a good average approximation at each node. Our approach can be applied to a decentralized prosumer market, in which participants act as energy consumers or producers or both, referred to as prosumers.
Nowadays the processing power of mobile phones, smartphones and PDAs is increasing as well as the transmission bandwidth. Nevertheless there is still the need to reduce the content and the need of processing the data. We discuss the proposals and solutions for dynamic reduction of the transmitted content. For that, device specific properties are taken into account, as much as for the aim to reduce the need of processing power at the client side to be able to display the 3D (virtual reality) data. Therefore, well known technologies, e.g. data compression are combined with new developed ideas to reach the goal of adaptive content transmission. To achieve a device dependant reduction of processing power the data have to be preprocessed at the server side or the server even has to take over functionality of weak mobile devices.