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The idea of this game is to use a flashcard system to create a short story in a foreign language. The story is developed by a group of people by exchanging sentences via a flashcard system. This way, people can learn from each other without fear of making mistakes because the group members are anonymous.
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.
To provide proper solutions to the problem of device dependant content delivery, a fine categorization of the application target devices is needed. Earlier attempts provided two different presentations for desktop and mobile platforms. The mobile platform presentation was divided into three categories, based on a general classification (PDA, Smartphone or mobile phone). In order to improve the on mobile device presentation a finer categorization is introduced. In this paper, our focus is to clarify the concept of this more flexible presentation module, in which the delivered content depends on the efficiency of the device based on a selected set of capabilities.
Signal detection and bandwidth estimation, also known as channel segmentation or information channel estimation, is a perpetual topic in communication systems. In the field of radio monitoring this issue is extremely challenging, since unforeseeable effects like fading occur accidentally. In addition, most radio monitoring devices normally scan a wide frequency range of several hundred MHz and have to detect a multitude of different signals, varying in signal power, bandwidth and spectral shape. Since narrowband sensing techniques cannot be directly applied, most radio monitoring devices use Nyquist wideband sensing to discover the huge frequency range. In practice, sensing is normally conducted by an FFT sweep spectrum analyzer that delivers the power spectral density (PSD) values to the radio monitoring system. The channel segmentation is the initial step of a comprehensive signal analysis in a radio monitoring system based on the PSD values. In this paper, a novel approach for channel segmentation is presented that is based on a quantization and a histogram evaluation of the measured PSD. It will be shown that only the combination of both evaluations will lead to an successful automatic channel segmentation. The performance of the proposed algorithm is shown in a real radio monitoring szenario.
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.
The iSign project started in 2000 as a web-based laboratory setting for students of electrical engineering. In the meantime it has broadened into a heterogeneous learning environment offering learning material, adaptive user settings and access to a simulation tool. All these offerings can be accessed via web and wireless by different clients, such as PCs, PDAs and mobile phones. User adaptive systems offer unique and personalised environment for every learner and therefore are a very important aspect of modern e-learning systems. The iSign project aims to personalise the content structure based on the learner's behaviour, content pattern, policies, and system environment. The second aspect of the recent research and development within this project is the generation of suitable content and presentation for different clients. This generation is based additionally on the user preferences in order to obtain the desirable presentation for a given device. New, valuable features are added to the mobile application, empowering the user not only to control the simulation process with his mobile device but also to input data, view the simulation's output and evaluate the results. Experiences with students have helped to improve functionality and look-and-feel whilst using the iSign system. Our goal is to provide unconstrained, continuous and personalised access to the laboratory settings and learning material everywhere and at anytime with different devices.
The concept of m-learning which differs from other forms of e-learning covers a wide range of possibilities opened up by the convergence of new mobile technologies, wireless communication structure and distance learning development. This process of converging has launched some new goals to support m-learning where heterogeneity of devices, their operating systems (Linux, Windows, Symbian, Android etc) and supported markup languages (WML, XHTML etc), adaptive content, preferences or characteristics of user have become some of the major problems to be solved. To facilitate the learning process even more and to establish literally anytime anywhere learning, learning material/content should be available to the user always even if the user is in offline. Multiple devices used by the same user should also be synchronized among themselves and with server to provide updated learning content and to give a freedom to the user to choose any device as per his/her convenience. In this paper software architecture has been proposed to solve these problems and has been implemented by using a multidimensional flashcard learning system which synchronizes among all the devices that are being used by the user.
Since cabling is very complex and often causes reliability problems in aircrafts new approaches which base on wireless technologies are highly desired. In this paper an innovative communication system is proposed that uses the essential elements of the airframe for data transfer. The communication is based on the wireless standard for Digital Video Broadcasting (DVB) and enables high data rates, which are required for the in-flight entertainment system as an example of use.
We consider the local group of agents for exchanging the time-series data value and computing the approximation of the mean value of all agents. An agent represented by a node knows all local neighbor nodes in the same group. The node has the contact information of other nodes in other groups. The nodes interact with each other in synchronous rounds to exchange the updated time-series data value using the random call communication model. The amount of data exchanged between agent-based sensors in the local group network affects the accuracy of the aggregation function results. At each time step, the agent-based sensor can update the input data value and send the updated data value to the group head node. The group head node sends the updated data value to all group members in the same group. Grouping nodes in peer-to-peer networks show an improvement in Mean Squared Error (MSE).