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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.
Mobile learning (m-learning) can be considered as a new paradigm of e-learning. The developed solution enables the presentation of animations and 3D virtual reality (VR) on mobile devices and is well suited for mobile learning. Difficult relations in physics as well as intricate experiments in optics can be visualised on mobile devices without need for a personal computer. By outsourcing the computational power to a server, the coverage is worldwide.
The mobile devices related industries are subject to rapid change, driven by technological advances and dynamic consumer behaviour. Hence, the understanding of the mobile devices markets is an important step in the analysis phase of mobile applications development. In this paper, a brief description of the different markets is introduced followed by an analysis of the main features of the markets leaders' devices which are important in the development process of mobile web applications. Finally, approaches are proposed to deal with the mobile devices diversity.
This paper explores the potential of an m-learning environment by introducing the concept of mLab, a remote laboratory environment accessible through the use of handheld devices.
We are aiming to enhance the existing e-learning platform and internet-assisted laboratory settings, where students are offered in-depth tutoring, by providing compact tuition and tools for controlling simulations that are made available to learners via handheld devices. In this way, students are empowered by having access totheir simulations from any place and at any time.
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.
Energy management in distribution grids is one of the key challenges that needs to be overcome to increase the share of fluctuating renewable energies. Current control systems for energy management mainly demonstrate centralized- or decentralized-hierarchical control structures. Very few systems manifest a fully decentralized multiagent-based control structure. Multiagent-based control systems promise to be an advantageous approach for the future distributed energy supply system because no central control entity is necessary, which eases parameterization in case of grid topology changes, and the agents are more stable against failures and changes of control topologies. Research is necessary to prove these benefits. In this study, we introduce a design of a multiagent-based voltage control system for low-voltage grids. In detail we introduce cooperative decision-making processes and software solutions that allow the agents to perceive and control their environment, the agent-discovery and localization in different types of communication networks, agent-to-agent communication, and the integration of the multiagent system in existing grid-control infrastructures. Furthermore, the study proposes how different existing technologies can be combined into an applicable multiagent-based voltage control system: the Java/OSGi-based OpenMUC framework allows a generic field–device interaction; peer-to-peer discovery and session establishment functionalities are combined with the agent communication defined by the Foundation for Intelligent Physical Agents (FIPA). The ripple control-signal technology is applied as a fallback communication between the agent and a central grid-control center.
Smoothie: a solution for device and content independent applications including 3D imaging as content
(2014)
Network landscape of recent time contains many different network technologies, a wide range of end-devices with a large scale of capabilities and power, and an immense quantity of information represented in different data formats. Research on 3D imaging, virtual reality and holographic techniques will result in new user interfaces (UI) for mobile devices and will increase their diversity and variety. A lot of effort is being made in order to establish open, scalable and seamless integration of various technologies and content presentation for different devices including those that are mobile, considering the individual situation of the end user. Till today the research is going on in different parts of the world but the task is not completed yet. The goal of this research work is to find a way to solve the above stated problems by investigating system architectures to provide unconstrained, continuous and personalized access to the content and interactive applications everywhere and at anytime with different devices. As a Solution of the problem considered, a new architecture named “Smoothie” is proposed.
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.