For transmission of multimedia over 3G wireless networks, H.264/AVC represents a major step forward in the development of video coding standards. In this paper, firstly, the authors briefly introduce a overview of H.2...
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Terrain LOD algorithm is a dynamic and local dough sheet subduction algorithm. On the basis of the research on traditional quadtree algorithm, this paper proposed a new terrain LOD algorithm using quadtree. On deviati...
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The ambiguity and complexity of medical cerebrovascular image makes the skeleton gained by conventional skeleton algorithm discontinuous, which is sensitive at the weak edges, with poor robustness and too many burrs. ...
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This paper proposed a method for entity answer extraction, which examined three levels of relevance, including document, passage and entity. The entity answer extraction system and homepage recognition are also descri...
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In this work, we present a monitor and rescue system utilizing hybrid networks which is a integration of stationary sensor networks and mobile sensor networks: stationary sensor networks comprised of large numbers of ...
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In this work, we present a monitor and rescue system utilizing hybrid networks which is a integration of stationary sensor networks and mobile sensor networks: stationary sensor networks comprised of large numbers of small, simple, and inexpensive wireless sensors, and the mobile sensor network contains a set of mobile sensors (robots). The static sensors in our network have “monitoring” ability, i.e., any activated static sensor can detect the event as long as its sensing range intersects the event region. And the mobile sensors have “moving” and “rescuing” ability, e.g., they can move toward the event region with limited speed and further perform certain rescuing/processing operations on the event. We can consider the event as a hazard, e.g., wild fire, and the mobile sensors as fireman robots. As soon as the fire is detected by the static sensors, the fireman robots are expected to move from its initial location to the hazard region within minimum latency. We define the reaction delay of the system as the delay from the occurrence of event till at least one mobile sensor reaches the event. In order to satisfy certain reaction delay requirement while minimizing the total cost, we propose a number of deployment strategies for the stationary sensor network and mobile sensor network respectively. We further design a random wake-up scheduling for the static sensors for the sake of energy efficiency. Finally, we propose a pure distributed motion strategy for mobile sensors without reliance on localization services such as GPS, focusing on simple algorithms for distributed decision making and information propagation. We demonstrate the efficacy of our system in simulation, providing empirical results.
The benefits of using mobile sink to prolong sensor network lifetime have been well recognized. However, few provably theoretical results remain are developed due to the complexity caused by time-dependent network top...
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The benefits of using mobile sink to prolong sensor network lifetime have been well recognized. However, few provably theoretical results remain are developed due to the complexity caused by time-dependent network topology. In this work, we investigate the optimum routing strategy for the static sensor network. We further propose a number of motion stratifies for the mobile sink(s) to gather real time data from static sensor network, with the objective to maximize the network lifetime. Specially, we consider a more realistic model where the moving speed and path for mobile sinks are constrained. Our extensive experiments show that our scheme can significantly prolong entire network lifetime and reduce delivery delay.
By using BP artificial nerve network's error reversion transmission. Summing up various data of comprehensive logging can solve the problem of low accurate rate for identifying oil, gas, water zones. The software ...
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By using BP artificial nerve network's error reversion transmission. Summing up various data of comprehensive logging can solve the problem of low accurate rate for identifying oil, gas, water zones. The software provides nerve network reservoir interpretation model by studying and training the initial data of tested oil. Practice proves the overall coincidence rate of interpretation reaches 97%. It can more efficiently reflects logging technique's advantage of wellsite quick evaluation oil, gas, water zones. The application in this technique improves the level of logging data interpretation and evaluation.
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