13,015 research outputs found
Meta-heuristic algorithms for optimized network flow wavelet-based image coding
Optimal multipath selection to maximize the received multiple description coding (MDCs) in a lossy network model is proposed. Multiple description scalar quantization (MDSQ) has been applied to the wavelet coefficients of a color image to generate the MDCs which are combating transmission loss over lossy networks. In the networks, each received description raises the reconstruction quality of an MDC-coded signal (image, audio or video). In terms of maximizing the received descriptions, a greater number of optimal routings between source and destination must be obtained. The rainbow network flow (RNF) collaborated with effective meta-heuristic algorithms is a good approach to resolve it. Two meta-heuristic algorithms which are genetic algorithm (GA) and particle swarm optimization (PSO) have been utilized to solve the multi-objective optimization routing problem for finding optimal routings each of which is assigned as a distinct color by RNF to maximize the coded descriptions in a network model. By employing a local search based priority encoding method, each individual in GA and particle in PSO is represented as a potential solution. The proposed algorithms are compared with the multipath Dijkstra algorithm (MDA) for both finding optimal paths and providing reliable multimedia communication. The simulations run over various random network topologies and the results show that the PSO algorithm finds optimal routings effectively and maximizes the received MDCs with assistance of RNF, leading to reduce packet loss and increase throughput
Exact Cover with light
We suggest a new optical solution for solving the YES/NO version of the Exact
Cover problem by using the massive parallelism of light. The idea is to build
an optical device which can generate all possible solutions of the problem and
then to pick the correct one. In our case the device has a graph-like
representation and the light is traversing it by following the routes given by
the connections between nodes. The nodes are connected by arcs in a special way
which lets us to generate all possible covers (exact or not) of the given set.
For selecting the correct solution we assign to each item, from the set to be
covered, a special integer number. These numbers will actually represent delays
induced to light when it passes through arcs. The solution is represented as a
subray arriving at a certain moment in the destination node. This will tell us
if an exact cover does exist or not.Comment: 20 pages, 4 figures, New Generation Computing, accepted, 200
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Leadership for resilient urban systems : two cases in Asheville, NC
The role of leadership in the resilience of urban systems is poorly understood. Leadership can be thought of as a complex practice, where the functions of leadership emerge from the relationships amongst actors, systems and institutions. There are five theorized functions of Complexity Leadership: Community Building, Information Gathering, Information Using, Generative and Administrative. The purpose of this dissertation was to explore the connection, if any, between Complexity Leadership and the resilience of urban systems.Â
This was explored in the context of two cases in Asheville, NC: the Residents' Council of Public Housing of Asheville and Rainbow Community School. The Residents' Council is a non profit that represents residents’ interests; Public Housing in Asheville is a typical for a 100k small city. The case documents some of the Residents' Council's attempt to adopt Dynamic Governance, a set of self-organizing governance practices. Rainbow Community School is a private k-8 school, recognized internationally as an Ashoka Change-Maker School for its innovative model of education. Data was collected through a hybrid of traditional ethnographic techniques and distributed ethnography. Data was analyzed inductively, using a combination of qualitative analysis and set theoretic analysis.
The research generated findings of three kinds. First, complexity leadership was necessary but not sufficient to account for the observed resilience qualities. To explain the observed coordination across other functions and capacity to engage with mystery , this research theorizes an additional function of Complexity Leadership—a Spiritual function. Second, individual strategic leadership played a role in fostering resilience through strengthening weak functions of complexity leadership. Third, resilience qualities emerged over time through the process of Panarchy. Spiritual leadership plays a role in fostering Panarchy through creating conditions for cross-scale resonance. The dissertation closes with the contributions of this research to theory, practice, and methods for research in complex urban systems.Community and Regional Plannin
Wireless Inter-Session Network Coding - An Approach Using Virtual Multicasts
This paper addresses the problem of inter-session network coding to maximize throughput for multiple communication sessions in wireless networks. We introduce virtual multicast connections which can extract packets from original sessions and code them together. Random linear network codes can be used for these virtual multicasts. The problem can be stated as a flow-based convex optimization problem with side constraints. The proposed formulation provides a rate region which is at least as large as the region without inter-session network coding. We show the benefits of our technique for several scenarios by means of simulation.United States. Defense Advanced Research Projects Agency (Subcontract 18870740-37362-C
Towards adaptive multi-robot systems: self-organization and self-adaptation
Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible
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