3 resultados para Classes of Degeneracy

em Instituto Politécnico do Porto, Portugal


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Fractional calculus generalizes integer order derivatives and integrals. Memristor systems generalize the notion of electrical elements. Both concepts were shown to model important classes of phenomena. This paper goes a step further by embedding both tools in a generalization considering complex-order objects. Two complex operators leading to real-valued results are proposed. The proposed class of models generate a broad universe of elements. Several combinations of values are tested and the corresponding dynamical behavior is analyzed.

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Wireless sensor networks (WSNs) emerge as underlying infrastructures for new classes of large-scale networked embedded systems. However, WSNs system designers must fulfill the quality-of-service (QoS) requirements imposed by the applications (and users). Very harsh and dynamic physical environments and extremely limited energy/computing/memory/communication node resources are major obstacles for satisfying QoS metrics such as reliability, timeliness, and system lifetime. The limited communication range of WSN nodes, link asymmetry, and the characteristics of the physical environment lead to a major source of QoS degradation in WSNs-the ldquohidden node problem.rdquo In wireless contention-based medium access control (MAC) protocols, when two nodes that are not visible to each other transmit to a third node that is visible to the former, there will be a collision-called hidden-node or blind collision. This problem greatly impacts network throughput, energy-efficiency and message transfer delays, and the problem dramatically increases with the number of nodes. This paper proposes H-NAMe, a very simple yet extremely efficient hidden-node avoidance mechanism for WSNs. H-NAMe relies on a grouping strategy that splits each cluster of a WSN into disjoint groups of non-hidden nodes that scales to multiple clusters via a cluster grouping strategy that guarantees no interference between overlapping clusters. Importantly, H-NAMe is instantiated in IEEE 802.15.4/ZigBee, which currently are the most widespread communication technologies for WSNs, with only minor add-ons and ensuring backward compatibility with their protocols standards. H-NAMe was implemented and exhaustively tested using an experimental test-bed based on ldquooff-the-shelfrdquo technology, showing that it increases network throughput and transmission success probability up to twice the values obtained without H-NAMe. H-NAMe effectiveness was also demonstrated in a target tracking application with mobile robots - over a WSN deployment.

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More than ever, the economic globalization is creating the need to increase business competitiveness. Lean manufacturing is a management philosophy oriented to the elimination of activities that do not create any type of value and are thus considered a waste. One of the main differences from other management philosophies is the shop-floor focus and the operators' involvement. Therefore, the training of all organization levels is crucial for the success of lean manufacturing. Universities should also participate actively in this process by developing students' lean management skills and promoting a better and faster integration of students into their future organizations. This paper proposes a single realistic manufacturing platform, involving production and assembly operations, to learn by playing many of the lean tools such as VSM, 5S, SMED, poke-yoke, line balance, TPM, Mizusumashi, plant layout, and JIT/kanban. This simulation game was built in tight cooperation with experienced lean companies under the international program “Lean Learning Academy,”http://www.leanlearningacademy.eu/ and its main aim is to make bachelor and master courses in applied sciences more attractive by integrating classic lectures with a simulated production environment that could result in more motivated students and higher study yields. The simulation game results show that our approach is efficient in providing a realistic platform for the effective learning of lean principles, tools, and mindset, which can be easily included in course classes of less than two hours.