145 research outputs found

    A Study on TPMS Pre-warning Threshold Algorithm Based on Multi-sensor Data Fusion

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    In order to improve the precision of the tire pressure monitoring system, the Bayes method is applied to establish its mathematical model of multi-sensor information fusion. The temperature and pressure in the tire, which are the complementary information, are integrated in the model through analyzing the mechanism of tire burst generated by temperature and pressure. Through the temperature compensation of tire burst pressure threshold value, the false alarm and false negative are avoided to the hilt. The experimental results show that compared with the traditional TPMS, the accuracy of the measuring results of this model is improved and thus the system’s monitoring ability is improved so that the traffic safety is guaranteed. DOI: http://dx.doi.org/10.11591/telkomnika.v14i3.7895

    Model and heuristic solutions for the multiple double-load crane scheduling problem in slab yards

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    This article studies a multiple double-load crane scheduling problem in steel slab yards. Consideration of multiple cranes and their double-load capability makes the scheduling problem more complex. This problem has not been studied previously. We first formulate the problem as a mixed-integer linear programming (MILP) model. A two-phase model-based heuristic is then proposed. To solve large problems, a pointer-based discrete differential evolution (PDDE) algorithm was developed with a dynamic programming (DP) algorithm embedded to solve the one-crane subproblem for a fixed sequence of tasks. Instances of real problems are collected from a steel company to test the performance of the solution methods. The experiment results show that the model can solve small problems optimally, and the solution greatly improves the schedule currently used in practice. The two-phase heuristic generates near-optimal solutions, but it can still only solve comparatively modest problems within reasonable (4 h) computational timeframes. The PDDE algorithm can solve large practical problems relatively quickly and provides better results than the two-phase heuristic solution, demonstrating its effectiveness and efficiency and therefore its suitability for practical use

    Competitive two-agent scheduling with deteriorating jobs on a single parallel-batching machine

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    We consider a scheduling problem in which the jobs are generated by two agents and have time-dependent proportional-linear deteriorating processing times. The two agents compete for a common single batching machine to process their jobs, and each agent has its own criterion to optimize. The jobs may have identical or different release dates. The batching machine can process several jobs simultaneously as a batch and the processing time of a batch is equal to the longest of the job processing times in the batch. The problem is to determine a schedule for processing the jobs such that the objective of one agent is minimized, while the objective of the other agent is maintained under a fixed value. For the unbounded model, we consider various combinations of regular objectives on the basis of the compatibility of the two agents. For the bounded model, we consider two different objectives for incompatible and compatible agents: minimizing the makespan of one agent subject to an upper bound on the makespan of the other agent and minimizing the number of tardy jobs of one agent subject to an upper bound on the number of tardy jobs of the other agent. We analyze the computational complexity of various problems by either demonstrating that the problem is intractable or providing an efficient exact algorithm for the problem. Moreover, for certain problems that are shown to be intractable, we provide efficient algorithms for certain special cases

    Signature of coexistence of superconductivity and ferromagnetism in two-dimensional NbSe\u3csub\u3e2\u3c/sub\u3e triggered by surface molecular adsorption

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    Ferromagnetism is usually deemed incompatible with superconductivity. Consequently, the coexistence of superconductivity and ferromagnetism is usually observed only in elegantly designed multi-ingredient structures in which the two competing electronic states originate from separate structural components. Here we report the use of surface molecular adsorption to induce ferromagnetism in two-dimensional superconducting NbSe2, representing the freestanding case of the coexistence of superconductivity and ferromagnetism in one two-dimensional nanomaterial. Surface-structural modulation of the ultrathin superconducting NbSe2 by polar reductive hydrazine molecules triggers a slight elongation of the covalent Nb–Se bond, which weakens the covalent interaction and enhances the ionicity of the tetravalent Nb with unpaired electrons, yielding ferromagnetic ordering. The induced ferromagnetic momentum couples with conduction electrons generating unique correlated effects of intrinsic negative magnetoresistance and the Kondo effect. We anticipate that the surface molecular adsorption will be a powerful tool to regulate spin ordering in the two-dimensional paradigm

    A Study on TPMS Pre-warning Threshold Algorithm Based on Multi-sensor Data Fusion

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    A novel clor image fragile watermarking based on the extended channel

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    The Research of the Model of Communication System Depending on the Queuing Theory

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