19 research outputs found
Extending MAM5 Meta-Model and JaCalIVE Framework to Integrate Smart Devices from Real Environments
[EN] This paper presents the extension of a meta-model (MAM5) and a framework based on the model (JaCalIVE) for developing intelligent virtual environments. The goal of this extension is to develop augmented mirror worlds that represent a real and virtual world coupled, so that the virtual world not only reflects the real one, but also complements it. A new component called a smart resource artifact, that enables modelling and developing devices to access the real physical world, and a human in the loop agent to place a human in the system have been included in the meta-model and framework. The proposed extension of MAM5 has been tested by simulating a light control system where agents can access both virtual and real sensor/actuators through the smart resources developed. The results show that the use of real environment interactive elements (smart resource artifacts) in agent-based simulations allows to minimize the error between simulated and real system.This work is partially supported by the TIN2009-13839-C03-01, TIN2011-27652-C03-01, 547CSD2007-00022, COST Action IC0801, FP7-294931 and the FPI grant AP2013-01276 548 awarded to Jaime-Andres Rincon.Rincón Arango, JA.; Poza Luján, JL.; Julian Inglada, VJ.; Posadas Yagüe, JL.; Carrascosa Casamayor, C. (2016). Extending MAM5 Meta-Model and JaCalIVE Framework to Integrate Smart Devices from Real Environments. PLoS ONE. 11(2):1-27. https://doi.org/10.1371/journal.pone.0149665S127112Luck, M., & Aylett, R. (2000). Applying artificial intelligence to virtual reality: Intelligent virtual environments. Applied Artificial Intelligence, 14(1), 3-32. doi:10.1080/088395100117142Barella A, Ricci A, Boissier O, Carrascosa C. MAM5: Multi-Agent Model For Intelligent Virtual Environments. 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Study on Gibbs Optimization-Based Resource Scheduling Algorithm in Data Aggregation Networks
In data aggregation networks (WSNs, ad hoc, mesh, etc.), it is key to schedule the network resources, such as channels and TDMA time slots, to minimize the communication conflict and optimize the network data-gathering performance. In this paper, the resources scheduling problem is formulated as a vertex coloring problem in graph theory. Then, a multi-channel TDMA scheduling algorithm based on the Gibbs optimization is proposed. By defining the Gibbs energy expression according to the objective function of the problem, the joint probability of channel and time slot can be computed for the optimized selection of channels and time slots. This algorithm is low-complexity and its convergence performance can be proven. Experiments with different network parameters demonstrate that the proposed algorithm can reduce the communication conflict, improve the network throughput, and effectively reduce the network transmission delay and scheduling length for the data aggregation networks
Protein Sequence Comparison Based on Physicochemical Properties and the Position-Feature Energy Matrix
© 2017 The Author(s). We develop a novel position-feature-based model for protein sequences by employing physicochemical properties of 20 amino acids and the measure of graph energy. The method puts the emphasis on sequence order information and describes local dynamic distributions of sequences, from which one can get a characteristic B-vector. Afterwards, we apply the relative entropy to the sequences representing B-vectors to measure their similarity/dissimilarity. The numerical results obtained in this study show that the proposed methods leads to meaningful results compared with competitors such as Clustal W
Study on Gibbs Optimization-Based Resource Scheduling Algorithm in Data Aggregation Networks
In data aggregation networks (WSNs, ad hoc, mesh, etc.), it is key to schedule the network resources, such as channels and TDMA time slots, to minimize the communication conflict and optimize the network data-gathering performance. In this paper, the resources scheduling problem is formulated as a vertex coloring problem in graph theory. Then, a multi-channel TDMA scheduling algorithm based on the Gibbs optimization is proposed. By defining the Gibbs energy expression according to the objective function of the problem, the joint probability of channel and time slot can be computed for the optimized selection of channels and time slots. This algorithm is low-complexity and its convergence performance can be proven. Experiments with different network parameters demonstrate that the proposed algorithm can reduce the communication conflict, improve the network throughput, and effectively reduce the network transmission delay and scheduling length for the data aggregation networks
A Path Forming Method for Water Surface Mobile Sink Using Voronoi Diagram and Dominating Set
Experimental investigations on the shear strength and creep properties of soil-rock mixture under freeze-thaw cycles
Explore on the quantitative analysis of specific surface area on sensitivity of polyacrylic acid-based QCM ammonia sensor
A anti-jamming method for satellite navigation system based on multi-objective optimization technique
Glutamylation of an HIV-1 protein inhibits the immune response by hijacking STING
Summary: Cyclic GMP-AMP synthase (cGAS) recognizes Y-form cDNA of human immunodeficiency virus type 1 (HIV-1) and initiates antiviral immune response through cGAS-stimulator of interferon genes (STING)-TBK1-IRF3-type I interferon (IFN-I) signalingcascade. Here, we report that the HIV-1 p6 protein suppresses HIV-1-stimulated expression of IFN-I and promotes immune evasion. Mechanistically, the glutamylated p6 at residue Glu6 inhibits the interaction between STING and tripartite motif protein 32 (TRIM32) or autocrine motility factor receptor (AMFR). This subsequently suppresses the K27- and K63-linked polyubiquitination of STING at K337, therefore inhibiting STING activation, whereas mutation of the Glu6 residue partially reverses the inhibitory effect. However, CoCl2, an agonist of cytosolic carboxypeptidases (CCPs), counteracts the glutamylation of p6 at the Glu6 residue and inhibits HIV-1 immune evasion. These findings reveal a mechanism through which an HIV-1 protein mediates immune evasion and provides a therapeutic drug candidate to treat HIV-1 infection