28 research outputs found

    Design and Implementation of a Wireless Sensor Network for Smart Homes

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    Wireless sensor networks (WSNs) have become indispensable to the realization of smart homes. The objective of this paper is to develop such a WSN that can be used to construct smart home systems. The focus is on the design and implementation of the wireless sensor node and the coordinator based on ZigBee technology. A monitoring system is built by taking advantage of the GPRS network. To support multi-hop communications, an improved routing algorithm based on the Dijkstra algorithm is presented. Preliminary simulations have been conducted to evaluate the performance of the algorithm.Comment: International Workshop on Mobile Cyber-Physical Systems (MobiCPS 2010), in conjunction with UIC2010, IEEE, Xi'an, China, 26 - 29 October, 201

    A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model

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    A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective

    GLP-1 receptor agonist as a modulator of innate immunity

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    Glucagon-like peptide-1 (GLP-1) is a 30-amino acid hormone secreted by L cells in the distal ileum, colon, and pancreatic α cells, which participates in blood sugar regulation by promoting insulin release, reducing glucagon levels, delaying gastric emptying, increasing satiety, and reducing appetite. GLP-1 specifically binds to the glucagon-like peptide-1 receptor (GLP-1R) in the body, directly stimulating the secretion of insulin by pancreatic β-cells, promoting proliferation and differentiation, and inhibiting cell apoptosis, thereby exerting a glycemic lowering effect. The glycemic regulating effect of GLP-1 and its analogues has been well studied in human and murine models in the circumstance of many diseases. Recent studies found that GLP-1 is able to modulate innate immune response in a number of inflammatory diseases. In the present review, we summarize the research progression of GLP-1 and its analogues in immunomodulation and related signal pathways

    Impact of Brain-Derived Neurotrophic Factor Val66Met Polymorphism on Cortical Thickness and Voxel-Based Morphometry in Healthy Chinese Young Adults

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    BACKGROUND: Following voxel-based morphometry (VBM), brain-derived neurotrophic factor (BDNF) Val66Met polymorphism (rs6265) has been shown to affect human brain morphology in Caucasians. However, little is known about the specific role of the Met/Met genotype on brain structure. Moreover, the relationship between BDNF Val66Met polymorphism and Chinese brain morphology has not been studied. METHODOLOGY/PRINCIPAL FINDINGS: The present study investigated brain structural differences among three genotypes of BDNF (rs6265) for the first time in healthy young Chinese adults via cortical thickness analysis and VBM. Brain differences in Met carriers using another grouping method (combining Val/Met and Met/Met genotypes into a group of Met carriers as in most previous studies) were also investigated using VBM. Dual-approach analysis revealed less gray matter (GM) in the frontal, temporal, cingulate and insular cortices in the Met/Met group compared with the Val/Val group (corrected, P<0.05). Areas with less GM in the Val/Met group were included in the Met/Met group. VBM differences in Met carriers were only found in the middle cingulate cortex. CONCLUSIONS/SIGNIFICANCE: The current results indicated a unique pattern of brain morphologic differences caused by BDNF (rs6265) in young Chinese adults, in which the Met/Met genotype markedly affected the frontal, temporal, cingulate, and insular regions. The grouping method with Met carriers was not suitable to detect the genetic effect of BDNF Val66Met polymorphism on brain morphology, at least in the Chinese population, because it may hide some specific roles of Met/Met and Val/Met genotypes on brain structure

    Stability Criterion for Linear Systems with Nonlinear Delayed Perturbations

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    A stability criterion for linear systems with nonlinear time-varying delayed perturbations has been derived in light of Razumikhin-type methods. As the proposed criterion is easily applicable and independent of the delay size, it provides an effective method for the stability analysis of time-delay systems. (C) 1999 Academic Press

    Improved delay time estimation of RC ladder networks

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    An improved delay time bound estimation is given in this paper for an n-cell RC ladder network with capacitive load

    An Improved Sparrow Search Algorithm for the Optimization of Variational Modal Decomposition Parameters

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    Variational modal decomposition (VMD) is frequently employed for both signal decomposition and extracting features; however, the decomposition outcome is influenced by the quantity of intrinsic modal functions (IMFs) and the specific parameter values of penalty factors. To tackle this issue, we propose an algorithm based on the Halton sequence and the Laplace crossover operator for the sparrow search algorithm–VMD (HLSSA-VMD) to fine-tune the parameters of VMD. First, the population initialization by the Halton sequence yields higher-quality initial solutions, which effectively addresses the issue of the algorithm’s sluggish convergence due to overlapping and the lack of diversity of the initial solutions. Second, the introduction of the Laplace crossover operator (LX) to perturb the position of the best individual in each iteration helps to prevent the algorithm from becoming ensnared in a local optimum and improves the convergence speed of the algorithm. Finally, from the simulation of 17 benchmark test functions, we found that the HLSSA exhibited superior convergence accuracy and accelerated convergence pace, as well as better robustness than the particle swarm optimization (PSO) algorithm, the whale optimization algorithm (WOA), the multiverse optimization (MVO) algorithm, and the traditional sparrow search algorithm (SSA). In addition, we verified the effectiveness of the HLSSA-VMD algorithm on two simulated signals and compared it with PSO-VMD, WOA-VMD, MVO-VMD, and SSA-VMD. The experimental findings indicate that the HLSSA-VMD obtains better parameters, confirming the superiority of the algorithm

    Nonlinear MPC using an identified LPV model

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    A method of nonlinear model predictive control based on an identified LPV model is proposed. In process identification, a linear parameter varying (LPV) model approach is used. First, typical working-points are selected and linear models are identified using data sets at various working-points; then the LPV model is identified by interpolating the linear models using total data that include transition test data. Further, nonlinear model predictive control based on the LPV model is proposed. The control action is computed via a multistep linearization method of nonlinear optimization problem. The method uses low cost tests and can reach higher control performance than linear MPC. Simulation studies are used to verify the effectiveness of the method

    A multi-iteration pseudo-linear regression method and an adaptive disturbance model for MPC

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    This paper proposes an MPC method that uses an adaptive disturbance model to improve the accuracy of prediction. In unmeasured disturbance model identification, a novel multi-iteration pseudo-linear regression (MIPLR) method is used which is more accurate and has faster convergence than traditional recursive identification methods. The adaptive disturbance model is used in an MPC scheme for improved performance in disturbance rejection. The method is demonstrated by the simulation of a distillation column and also tested on the real process. The test results show that the proposed MPC scheme can not only increase control performance, but also increase robustness