63 research outputs found

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    This paper is concerned with the H∞ filtering problem for networked systems with bounded measurement missing. A switched linear system model is proposed to describe the considered filtering error system. A sufficient condition is derived for the filtering error system to be exponentially stable and achieve a prescribed H∞ filtering performance level. The obtained condition establishes quantitative relations among the H∞ performance level and two parameters characterizing the measurement missing, namely, the measurement missing rate bound and the maximal number of consecutive measurement missing. A convex optimization problem is presented to design the linear H∞ filters. Finally, an illustrative example is given to show the effectiveness of the proposed results

    COLTRANE: ConvolutiOnaL TRAjectory NEtwork for Deep Map Inference

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    The process of automatic generation of a road map from GPS trajectories, called map inference, remains a challenging task to perform on a geospatial data from a variety of domains as the majority of existing studies focus on road maps in cities. Inherently, existing algorithms are not guaranteed to work on unusual geospatial sites, such as an airport tarmac, pedestrianized paths and shortcuts, or animal migration routes, etc. Moreover, deep learning has not been explored well enough for such tasks. This paper introduces COLTRANE, ConvolutiOnaL TRAjectory NEtwork, a novel deep map inference framework which operates on GPS trajectories collected in various environments. This framework includes an Iterated Trajectory Mean Shift (ITMS) module to localize road centerlines, which copes with noisy GPS data points. Convolutional Neural Network trained on our novel trajectory descriptor is then introduced into our framework to detect and accurately classify junctions for refinement of the road maps. COLTRANE yields up to 37% improvement in F1 scores over existing methods on two distinct real-world datasets: city roads and airport tarmac.Comment: BuildSys 201

    A Lifetime Optimization Algorithm Limited by Data Transmission Delay and Hops for Mobile Sink-Based Wireless Sensor Networks

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    To improve the lifetime of mobile sink-based wireless sensor networks and considering that data transmission delay and hops are limited in actual system, a lifetime optimization algorithm limited by data transmission delay and hops (LOA_DH) for mobile sink-based wireless sensor networks is proposed. In LOA_DH, some constraints are analyzed, and an optimization model is proposed. Maximum capacity path routing algorithm is used to calculate the energy consumption of communication. Improved genetic algorithm which modifies individuals to meet all constraints is used to solve the optimization model. The optimal solution of sink node’s sojourn grid centers and sojourn times which maximizes network lifetime is obtained. Simulation results show that, in three node distribution scenes, LOA_DH can find the movement solution of sink node which covers all sensor nodes. Compared with MCP_RAND, MCP_GMRE, and EASR, the solution improves network lifetime and reduces average amount of node discarded data and average energy consumption of nodes

    Do Honored Cities Achieve a Sustainable Development? A Quasi-Natural Experimental Study Based on “National Civilized City” Campaign in China

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    As a new model of urban governance with Chinese characteristics, the national honored cities from city evaluation competitions, represented by the “National Civilized City” campaign, has always been popular among Chinese cities. Can the honored cities of the campaigns achieve sustainable development, and how? Based on the five concepts of sustainable development, which are innovation, coordination, green, openness and sharing, this study sets up a comprehensive index to measure the sustainability of the growth of a city. Then, the data of 242 Chinese cities from 2011 to 2019 and the difference-in-differences (DID) approach are used to evaluate the impacts of the Civilized City honored in the campaigns on the sustainability of growth. The results show that: (1) the “Civilized City” honor promotes sustainable development in Chinese cities; (2) the mechanism analysis shows that the “Civilized City” honor contributes to the sustainability of growth by effectively promoting the level of industrial agglomeration in cities; (3) further heterogeneity analysis shows that the effect of the “Civilized City” honor on the sustainability of growth varies by city size, the administrative level and the location of the city. By providing the evidence of economic effects of the “Civilized City” honor, this research rationalizes the city campaigns run by the Chinese government and provides important enlightenment for the continuous improvement of the selection mechanism of the national honored cities to promote sustainable development

    An Improved Feature Parameter Extraction Algorithm of Composite Detection Method Based on the Fusion Theory

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    An improved feature parameter extraction algorithm is proposed in this study to solve the problem of quantitative detection of subsurface defects. Firstly, the common feature parameters from the differential signal of pulsed eddy current and ultrasonic are extracted in time domain and frequency domain. Then, the dispersion model and ReliefF model are established to determine the weights of each parameter. Finally, the weights from the two different algorithms are fused by the D-S evidence theory to determine feature parameters. Compared with the PCA feature parameter algorithm from the pulsed eddy current or ultrasonic, the experiment results show the feature parameters extracted by the algorithm proposed in this paper are more effective in quantitative detection of subsurface defects. It will lead to high accuracy in the subsurface defections

    Maximizing Lifetime of Wireless Sensor Networks with Mobile Sink Nodes

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    In order to maximize network lifetime and balance energy consumption when sink nodes can move, maximizing lifetime of wireless sensor networks with mobile sink nodes (MLMS) is researched. The movement path selection method of sink nodes is proposed. Modified subtractive clustering method, k-means method, and nearest neighbor interpolation method are used to obtain the movement paths. The lifetime optimization model is established under flow constraint, energy consumption constraint, link transmission constraint, and other constraints. The model is solved from the perspective of static and mobile data gathering of sink nodes. Subgradient method is used to solve the lifetime optimization model when one sink node stays at one anchor location. Geometric method is used to evaluate the amount of gathering data when sink nodes are moving. Finally, all sensor nodes transmit data according to the optimal data transmission scheme. Sink nodes gather the data along the shortest movement paths. Simulation results show that MLMS can prolong network lifetime, balance node energy consumption, and reduce data gathering latency under appropriate parameters. Under certain conditions, it outperforms Ratio_w, TPGF, RCC, and GRND

    Design of Building Monitoring Systems Based on Wireless Sensor Networks*

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    Wireless Sensor Network provides a potential technique for monitoring the indoor environment. This paper presents a Building Monitoring system based on Wireless Sensor Networks. A clustering-based network specified for building monitoring is proposed, which is inspired by LEACH (Low Energy Adaptive Cluster Hierarchy) method. Further, two key ideas are used to implement the clustering-based network. First, the configuration module of building management software is used to conduct all nodes in a room forming a local cluster. This cluster formation method does not consume node energy. Second, because cluster-heads cannot directly transmit packets to the sink node due to limited wireless communication range, the cluster-head communications are represented by a multi-hop tree rooted at the sink node. The experiment has been mad
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