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  • 1
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    Detecting Local Community Structures in Networks Based on Boundary Identification (2014)
    Hindawi
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    Publication Date: 2014-09-02
    Description: Detecting communities within networks is of great importance to understand the structure and organizations of real-world systems. To this end, one of the major challenges is to find the local community from a given node with limited knowledge of the global network. Most of the existing methods largely depend on the starting node and require predefined parameters to control the agglomeration procedure, which may cause disturbing inference to the results of local community detection. In this work, we propose a parameter-free local community detecting algorithm, which uses two self-adaptive phases in detecting the local community, thus comprehensively considering the external and internal link similarity of neighborhood nodes in each clustering iteration. Based on boundary nodes identification, our self-adaptive method can effectively control the scale and scope of the local community. Experimental results show that our algorithm is efficient and well-behaved in both computer-generated and real-world networks, greatly improving the performance of local community detection in terms of stability and accuracy.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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  • 2
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    Study on the Thick-Walled Pipe Ultrasonic Signal Enhancement of Modified S-Transform and Singular Value Decomposition (2015)
    Hindawi
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    Publication Date: 2015-01-14
    Description: When detecting the ultrasonic flaw of thick-walled pipe, the flaw echo signals are often interrupted by scanning system frequency and background noise. In particular when the thick-walled pipe defect is small, echo signal amplitude is often drowned in noise signal and affects the extraction of defect signal and the position determination accuracy. This paper presents the modified S-transform domain singular value decomposition method for the analysis of ultrasonic flaw echo signals. By changing the scale rule of Gaussian window functions with S-transform to improve the time-frequency resolution. And the paper tries to decompose the singular value decomposition of time-frequency matrix after the S-transform to determine the singular entropy of effective echo signal and realize the adaptive filter. Experiments show that, using this method can not only remove high frequency noise but also remove the low frequency noise and improve the signal-to-noise ratio of echo signal.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 3
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    Dominant Large-Scale Atmospheric Circulation Systems for the Extreme Precipitation over the Western Sichuan Basin in Summer 2013 (2015)
    Hindawi
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    Publication Date: 2015-08-26
    Description: The western Sichuan Basin (WSB) is a rainstorm center influenced by complicated factors such as topography and circulation. Based on multivariable empirical orthogonal function technique for extreme precipitation processes (EPP) in WSB in 2013, this study reveals the dominant circulation patterns. Results indicate that the leading modes are characterized by “Saddle” and “Sandwich” structures, respectively. In one mode, a TC from the South China Sea (SCS) converts into the inverted trough and steers warm moist airflow northward into the WSB. At the same time, WPSH extends westward over the Yangtze River and conveys a southeasterly warm humid flow. In the other case, WPSH is pushed westward by TC in the Western Pacific and then merges with an anomalous anticyclone over SCS. The anomalous anticyclone and WPSH form a conjunction belt and convey the warm moist southwesterly airflow to meet with the cold flow over the WSB. The configurations of WPSH and TC in the tropic and the blocking and trough in the midhigh latitudes play important roles during the EPPs over the WSB. The persistence of EPPs depends on the long-lived large-scale circulation configuration steady over the suitable positions.
    Print ISSN: 1687-9309
    Electronic ISSN: 1687-9317
    Topics: Geosciences , Physics
    Published by Hindawi
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  • 4
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    Evaluation of Optimal Pore Size of (3-Aminopropyl)triethoxysilane Grafted MCM-41 for Improved CO2 Adsorption (2015)
    Hindawi
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    Publication Date: 2015-10-02
    Description: An array of new MCM-41 with substantially larger average pore diameters was synthesized through adding 1,3,5-trimethylbenzene (TMB) as the swelling agent to explore the effect of pore size on final adsorbent properties. The pore expanded MCM-41 was also grafted with (3-Aminopropyl)triethoxysilane (APTES) to determine the optimal pore size for CO2 adsorption. The pore-expanded mesoporous MCM-41s showed relatively less structural regularity but significant increments of pore diameter (4.64 to 7.50 nm); the fraction of mesopore volume also illustrated an increase. The adsorption heat values were correlated with the order of the adsorption capacities for pore expanded MCM-41s. After amine functionalization, the adsorption capacities and heat values showed a significant increase. APTES-grafted pore-expanded MCM-41s depicted a high potential for CO2 capture regardless of the major drawback of the high energy required for regeneration.
    Print ISSN: 2090-9063
    Topics: Chemistry and Pharmacology
    Published by Hindawi
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  • 5
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    State-Feedback Control for LPV System Using T-S Fuzzy Linearization Approach (2013)
    Hindawi
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    Publication Date: 2013-10-01
    Description: This paper discusses the linear parameter varying (LPV) gain scheduling control problem based on the Takagi-Sugeno (T-S) fuzzy linearization approach. Firstly, the affine nonlinear parameter varying (ANPV) description of a class of nonlinear dynamic processes is defined; that is, at any scheduling parameter, the corresponding system is affine nonlinear as usual. For such a class of ANPV systems, a kind of developed T-S fuzzy modeling procedure is proposed to deal with the nonlinearity, instead of the traditional Jacobian linearization approach. More concretely, the evaluation system for the approximation ability of the novelly developed T-S fuzzy modeling procedure is established. Consequently, the LPV T-S fuzzy system is obtained which can approximate the ANPV system with required accuracy. Secondly, the notion of piecewise parameter-dependent Lyapunov function is introduced, and then the stabilization problem and the state-feedback control problem of the LPV T-S fuzzy system are studied. The sufficient conditions are given in linear matrix inequalities (LMIs) form. Finally, a numerical example is provided to demonstrate the availability of the above approaches. The simulation results show the high approximation accuracy of the LPV T-S fuzzy system to the ANPV system and the effectiveness of the LPV T-S fuzzy gain scheduling control.
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    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 6
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    Nonlinear Forced Vibration of a Viscoelastic Buckled Beam with 2 : 1 Internal Resonance (2014)
    Hindawi
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    Publication Date: 2014-01-09
    Description: Nonlinear dynamics of a viscoelastic buckled beam subjected to primary resonance in the presence of internal resonance is investigated for the first time. For appropriate choice of system parameters, the natural frequency of the second mode is approximately twice that of the first providing the condition for 2 : 1 internal resonance. The ordinary differential equations of the two mode shapes are established using the Galerkin method. The problem is replaced by two coupled second-order differential equations with quadratic and cubic nonlinearities. The multiple scales method is applied to derive the modulation-phase equations. Steady-state solutions of the system as well as their stability are examined. The frequency-amplitude curves exhibit the steady-state response in the directly excited and indirectly excited modes due to modal interaction. The double-jump, the saturation phenomenon, and the nonperiodic region phenomena are observed illustrating the influence of internal resonance. The validity range of the analytical approximations is assessed by comparing the analytical approximate results with a numerical solution by the Runge-Kutta method. The unstable regions in the internal resonance are explored via numerical simulations.
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    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
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  • 7
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    Existence and Uniqueness of Positive Periodic Solutions for a Delayed Predator-Prey Model with Dispersion and Impulses (2014)
    Hindawi
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    Publication Date: 2014-03-28
    Description: An impulsive Lotka-Volterra type predator-prey model with prey dispersal in two-patch environments and time delays is investigated, where we assume the model of patches with a barrier only as far as the prey population is concerned, whereas the predator population has no barriers between patches. By applying the continuation theorem of coincidence degree theory and by means of a suitable Lyapunov functional, a set of easily verifiable sufficient conditions are obtained to guarantee the existence, uniqueness, and global stability of positive periodic solutions of the system. Some known results subject to the underlying systems without impulses are improved and generalized. As an application, we also give two examples to illustrate the feasibility of our main results.
    Print ISSN: 1110-757X
    Electronic ISSN: 1687-0042
    Topics: Mathematics
    Published by Hindawi
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  • 8
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    The Influence of Climate Factors, Meteorological Conditions, and Boundary-Layer Structure on Severe Haze Pollution in the Beijing-Tianjin-Hebei Region during January 2013 (2014)
    Hindawi
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    Publication Date: 2014-11-18
    Description: The air-pollution episodes in China in January 2013 were the most hazardous in the Beijing-Tianjin-Hebei (BTH) region. PM2.5, AOD, and long-term visibility data, along with various climate and meteorological factors and the boundary-layer structure, were used to investigate the cause of the heavy-haze pollution events in January 2013. The result suggests that unfavorable diffusion conditions (weak surface winds and high humidity) and high primary-pollutant emissions have induced heavy-haze pollution in the BTH region over the past two decades. A sudden stratospheric warming (SSW), weak East Asian winter monsoon, a weak Siberian High, weak meridional circulation, southerly wind anomalies in the lower troposphere, and abnormally weak surface winds and high humidity were responsible for the severe haze pollution events, rather than an abrupt increase in emissions. Heavy/severe haze pollution is associated with orographic wind convergence zones along the Taihang and Yanshan Mountains, slight winds (1.7∼2.1 m/s), and high humidity (70%∼90%), which limits the diffusion of pollutants and facilitates the hygroscopic growth of aerosols. Recirculation and regional transport, along with the poorest diffusion conditions and favorable conditions for hygroscopic growth of aerosols and secondary transformation under the high emission, led to explosive growth and the record high hourly average concentration of PM2.5 in Beijing.
    Print ISSN: 1687-9309
    Electronic ISSN: 1687-9317
    Topics: Geosciences , Physics
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  • 9
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    A Self-Learning Sensor Fault Detection Framework for Industry Monitoring IoT (2013)
    Hindawi
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    Publication Date: 2013-10-22
    Description: Many applications based on Internet of Things (IoT) technology have recently founded in industry monitoring area. Thousands of sensors with different types work together in an industry monitoring system. Sensors at different locations can generate streaming data, which can be analyzed in the data center. In this paper, we propose a framework for online sensor fault detection. We motivate our technique in the context of the problem of the data value fault detection and event detection. We use the Statistics Sliding Windows (SSW) to contain the recent sensor data and regress each window by Gaussian distribution. The regression result can be used to detect the data value fault. Devices on a production line may work in different workloads and the associate sensors will have different status. We divide the sensors into several status groups according to different part of production flow chat. In this way, the status of a sensor is associated with others in the same group. We fit the values in the Status Transform Window (STW) to get the slope and generate a group trend vector. By comparing the current trend vector with history ones, we can detect a rational or irrational event. In order to determine parameters for each status group we build a self-learning worker thread in our framework which can edit the corresponding parameter according to the user feedback. Group-based fault detection (GbFD) algorithm is proposed in this paper. We test the framework with a simulation dataset extracted from real data of an oil field. Test result shows that GbFD detects 95% sensor fault successfully.
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    Topics: Mathematics , Technology
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  • 10
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    Detecting Communities in 2-Mode Networks via Fast Nonnegative Matrix Trifactorization (2015)
    Hindawi
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    Publication Date: 2015-03-03
    Description: With the rapid development of the Internet and communication technologies, a large number of multitype relational networks widely emerge in real world applications. The bipartite network is one representative and important kind of complex networks. Detecting community structure in bipartite networks is crucial to obtain a better understanding of the network structures and functions. Traditional nonnegative matrix factorization methods usually focus on homogeneous networks, and they are subject to several problems such as slow convergence and large computation. It is challenging to effectively integrate the network information of multiple dimensions in order to discover the hidden community structure underlying heterogeneous interactions. In this work, we present a novel fast nonnegative matrix trifactorization (F-NMTF) method to cocluster the 2-mode nodes in bipartite networks. By constructing the affinity matrices of 2-mode nodes as manifold regularizations of NMTF, we manage to incorporate the intratype and intratype information of 2-mode nodes to reveal the latent community structure in bipartite networks. Moreover, we decompose the NMTF problem into two subproblems, which are involved with much less matrix multiplications and achieve faster convergence. Experimental results on synthetic and real bipartite networks show that the proposed method improves the slow convergence of NMTF and achieves high accuracy and stability on the results of community detection.
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    Topics: Mathematics , Technology
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