Mathematical Problems in Engineering The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. Fixed Points and Exponential Stability for Impulsive Time-Delays BAM Neural Networks via LMI Approach and Contraction Mapping Principle Thu, 20 Oct 2016 14:02:05 +0000 The fixed point technique has been employed in the stability analysis of time-delays bidirectional associative memory (BAM) neural networks with impulse. By formulating a contraction mapping in a product space, a new LMI-based exponential stability criterion was derived. Lately, fixed point methods have educed various good results inspiring this work, but those criteria cannot be programmed by a computer. In this paper, LMI conditions of the obtained result can be applicable to computer Matlab LMI toolbox which meets the need of the large-scale calculation in real engineering. Moreover, a numerical example and a comparable table are presented to illustrate the effectiveness of the proposed methods. Ruofeng Rao, Zhilin Pu, Shouming Zhong, and Xinggui Li Copyright © 2016 Ruofeng Rao et al. All rights reserved. Research and Application of Influences of Lateral Pressure Coefficients on the Extension Angle of Coal Cracks Thu, 20 Oct 2016 13:00:07 +0000 Fluid-solid coupling seepage fields are ubiquitous in engineering practices. However, few investigations have been carried out on the rules of crack extension of solids under the effect of fluids. By using the RFPA2D (realistic failure process analysis in 2 dimensions), this research studied the influences of different lateral pressure coefficients on the extension direction and length of coal cracks. Also the result can be proved by fracture mechanics, stress intensity factor theory, and sliding crack theory. On this basis, aiming at a coal mine with the mining depth being over 700 m, the reliability of the above conclusion was further proved by testing the crustal stress at the positions with the buried depth varying from 750 m to 1,300 m. At the same time, in condition of meeting the water pressure required by the crack extension, permeability-increasing radius is selected preferably through AE energy index by simulation of hydraulic fracturing for coal seams under different lateral pressure coefficients, and the gas drainage achieves good effect in engineering practice. Cheng Liu, Shu-gang Li, Song Qin, and Shou-guo Yang Copyright © 2016 Cheng Liu et al. All rights reserved. Structural Parameter Identification of Articulated Arm Coordinate Measuring Machines Thu, 20 Oct 2016 08:47:10 +0000 Precise structural parameter identification of a robotic articulated arm coordinate measuring machine (AACMM) is essential for improving its measuring accuracy, particularly in robotic applications. This paper presents a constructive parameter identification approach for robotic AACMMs. We first develop a mathematical kinematic model of the AACMM based on the Denavit-Hartenberg (DH) approach established for robotic systems. This model is further calibrated and verified via the practical test data. Based on the difference between the calculated coordinates of the AACMM probe via the kinematic model and the given reference coordinates, a parameter identification approach is proposed to estimate the structural parameters in terms of the test data set. The Jacobian matrix is further analyzed to determine the solvability of the identification model. It shows that there are two coupling parameters, which can be removed in the regressor. Finally, a parameter identification algorithm taking the least-square solution of the identification model as the structural parameters by using the obtained poses data is suggested. Practical experiments based on a robotic AACMM test rig are carried out, and the results reveal the effectiveness and robustness of the proposed identification approach. Guanbin Gao, Huaishan Zhang, Xing Wu, and Yu Guo Copyright © 2016 Guanbin Gao et al. All rights reserved. Optimal Preview Control for a Class of Linear Continuous Stochastic Control Systems in the Infinite Horizon Thu, 20 Oct 2016 05:59:54 +0000 This paper discusses the optimal preview control problem for a class of linear continuous stochastic control systems in the infinite horizon, based on the augmented error system method. Firstly, an assistant system is designed and the state equation is translated to the assistant system. Then, an integrator is introduced to construct a stochastic augmented error system. As a result, the tracking problem is converted to a regulation problem. Secondly, the optimal regulator is solved based on dynamic programming principle for the stochastic system, and the optimal preview controller of the original system is obtained. Compared with the finite horizon, we simplify the performance index. We also study the stability of the stochastic augmented error system and design the observer for the original stochastic system. Finally, the simulation example shows the effectiveness of the conclusion in this paper. Jiang Wu, Fucheng Liao, and Jiamei Deng Copyright © 2016 Jiang Wu et al. All rights reserved. Steady-State Thermoelastic Analytical Solutions for Insulated Pipelines Wed, 19 Oct 2016 14:38:06 +0000 A steady-state thermoelastic analytical solution for a multilayer hollow cylinder, composed of an arbitrary number of phases and subject to both radial pressure and temperature gradient, is presented. By assuming each phase to be homogeneous and thermally isotropic and by varying the mechanical and thermal constitutive parameters, a sensitivity analysis has been performed with the aim of finally applying the study to the mechanical behaviour of an industrial pipeline composed of three phases (steel, insulating coating, and polyethylene) under the action of the above-mentioned load conditions. By making reference to a classical Hencky-von Mises criterion, the stress profiles along the thickness of the layers have been carried out, also localizing the onset of plasticity as a function of the temperature variations, material properties, and geometrical features characterizing the composite structure of interest. At the end, some numerical results of practical interest in the engineering applications have been specialized to three different insulated coating materials (expanded polyurethane, laminate glass, and syntactic foam), to highlight the cases in which thermal properties and loads can significantly interfere with the mechanical response in pipes, in terms of stresses, in this way suggesting possible strategies for avoiding unexpected failure and supporting the optimal structural design of these systems. M. Fraldi, L. Esposito, F. Carannante, A. Cutolo, and L. Nunziante Copyright © 2016 M. Fraldi et al. All rights reserved. Salient Region Detection by Fusing Foreground and Background Cues Extracted from Single Image Wed, 19 Oct 2016 08:47:19 +0000 Saliency detection is an important preprocessing step in many application fields such as computer vision, robotics, and graphics to reduce computational cost by focusing on significant positions and neglecting the nonsignificant in the scene. Different from most previous methods which mainly utilize the contrast of low-level features, various feature maps are fused in a simple linear weighting form. In this paper, we propose a novel salient object detection algorithm which takes both background and foreground cues into consideration and integrate a bottom-up coarse salient regions extraction and a top-down background measure via boundary labels propagation into a unified optimization framework to acquire a refined saliency detection result. Wherein the coarse saliency map is also fused by three components, the first is local contrast map which is in more accordance with the psychological law, the second is global frequency prior map, and the third is global color distribution map. During the formation of background map, first we construct an affinity matrix and select some nodes which lie on border as labels to represent the background and then carry out a propagation to generate the regional background map. The evaluation of the proposed model has been implemented on four datasets. As demonstrated in the experiments, our proposed method outperforms most existing saliency detection models with a robust performance. Qiangqiang Zhou, Weidong Zhao, Lin Zhang, and Zhicheng Wang Copyright © 2016 Qiangqiang Zhou et al. All rights reserved. Topology Optimization of 3-DOF Peristaltic Structure Robot Based on Vector Continuous Mapping Matrix Wed, 19 Oct 2016 08:13:26 +0000 A mechanism for topology optimization of 3-DOF parallel peristaltic structure robot with vector continuous mapping matrix using Solid Isotropic Material with Penalization (SIMP) method is presented in this paper. We focus on how to prevent the differential motion consistency between parallel prototype mechanisms with peristaltic structure. As the conventional parallel robot joints/hinges are no longer needed after topology optimization, therefore, we renamed this kind of 3-DOF robot structures as peristaltic structure. In the proposed method, the vector continuous mapping matrix is built as stress/strain transfer direction conditions for topology optimization of peristaltic structure, and SIMP method is used for multi-inputs and multioutputs decided by parallel prototype mechanisms. Some numerical examples are presented to illustrate the validity of the proposed method. Gao Wang, Dachang Zhu, and Ning Liu Copyright © 2016 Gao Wang et al. All rights reserved. A New Double Sliding Mode Observer for EV Lithium Battery SOC Estimation Tue, 18 Oct 2016 16:21:26 +0000 A new sliding mode observer is proposed in this paper; compared with the existing sliding mode observer used for SOC estimation, the new observer has the advantages of simple design and good generality. The robustness of the new observer was proved by Lyapunov stability theorem. Taking the first-order Randle circuit model of the battery as an example, the new sliding mode observer was designed. Battery test was done with the simulated FUDS condition, and the robustness of the new observer was verified by the test. Because battery internal ohmic resistance is changing in battery working process, which has a significant effect on SOC estimation, a new double sliding mode observer was designed to identify the internal resistance. The tests results show that the battery internal ohmic resistance changes greatly when the SOC is low and the double observer can accurately identify the resistance which improves the accuracy of the battery model. The results also show that the new double observer is robust and can improve the precision of SOC estimation when the battery remaining capacity is low. Qiaoyan Chen, Jiuchun Jiang, Haijun Ruan, and Caiping Zhang Copyright © 2016 Qiaoyan Chen et al. All rights reserved. Effective and Fast Near Duplicate Detection via Signature-Based Compression Metrics Tue, 18 Oct 2016 14:52:31 +0000 Detecting near duplicates on the web is challenging due to its volume and variety. Most of the previous studies require the setting of input parameters, making it difficult for them to achieve robustness across various scenarios without careful tuning. Recently, a universal and parameter-free similarity metric, the normalized compression distance or NCD, has been employed effectively in diverse applications. Nevertheless, there are problems preventing NCD from being applied to medium-to-large datasets as it lacks efficiency and tends to get skewed by large object size. To make this parameter-free method feasible on a large corpus of web documents, we propose a new method called SigNCD which measures NCD based on lightweight signatures instead of full documents, leading to improved efficiency and stability. We derive various lower bounds of NCD and propose pruning policies to further reduce computational complexity. We evaluate SigNCD on both English and Chinese datasets and show an increase in score compared with the original NCD method and a significant reduction in runtime. Comparisons with other competitive methods also demonstrate the superiority of our method. Moreover, no parameter tuning is required in SigNCD, except a similarity threshold. Xi Zhang, Yuntao Yao, Yingsheng Ji, and Binxing Fang Copyright © 2016 Xi Zhang et al. All rights reserved. Smooth Adaptive Internal Model Control Based on Model for Nonlinear Systems with Dynamic Uncertainties Tue, 18 Oct 2016 14:36:03 +0000 An improved smooth adaptive internal model control based on model control method is presented to simplify modeling structure and parameter identification for a class of uncertain dynamic systems with unknown model parameters and bounded external disturbances. Differing from traditional adaptive methods, the proposed controller can simplify the identification of time-varying parameters in presence of bounded external disturbances. Combining the small gain theorem and the virtual equivalent system theory, learning rate of smooth adaptive internal model controller has been analyzed and the closed-loop virtual equivalent system based on discrete model has been constructed as well. The convergence of this virtual equivalent system is proved, which further shows the convergence of the complex closed-loop discrete model system. Finally, simulation and experimental results on a typical nonlinear dynamic system verified the feasibility of the proposed algorithm. The proposed method is shown to have lighter identification burden and higher control accuracy than the traditional adaptive controller. Li Zhao, Jing Wang, and Weicun Zhang Copyright © 2016 Li Zhao et al. All rights reserved. Representations of Generalized Inverses and Drazin Inverse of Partitioned Matrix with Banachiewicz-Schur Forms Tue, 18 Oct 2016 11:16:19 +0000 Representations of -inverses, -inverses, and Drazin inverse of a partitioned matrix related to the generalized Schur complement are studied. First, we give the necessary and sufficient conditions under which -inverses, -inverses, and group inverse of a block matrix can be represented in the Banachiewicz-Schur forms. Some results from the paper of Cvetković-Ilić, 2009, are generalized. Also, we expressed the quotient property and the first Sylvester identity in terms of the generalized Schur complement. Xiaoji Liu, Hongwei Jin, and Jelena Višnjić Copyright © 2016 Xiaoji Liu et al. All rights reserved. Underdetermined Separation of Speech Mixture Based on Sparse Bayesian Learning Mon, 17 Oct 2016 14:07:20 +0000 This paper describes a novel algorithm for underdetermined speech separation problem based on compressed sensing which is an emerging technique for efficient data reconstruction. The proposed algorithm consists of two steps. The unknown mixing matrix is firstly estimated from the speech mixtures in the transform domain by using -means clustering algorithm. In the second step, the speech sources are recovered based on an autocalibration sparse Bayesian learning algorithm for speech signal. Numerical experiments including the comparison with other sparse representation approaches are provided to show the achieved performance improvement. Zhe Wang, Luyun Wang, Xiumei Li, Lifan Zhao, and Guoan Bi Copyright © 2016 Zhe Wang et al. All rights reserved. Characterization of Energy Availability in RF Energy Harvesting Networks Mon, 17 Oct 2016 10:00:48 +0000 The multiple nodes forming a Radio Frequency (RF) Energy Harvesting Network (RF-EHN) have the capability of converting received electromagnetic RF signals in energy that can be used to power a network device (the energy harvester). Traditionally the RF signals are provided by high power transmitters (e.g., base stations) operating in the neighborhood of the harvesters. Admitting that the transmitters are spatially distributed according to a spatial Poisson process, we start by characterizing the distribution of the RF power received by an energy harvester node. Considering Gamma shadowing and Rayleigh fading, we show that the received RF power can be approximated by the sum of multiple Gamma distributions with different scale and shape parameters. Using the distribution of the received RF power, we derive the probability of a node having enough energy to transmit a packet after a given amount of charging time. The RF power distribution and the probability of a harvester having enough energy to transmit a packet are validated through simulation. The numerical results obtained with the proposed analysis are close to the ones obtained through simulation, which confirms the accuracy of the proposed analysis. Daniela Oliveira and Rodolfo Oliveira Copyright © 2016 Daniela Oliveira and Rodolfo Oliveira. All rights reserved. Improved DDA Method Based on Explicitly Solving Contact Constraints Mon, 17 Oct 2016 09:28:52 +0000 This paper proposes an improved DDA method based on explicitly solving contact constraints. The potential energy function generated by contacting, which contains only displacement variables as an unknown, is deduced based on the approximated step function and Lagrange interpolation, and the displacement variables and contact constraints are obtained via the variable metric method by analyzing the potential energy extremum. There is no need to conduct the open-close iteration during the process of calculation. The improved DDA method based on explicitly solving contact constraints has high precision and a more stable and more robust computational convergence. The accuracy and iterative stability of the improved DDA method are verified using two numerical examples. Jian Zhao, Ming Xiao, Juntao Chen, and Dongdong Li Copyright © 2016 Jian Zhao et al. All rights reserved. A Trigonometric Analytical Solution of Simply Supported Horizontally Curved Composite I-Beam considering Tangential Slips Mon, 17 Oct 2016 09:28:29 +0000 This paper presents an analytical solution of the simply supported horizontally composite curved I-beam by trigonometric series considering the effect of partial interaction in the tangential direction. Governing equations and boundary conditions are obtained by using the Vlasov curved beam theory and the principle of minimum potential energy. The deflection functions and the Lagrange multiplier functions are expressed as trigonometric series to satisfy the governing equations and the simply supported constraints at both ends. The numerical results of deflections and forces which are obtained by this method are compared with both FEM results and experimental results, and the inaccuracy between the analytical solutions in this paper and the FEM results is small and reasonable. Qin Xu-xi, Liu Han-bing, Wu Chun-li, and Gu Zheng-wei Copyright © 2016 Qin Xu-xi et al. All rights reserved. Elastic-Plastic Numerical Analysis of Tunnel Stability Based on the Closest Point Projection Method Considering the Effect of Water Pressure Mon, 17 Oct 2016 06:51:35 +0000 To study the tunnel stability at various static water pressures and determine the mechanical properties and deformation behavior of surrounding rock, a modified effective stress formula was introduced into a numerical integration algorithm of elastic-plastic constitutive equation, that is, closest point projection method (CPPM). Taking the effects of water pressure and seepage into account, a CPPM-based formula was derived and a CPPM algorithm based on Drucker-Prager yield criterion considering the effect of pore water pressure was provided. On this basis, a CPPM-based elastic-plastic numerical analysis program considering pore water pressure was developed, which can be applied in the engineering of tunnels and other underground structures. The algorithm can accurately take the effects of groundwater on stability of surrounding rock mass into account and it can show the more pronounced effect of pore water pressure on stress, deformation, and the plastic zone in a tunnel. The stability of water flooding in Fusong tunnel was systematically analyzed using the developed program. The analysis results showed that the existence of groundwater seepage under tunnel construction will give rise to stress redistribution in the surrounding rock mass. Pore water pressure has a significant effect on the surrounding rock mass. Zhan-ping Song, Ten-tian Yang, and An-nan Jiang Copyright © 2016 Zhan-ping Song et al. All rights reserved. Numerical Investigation of Water Entry of Half Hydrophilic and Half Hydrophobic Spheres Sun, 16 Oct 2016 13:19:56 +0000 A numerical simulation to investigate the water entry of half-half sphere which is hydrophobic on one hemisphere and hydrophilic on the other is performed. Particular attention is given to the simulation method based on solving the Navier-Stokes equations coupled with VOF (volume of fluid) method and CSF (continuum surface force) method. Numerical results predicted experimental results, validating the suitability of the numerical approach to simulate the water entry problem of sphere under different wetting conditions. Numerical results show that the water entry of the half-half sphere creates an asymmetric cavity and “cardioid” splash, causing the sphere to travel laterally from the hydrophobic side to the hydrophilic side. Further investigations show that the density ratio and mismatch of asymmetric in wetting condition affect the trajectory, velocity, and acceleration of the half-half sphere during water entry. In addition, the total hydrodynamic force coefficient is investigated as a result of the forces acting on the sphere during water entry dictated by the cavity formation. Sun Zhao, Cao Wei, and Wang Cong Copyright © 2016 Sun Zhao et al. All rights reserved. Equilibrium Time-Consistent Strategy for Corporate International Investment Problem with Mean-Variance Criterion Sun, 16 Oct 2016 08:38:40 +0000 We analyze a continuous-time model for corporate international investment problem (CIIP) with mean-variance criterion. Based on Nash subgame perfect equilibrium theory, we define an infinitesimal operator and directly derive an extended Hamilton-Jacobi-Bellman (HJB) equation. Besides, we also obtain the equilibrium time-consistent strategy for CIIP. In addition, we discuss two cases of risk aversion coefficient; one is constant and the other is state dependent. Finally, the simulation results are given to illustrate our conclusions and the influence of some parameters on the optimal solution. Jun Long and Sanyun Zeng Copyright © 2016 Jun Long and Sanyun Zeng. All rights reserved. An Extended VIKOR Method for Multiple Attribute Decision Analysis with Bidimensional Dual Hesitant Fuzzy Information Sun, 16 Oct 2016 07:43:57 +0000 Bidimensional dual hesitant fuzzy (BDHF) set is developed to present preferences of a decision maker or an expert, which is more objective than existing fuzzy sets such as Atanassov’s intuitionistic fuzzy set, hesitant fuzzy set, and dual hesitant fuzzy set. Then, after investigating some distance measures, we define a new generalized distance measure between two BDHF elements with parameter for the sake of overcoming some drawbacks in existing distance measures. Covering all possible values of parameter , a new approach is designed to calculate the generalized distance measure between two BDHF elements. In order to address complex multiple attribute decision analysis (MADA) problems, an extension of fuzzy VIKOR method in BDHF context is proposed in this paper. In VIKOR method for MADA problems, weight of each attribute indicates its relative importance. To obtain weights of attributes objectively, a new entropy measure with BDHF information is developed to create weight of each attribute. Finally, an evaluation problem of performance of people’s livelihood project in several regions is analyzed by the proposed VIKOR method to demonstrate its applicability and validity. Min Xue, Xiaoan Tang, and Nanping Feng Copyright © 2016 Min Xue et al. All rights reserved. Evolutionary Game Analysis of the Supervision Behavior for Public-Private Partnership Projects with Public Participation Thu, 13 Oct 2016 14:14:28 +0000 The public can directly or indirectly participate in the PPP (public-private partnership) projects and then has an impact on the project profit and public or private behavior. To explore the influence of the public participation of the PPP projects supervision behavior, this paper analyzes the mutual evolutionary regularity of the private sector and government supervision department and the influence of public participation level on public and private behavior based on evolutionary game theory. The results show that the supervision strategy is not chosen when the supervision cost of government supervision department is greater than the supervision benefit; it can make private sector consciously provide the high-quality public products/services with the improvement of public participation level. Therefore, the government should reduce the cost of public participation and improve the public participation level and influence through the application of the Internet, big data, and other advanced technologies, in order to restrain the behavior of the private sector and improve the supervision efficiency. Congdong Li, Xiaoli Li, and Yu Wang Copyright © 2016 Congdong Li et al. All rights reserved. Study on Leading Vehicle Detection at Night Based on Multisensor and Image Enhancement Method Thu, 13 Oct 2016 09:50:32 +0000 Low visibility is one of the reasons for rear accident at night. In this paper, we propose a method to detect the leading vehicle based on multisensor to decrease rear accidents at night. Then, we use image enhancement algorithm to improve the human vision. First, by millimeter wave radar to get the world coordinate of the preceding vehicles and establish the transformation of the relationship between the world coordinate and image pixels coordinate, we can convert the world coordinates of the radar target to image coordinate in order to form the region of interesting image. And then, by using the image processing method, we can reduce interference from the outside environment. Depending on D-S evidence theory, we can achieve a general value of reliability to test vehicles of interest. The experimental results show that the method can effectively eliminate the influence of illumination condition at night, accurately detect leading vehicles, and determine their location and accurate positioning. In order to improve nighttime driving, the driver shortage vision, reduce rear-end accident. Enhancing nighttime color image by three algorithms, a comparative study and evaluation by three algorithms are presented. The evaluation demonstrates that results after image enhancement satisfy the human visual habits. Mei Chen, Lisheng Jin, Yuying Jiang, Linlin Gao, Faji Wang, and Xianyi Xie Copyright © 2016 Mei Chen et al. All rights reserved. Analytical Analysis and Field Observation of Break Line in the Main Roof over the Goaf Edge of Longwall Coal Mines Thu, 13 Oct 2016 05:56:15 +0000 This paper presents an integrated approach for analytical analysis and field tests to estimate the break line in a main roof over the goaf edge. An analytical model which treated the main roof as a beam seating on the Winkler foundation and subjected to nonuniformity roof loading was established. Further analysis of the bending moment distribution of such a main roof beam was undertaken. Based on the geological conditions pertaining to a case study at Wangjialing coal mine, Shanxi Province, China, the break line in the main roof in a typical longwall panel was calculated in the rib-sides at a distance of 5.6 to 7.4 m from the goaf edge. The influence of main roof flexural rigidity and foundation rigidity and so forth on the bending moment distribution was revealed by a parametric study. Borehole camera detection was employed to further validate the analytical model and its results. The results of the field test demonstrated that the break line detected in the main roof was about 5.5 to 6.8 m away from the goaf edge, which was in good agreement with the analytical model. Zhang Guangchao, He Fulian, and Jiang Lishuai Copyright © 2016 Zhang Guangchao et al. All rights reserved. Dynamic Recognition of Driver’s Propensity Based on GPS Mobile Sensing Data and Privacy Protection Wed, 12 Oct 2016 12:29:14 +0000 Driver’s propensity is a dynamic measurement of driver’s emotional preference characteristics in driving process. It is a core parameter to compute driver’s intention and consciousness in safety driving assist system, especially in vehicle collision warning system. It is also an important influence factor to achieve the Driver-Vehicle-Environment Collaborative Wisdom and Control macroscopically. In this paper, dynamic recognition model of driver’s propensity based on support vector machine is established taking the vehicle safety controlled technology and respecting and protecting the driver’s privacy as precondition. The experiment roads travel time obtained through GPS is taken as the characteristic parameter. The sensing information of Driver-Vehicle-Environment was obtained through psychological questionnaire tests, real vehicle experiments, and virtual driving experiments, and the information is used for parameter calibration and validation of the model. Results show that the established recognition model of driver’s propensity is reasonable and feasible, which can achieve the dynamic recognition of driver’s propensity to some extent. The recognition model provides reference and theoretical basis for personalized vehicle active safety systems taking people as center especially for the vehicle safety technology based on the networking. Xiaoyuan Wang, Jianqiang Wang, Jinglei Zhang, and Jingheng Wang Copyright © 2016 Xiaoyuan Wang et al. All rights reserved. Effects of Separation Strategy on Deployment of Multitethered Chain-Type Satellite System Wed, 12 Oct 2016 12:18:46 +0000 This paper investigates the effects of separation strategy and parameters related to deployment on the dynamic behavior of multitethered chain-type satellite system. The system, including several satellites connected by tethers which are considered as massless and straight, is modeled as an extension of a two-body dumbbell tethered system. The dynamic equations of system in absence of perturbations and external disturbances are derived using Newtonian Method. To observe the effect of deployment rate on the motion of system, a parametric analysis of the deployment of a three-body tethered system with different deployment rates is carried out. Moreover, a four-body tethered system is used to investigate the effect of separation strategies on the dynamic behavior of system during the deployment phase. The numerical results suggest that the system with simultaneous separation costs less time to complete the deployment. If the ratio of deployment rates is in consistence with that of their desired lengths, the tethers deployed simultaneously would have a synchronous motion. It is also observed that the system employing separation bolt has a better performance than the system separated by spring mechanism since the larger separation velocity which is not along local vertical may cause a rotation. Jinxiu Zhang and Zhigang Zhang Copyright © 2016 Jinxiu Zhang and Zhigang Zhang. All rights reserved. - and -Norm Joint Regularization Based Sparse Signal Reconstruction Scheme Wed, 12 Oct 2016 09:21:28 +0000 Many problems in signal processing and statistical inference involve finding sparse solution to some underdetermined linear system of equations. This is also the application condition of compressive sensing (CS) which can find the sparse solution from the measurements far less than the original signal. In this paper, we propose - and -norm joint regularization based reconstruction framework to approach the original -norm based sparseness-inducing constrained sparse signal reconstruction problem. Firstly, it is shown that, by employing the simple conjugate gradient algorithm, the new formulation provides an effective framework to deduce the solution as the original sparse signal reconstruction problem with -norm regularization item. Secondly, the upper reconstruction error limit is presented for the proposed sparse signal reconstruction framework, and it is unveiled that a smaller reconstruction error than -norm relaxation approaches can be realized by using the proposed scheme in most cases. Finally, simulation results are presented to validate the proposed sparse signal reconstruction approach. Chanzi Liu, Qingchun Chen, Bingpeng Zhou, and Hengchao Li Copyright © 2016 Chanzi Liu et al. All rights reserved. Robust Fuzzy Control for Fractional-Order Uncertain Hydroturbine Regulating System with Random Disturbances Wed, 12 Oct 2016 06:50:36 +0000 The robust fuzzy control for fractional-order hydroturbine regulating system is studied in this paper. First, the more practical fractional-order hydroturbine regulating system with uncertain parameters and random disturbances is presented. Then, on the basis of interval matrix theory and fractional-order stability theorem, a fuzzy control method is proposed for fractional-order hydroturbine regulating system, and the stability condition is expressed as a group of linear matrix inequalities. Furthermore, the proposed method has good robustness which can process external random disturbances and uncertain parameters. Finally, the validity and superiority are proved by the numerical simulations. Fengjiao Wu, Guitao Zhang, and Zhengzhong Wang Copyright © 2016 Fengjiao Wu et al. All rights reserved. A Novel Multiobjective Optimization Method Based on Sensitivity Analysis Tue, 11 Oct 2016 14:39:15 +0000 For multiobjective optimization problems, different optimization variables have different influences on objectives, which implies that attention should be paid to the variables according to their sensitivity. However, previous optimization studies have not considered the variables sensitivity or conducted sensitivity analysis independent of optimization. In this paper, an integrated algorithm is proposed, which combines the optimization method SPEA (Strength Pareto Evolutionary Algorithm) with the sensitivity analysis method SRCC (Spearman Rank Correlation Coefficient). In the proposed algorithm, the optimization variables are worked as samples of sensitivity analysis, and the consequent sensitivity result is used to guide the optimization process by changing the evolutionary parameters. Three cases including a mathematical problem, an airship envelope optimization, and a truss topology optimization are used to demonstrate the computational efficiency of the integrated algorithm. The results showed that this algorithm is able to simultaneously achieve parameter sensitivity and a well-distributed Pareto optimal set, without increasing the computational time greatly in comparison with the SPEA method. Tiane Li, Xiaoying Sun, Zhengzheng Lu, and Yue Wu Copyright © 2016 Tiane Li et al. All rights reserved. A New Approach for Large-Scale Scene Image Retrieval Based on Improved Parallel -Means Algorithm in MapReduce Environment Mon, 10 Oct 2016 13:33:55 +0000 The rapid growth of digital images has caused the traditional image retrieval technology to be faced with new challenge. In this paper we introduce a new approach for large-scale scene image retrieval to solve the problems of massive image processing using traditional image retrieval methods. First, we improved traditional -Means clustering algorithm, which optimized the selection of the initial cluster centers and iteration procedure. Second, we presented a parallel design and realization method for improved -Means algorithm applied it to feature clustering of scene images. Finally, a storage and retrieval scheme for large-scale scene images was put forward using the large storage capacity and powerful parallel computing ability of the Hadoop distributed platform. The experimental results demonstrated that the proposed method achieved good performance. Compared with the traditional algorithms with single node architecture and parallel -Means algorithm, the proposed method has obvious advantages for use in large-scale scene image data retrieval in terms of retrieval accuracy, retrieval time overhead, and computational performance (speedup and efficiency, sizeup, and scaleup), which is a significant improvement from applying parallel processing to intelligent algorithms with large-scale datasets. Jianfang Cao, Min Wang, Hao Shi, Guohua Hu, and Yun Tian Copyright © 2016 Jianfang Cao et al. All rights reserved. Structural Safety Monitoring of High Arch Dam Using Improved ABC-BP Model Mon, 10 Oct 2016 10:18:18 +0000 The establishment of a structural safety monitoring model of a dam is necessary for the evaluation of the dam’s deformation status. The structural safety monitoring method based on the monitoring data is widely used in traditional research. On the basis of the analysis of the high arch dam’s deformation principles, this study proposes a structural safety monitoring method derived from the dam deformation monitoring data. The method first analyzes and establishes the spatial and temporal distribution of high arch dam’s safety monitoring, overcoming the standard artificial bee colony (ABC) algorithm’s shortcoming of easily falling into the local optimum by adopting the adaptive proportion and average Euclidean distance afterwards. The improved ABC algorithm is used to optimize the backpropagation (BP) neural network’s initial weight and threshold. The application example proves that ABC-BP model’s improvement method is important for the establishment of a high arch deformation safety monitoring model and can effectively improve the model’s fitting and forecasting ability. This method provides a reference for the establishment of a structural safety monitoring model of dam and provides guidance for the establishment of a forecasting model in other fields. Yantao Zhu, Chongshi Gu, Erfeng Zhao, Jintao Song, and Zhiyun Guo Copyright © 2016 Yantao Zhu et al. All rights reserved. A Novel Detection Scheme with Multiple Observations for Sparse Signal Based on Likelihood Ratio Test with Sparse Estimation Mon, 10 Oct 2016 10:15:14 +0000 Recently, the problem of detecting unknown and arbitrary sparse signals has attracted much attention from researchers in various fields. However, there remains a peck of difficulties and challenges as the key information is only contained in a small fraction of the signal and due to the absence of prior information. In this paper, we consider a more general and practical scenario of multiple observations with no prior information except for the sparsity of the signal. A new detection scheme referred to as the likelihood ratio test with sparse estimation (LRT-SE) is presented. Under the Neyman-Pearson testing framework, LRT-SE estimates the unknown signal by employing the -minimization technique from compressive sensing theory. The detection performance of LRT-SE is preliminarily analyzed in terms of error probabilities in finite size and Chernoff consistency in high dimensional condition. The error exponent is introduced to describe the decay rate of the error probability as observations number grows. Finally, these properties of LRT-SE are demonstrated based on the experimental results of synthetic sparse signals and sparse signals from real satellite telemetry data. It could be concluded that the proposed detection scheme performs very close to the optimal detector. Hongbo Zhao, Lei Chen, Wenquan Feng, and Chuan Lei Copyright © 2016 Hongbo Zhao et al. All rights reserved.