Mathematical Problems in Engineering The latest articles from Hindawi © 2017 , Hindawi Limited . All rights reserved. A New and Efficient Boundary Element-Free Method for 2-D Crack Problems Tue, 21 Feb 2017 00:00:00 +0000 An efficient boundary element-free method is established for 2-D crack problems by combining a pair of boundary integral equations and the moving-least square approximation. The displacement boundary integral equation is collated on the on-crack boundary, and a new traction boundary integral equation is applied on the crack surface without the separate consideration of the upper and lower sides. In virtue of integration by parts, only singularity in order is involved in the integral kernels of new traction boundary integral equation, which brings convenience to the numerical implementation. Meanwhile, the integration by parts produces the new variables, the displacement density, and displacement dislocation density, and they are the coexisting unknowns along with the displacement and displacement dislocation. With the high-order continuity of the moving-least square approximation, these new variables are directly approximated with the nodal displacement or displacement dislocation, and the final system of equations contains the unknowns of nodal displacements and displacement dislocations only. The boundary element-free computational scheme is established, and several examples show the efficiency and flexibility of the proposed method. Jinchao Yue, Liwu Chang, and Yuzhou Sun Copyright © 2017 Jinchao Yue et al. All rights reserved. Fractionally Spaced Constant Modulus Equalizer with Recognition Capability for Digital Array Radar Tue, 21 Feb 2017 00:00:00 +0000 Fractionally spaced blind equalizer (BE) based on constant modulus criteria is exploited to compensate for the channel-to-channel mismatch in a digital array radar. We apply the technique of recognition to improve the stability and reliability of the BE. The surveillance of the calibration signal and the convergence property of BE are both implemented with recognition description words. BE with cognitive capability is appropriate for the equalization of a digital array radar with thousands of channels and hundreds of working frequencies, where reliability becomes the most concerned indicator. The improvement of performance in the accidental scenarios is tested via numerical simulations with the cost of increased computational complexity. Feng Wang, Shuang Wei, and Defu Jiang Copyright © 2017 Feng Wang et al. All rights reserved. Novel Stability Analysis for Uncertain Neutral-Type Lur’e Systems with Time-Varying Delays Using New Inequality Tue, 21 Feb 2017 00:00:00 +0000 This paper considers the delay-dependent stability analysis of neutral-type Lur’e systems with time-varying delays and sector bounded nonlinearities. First of all, using constructed function methods, a new Jensen-like inequality is introduced to obtain less conservative results. Second, a new class of Lyapunov-Krasovskii functional (LKF) is constructed according to the characteristic of the considered systems. Third, combining with the new inequality and reciprocal convex approach and some other inequality techniques, the new less conservative robust stability criteria are shown in the form of linear matrix inequalities (LMIs). Finally, three examples demonstrate the feasibility and the superiority of our methods. Yanmeng Wang, Lianglin Xiong, Yongkun Li, Haiyang Zhang, and Chen Peng Copyright © 2017 Yanmeng Wang et al. All rights reserved. MIMO SAR Imaging for Wide-Swath Based on Compressed Sensing Tue, 21 Feb 2017 00:00:00 +0000 To reduce the amount of data to be stored and software/hardware complexity and suppress range ambiguity, a novel MIMO SAR imaging based on compressed sensing is proposed under the condition of wide-swath imaging. Random phase orthogonal waveform (RPOW) is designed for MIMO SAR based on compressed sensing (CS). Echo model of sparse array in range and compressive sampling is reconstructed with CS theory. Resolution in range imaging is improved by using the techniques of digital beamforming (DBF) in transmit. Zero-point technique based on CS is proposed with DBF in receive and the range ambiguity is suppressed effectively. Comprehensive numerical simulation examples are performed. Its validity and practicality are validated by simulations. Feng Liu, Shanxiang Mu, and Wanghan Lv Copyright © 2017 Feng Liu et al. All rights reserved. Resource Leveling Based on Backward Controlling Activity in Line of Balance Tue, 21 Feb 2017 00:00:00 +0000 The line of balance method that provides continuous and uninterrupted use of resources is one of the best methods for repetitive project resource management. This paper develops a resource leveling algorithm based on the backward controlling activity in line of balance. The backward controlling activity is a kind of special activity, and if its duration is prolonged the project duration could be reduced. It brings two advantages to the resource leveling: both the resource allocated on the backward activity and the project duration are reduced. A resource leveling algorithm is presented which permits the number of crews of the backward controlling activity to be reduced until the terminal situation is reached, where the backward controlling activity does not exist or the number of crews cannot be reduced. That adjustment enables the productivity of all activities to be consistent. An illustrative pipeline project demonstrates the improvement in resource leveling. And this study designed a MATLAB program to execute the design algorithm. The proposed model could help practitioners to achieve the goals of both resource leveling and project duration reduction without increasing any resource. Lihui Zhang, Yaping Tang, and Jianxun Qi Copyright © 2017 Lihui Zhang et al. All rights reserved. Modeling and Control of Active-Passive Vibration Isolation for Floating Raft System Tue, 21 Feb 2017 00:00:00 +0000 This paper presents a new approach for constructing a mathematical model of the floating raft system directly from input-output measurements in the presence of noise. In contrast to the original OKID/ERA algorithm, which works through the observer Markov parameters, the new approach used observer output residuals to convert the initial stochastic identification to a virtually deterministic identification problem. The extension of deterministic algorithm to stochastic problems by proposed stochastic-to-deterministic conversion can be done with ease. A MIMO (multiple-input multiple-output) system state-space model and an associated Kalman filter gain can be identified. controller with high robustness to model error is designed to solve multifrequency varying vibration for floating raft system. Both simulated and experimental results confirm the validity and the benefits of the approach. Beibei Yang, Yefa Hu, and Jinguang Zhang Copyright © 2017 Beibei Yang et al. All rights reserved. Chaos Suppression of an Electrically Actuated Microresonator Based on Fractional-Order Nonsingular Fast Terminal Sliding Mode Control Mon, 20 Feb 2017 12:14:54 +0000 This paper focuses on chaos suppression strategy of a microresonator actuated by two symmetrical electrodes. Dynamic behavior of this system under the case where the origin is the only stable equilibrium is investigated first. Numerical simulations reveal that system may exhibit chaotic motion under certain excitation conditions. Then, bifurcation diagrams versus amplitude or frequency of AC excitation are drawn to grasp system dynamics nearby its natural frequency. Results show that the vibration is complex and may exhibit period-doubling bifurcation, chaotic motion, or dynamic pull-in instability. For the suppression of chaos, a novel control algorithm, based on an integer-order nonsingular fast terminal sliding mode and a fractional-order switching law, is proposed. Fractional Lyapunov Stability Theorem is used to guarantee the asymptotic stability of the system. Finally, numerical results with both fractional-order and integer-order control laws show that our proposed control law is effective in controlling chaos with system uncertainties and external disturbances. Jianxin Han, Qichang Zhang, Wei Wang, Gang Jin, Houjun Qi, and Qiu Li Copyright © 2017 Jianxin Han et al. All rights reserved. Numerical Simulation for 2D Sedimentation Model by an Upwind Discontinuous Galerkin Procedure Mon, 20 Feb 2017 11:28:32 +0000 We reformulate the mathematical model for the 2D sedimentation in an estuary as a coupled nonlinear differential system. Combining the mass-conservation character of the discontinuous Galerkin method and the jump-capturing property of Lesaint-Raviart upwind technique, we design an upwind discontinuous Galerkin finite element method, which obeys the local mass conservation and possesses good stability. Our theoretical analysis shows that there exists a unique solution to the numerical procedure and the discrete solution permits convergence rate. Numerical experiments are conducted to verify our theoretical findings. This may provide a theoretical principle for better understanding of the mechanism and morphological characters of sedimentation at estuaries. JinFeng Jian, HuanZhen Chen, and BaoHai Shi Copyright © 2017 JinFeng Jian et al. All rights reserved. An Improved Grey Wolf Optimization Strategy Enhanced SVM and Its Application in Predicting the Second Major Mon, 20 Feb 2017 09:58:51 +0000 In order to develop a new and effective prediction system, the full potential of support vector machine (SVM) was explored by using an improved grey wolf optimization (GWO) strategy in this study. An improved GWO, IGWO, was first proposed to identify the most discriminative features for major prediction. In the proposed approach, particle swarm optimization (PSO) was firstly adopted to generate the diversified initial positions, and then GWO was used to update the current positions of population in the discrete searching space, thus getting the optimal feature subset for the better classification purpose based on SVM. The resultant methodology, IGWO-SVM, is rigorously examined based on the real-life data which includes a series of factors that influence the students’ final decision to choose the specific major. To validate the proposed method, other metaheuristic based SVM methods including GWO based SVM, genetic algorithm based SVM, and particle swarm optimization-based SVM were used for comparison in terms of classification accuracy, AUC (the area under the receiver operating characteristic (ROC) curve), sensitivity, and specificity. The experimental results demonstrate that the proposed approach can be regarded as a promising success with the excellent classification accuracy, AUC, sensitivity, and specificity of 87.36%, 0.8735, 85.37%, and 89.33%, respectively. Promisingly, the proposed methodology might serve as a new candidate of powerful tools for second major selection. Yan Wei, Ni Ni, Dayou Liu, Huiling Chen, Mingjing Wang, Qiang Li, Xiaojun Cui, and Haipeng Ye Copyright © 2017 Yan Wei et al. All rights reserved. Intuitionistic Trapezoidal Fuzzy Group Decision-Making Based on Prospect Choquet Integral Operator and Grey Projection Pursuit Dynamic Cluster Mon, 20 Feb 2017 09:44:10 +0000 In consideration of the interaction among attributes and the influence of decision makers’ risk attitude, this paper proposes an intuitionistic trapezoidal fuzzy aggregation operator based on Choquet integral and prospect theory. With respect to a multiattribute group decision-making problem, the prospect value functions of intuitionistic trapezoidal fuzzy numbers are aggregated by the proposed operator; then a grey relation-projection pursuit dynamic cluster method is developed to obtain the ranking of alternatives; the firefly algorithm is used to optimize the objective function of projection for obtaining the best projection direction of grey correlation projection values, and the grey correlation projection values are evaluated, which are applied to classify, rank, and prefer the alternatives. Finally, an illustrative example is taken in the present study to make the proposed method comprehensible. Jiahang Yuan and Cunbin Li Copyright © 2017 Jiahang Yuan and Cunbin Li. All rights reserved. Automatic Segmentation for Plant Leaves via Multiview Stereo Reconstruction Mon, 20 Feb 2017 09:41:56 +0000 This paper presented a new method for automatic plant point cloud acquisition and leaves segmentation. Quasi-dense point cloud of the plant is obtained from multiview stereo reconstruction based on surface expansion. In order to overcome the negative effects from complex natural light changes and to obtain a more accurate plant point cloud, the Adaptive Normalized Cross-Correlation algorithm is used in calculating the matching cost between two images, which is robust to radiometric factors and can reduce the fattening effect around boundaries. In the stage of segmentation for each single leaf, an improved region growing method based on fully connected conditional random field (CRF) is proposed to separate the connected leaves with similar color. The method has three steps: boundary erosion, initial segmentation, and segmentation refinement. First, the edge of each leaf point cloud is eroded to remove the connectivity between leaves. Then leaves will be initially segmented by region growing algorithm based on local surface normal and curvature. Finally an efficient CRF inference method based on mean field approximation is applied to remove small isolated regions. Experimental results show that our multiview stereo reconstruction method is robust to illumination changes and can obtain accurate color point clouds. And the improved region growing method based on CRF can effectively separate the connected leaves in obtained point cloud. Jingwei Guo and Lihong Xu Copyright © 2017 Jingwei Guo and Lihong Xu. All rights reserved. Social Network Community Detection for DMA Creation: Criteria Analysis through Multilevel Optimization Mon, 20 Feb 2017 00:00:00 +0000 Management of large water distribution systems can be improved by dividing their networks into so-called district metered areas (DMAs). However, such divisions must be based on appropriated technical criteria. Considering the importance of deeply understanding the relationship between DMA creation and these criteria, this work proposes a performance analysis of DMA generation that takes into account such indicators as resilience index, demand similarity, pressure uniformity, water age (and thus water quality), solution implantation costs, and electrical consumption. To cope with the complexity of the problem, suitable mathematical techniques are proposed in this paper. We use a social community detection technique to define the sectors, and then a multilevel particle swarm optimization approach is applied to find the optimal placement and operating point of the necessary devices. The results obtained by implementing the methodology in a real water supply network show its validity and the meaningful influence on the final result of, especially, elevation and pipe length. Bruno M. Brentan, Enrique Campbell, Gustavo L. Meirelles, Edevar Luvizotto Jr., and Joaquín Izquierdo Copyright © 2017 Bruno M. Brentan et al. All rights reserved. Optical Axis Perturbation Analysis for the Unit-Magnification Multipass System Mon, 20 Feb 2017 00:00:00 +0000 The optical axis sensitivity for the unit-magnification multipass system (UMS) is presented by using a general misaligned optical element transfer model. The generalized sensitivity factors SD1, SD2, ST1, and ST2 influenced by both the axial and angular misalignments of the objective mirrors in a UMS have been calculated for the first time. The Bernstein-Herzberg White Cells are used as an example, and their alignment tolerance and stability properties are found when their configurations change. The analysis in this paper is helpful for the design of other kinds of multipass gas cells (MGC) with high robustness and avoiding the violent vibration of the optical axis when the misalignment of each mirror is controlled within the tolerance range. Among the five possible perturbations sources, the misaligned factors have more effects on the output beam’s position and the perturbed sources from and have more impacts on the output beam’s slope referred to as -axis and -axis, respectively. Higher reflection times mean smaller tolerance range. The results benefit the multipass cell design and the precise alignment of the mirrors within the cell with the purpose of long-term stability in measurements. Yin Guo, Liqun Sun, and Zheng Yang Copyright © 2017 Yin Guo et al. All rights reserved. Best Speed Fit EDF Scheduling for Performance Asymmetric Multiprocessors Mon, 20 Feb 2017 00:00:00 +0000 In order to improve the performance of a real-time system, asymmetric multiprocessors have been proposed. The benefits of improved system performance and reduced power consumption from such architectures cannot be fully exploited unless suitable task scheduling and task allocation approaches are implemented at the operating system level. Unfortunately, most of the previous research on scheduling algorithms for performance asymmetric multiprocessors is focused on task priority assignment. They simply assign the highest priority task to the fastest processor. In this paper, we propose BSF-EDF (best speed fit for earliest deadline first) for performance asymmetric multiprocessor scheduling. This approach chooses a suitable processor rather than the fastest one, when allocating tasks. With this proposed BSF-EDF scheduling, we also derive an effective schedulability test. Peng Wu and Minsoo Ryu Copyright © 2017 Peng Wu and Minsoo Ryu. All rights reserved. MIMO PI Controllers for LTI Systems with Multiple Time Delays Based on ILMIs and Sensitivity Functions Mon, 20 Feb 2017 00:00:00 +0000 In this paper, a MIMO PI design procedure is proposed for linear time invariant (LTI) systems with multiple time delays. The controller tuning is established in two stages and guarantees performances for set-point changes, disturbance variations, and parametric uncertainties. In the first stage, an iterative linear matrix inequality (ILMI) approach is extended to design PI controllers for systems with multiple time delays without performance guarantee, a priori. The second stage is devoted to improve the closed-loop performances by minimizing sensitivity functions. Simulations results carried out on the unstable distillation column, the stable industrial scale polymerization (ISP) reactor, and the non-minimum phase 4-tank benchmark prove the efficiency of the proposed approach. A comparative analysis with the conventional internal model control (IMC) approach, a multiloop IMC-PI approach, and a previous ILMI PID approach proves the superiority of the proposed approach compared to the related ones. Wajdi Belhaj and Olfa Boubaker Copyright © 2017 Wajdi Belhaj and Olfa Boubaker. All rights reserved. An Effective Way to Control Numerical Instability of a Nonordinary State-Based Peridynamic Elastic Model Mon, 20 Feb 2017 00:00:00 +0000 The constitutive modeling and numerical implementation of a nonordinary state-based peridynamic (NOSB-PD) model corresponding to the classical elastic model are presented. Besides, the numerical instability problem of the NOSB-PD model is analyzed, and a penalty method involving the hourglass force is proposed to control the instabilities. Further, two benchmark problems, the static elastic deformation of a simple supported beam and the elastic wave propagation in a two-dimensional rod, are discussed with the present method. It proves that the penalty instability control method is effective in suppressing the displacement oscillations and improving the accuracy of calculated stress fields with a proper hourglass force coefficient, and the NOSB-PD approach with instability control can analyze the problems of structure deformation and elastic wave propagation well. Xin Gu, Qing Zhang, and Yangtian Yu Copyright © 2017 Xin Gu et al. All rights reserved. Study on Reverse Reconstruction Method of Vehicle Group Situation in Urban Road Network Based on Driver-Vehicle Feature Evolution Mon, 20 Feb 2017 00:00:00 +0000 Vehicle group situation is the status and situation of dynamic permutation which is composed of target vehicle and neighboring traffic entities. It is a concept which is frequently involved in the research of traffic flow theory, especially the active vehicle security. Studying vehicle group situation in depth is of great significance for traffic safety. Three-lane condition was taken as an example; the characteristics of target vehicle and its neighboring vehicles were synthetically considered to restructure the vehicle group situation in this paper. The Gamma distribution theory was used to identify the vehicle group situation when target vehicle arrived at the end of the study area. From the perspective of driver-vehicle feature evolution, the reverse reconstruction method of vehicle group situation in the urban road network was proposed. Results of actual driving, virtual driving, and simulation experiments showed that the model established in this paper was reasonable and feasible. Xiaoyuan Wang, Jianqiang Wang, Zhenxue Liu, Yaqi Liu, and Jingheng Wang Copyright © 2017 Xiaoyuan Wang et al. All rights reserved. Large-Scale Portfolio Optimization Using Multiobjective Evolutionary Algorithms and Preselection Methods Mon, 20 Feb 2017 00:00:00 +0000 Portfolio optimization problems involve selection of different assets to invest in order to maximize the overall return and minimize the overall risk simultaneously. The complexity of the optimal asset allocation problem increases with an increase in the number of assets available to select from for investing. The optimization problem becomes computationally challenging when there are more than a few hundreds of assets to select from. To reduce the complexity of large-scale portfolio optimization, two asset preselection procedures that consider return and risk of individual asset and pairwise correlation to remove assets that may not potentially be selected into any portfolio are proposed in this paper. With these asset preselection methods, the number of assets considered to be included in a portfolio can be increased to thousands. To test the effectiveness of the proposed methods, a Normalized Multiobjective Evolutionary Algorithm based on Decomposition (NMOEA/D) algorithm and several other commonly used multiobjective evolutionary algorithms are applied and compared. Six experiments with different settings are carried out. The experimental results show that with the proposed methods the simulation time is reduced while return-risk trade-off performances are significantly improved. Meanwhile, the NMOEA/D is able to outperform other compared algorithms on all experiments according to the comparative analysis. B. Y. Qu, Q. Zhou, J. M. Xiao, J. J. Liang, and P. N. Suganthan Copyright © 2017 B. Y. Qu et al. All rights reserved. Unsteady Micropolar Fluid over a Permeable Curved Stretching Shrinking Surface Mon, 20 Feb 2017 00:00:00 +0000 This work deals with the unsteady micropolar fluid over a permeable curved stretching and shrinking surface. Using similarity transformations, the governing boundary layer equations are transformed into the nonlinear ordinary (similarity) differential equations. The transformed equations are then solved numerically using the shooting method. The effects of the governing parameters on the skin friction and couple stress are illustrated graphically. The results reveal that dual solutions exist for stretching/shrinking surface as well as weak/strong concentration. A comparison with known results from the open literature has been done and it is shown to be in excellent agreement. Siti Hidayah Muhad Saleh, Norihan Md Arifin, Roslinda Nazar, and Ioan Pop Copyright © 2017 Siti Hidayah Muhad Saleh et al. All rights reserved. Application of Variance Analyses Comparison in Seismic Damage Assessment of Masonry Buildings Using Three Simplified Indexes Mon, 20 Feb 2017 00:00:00 +0000 The reasonable assessment of potential damage type of masonry structures in seismic-prone zone is very significant to strengthen existing masonry structures and guide the construction of the new building. The primary objective of the study is to propose and determine a reasonable assessment index to predict the damage type of masonry structures in different seismic intensity zones using the survey results of the 2008 Wenchuan earthquake and variance analyses comparison methods. Three potential theory assessment indexes are considered in the evaluation of damage of masonry structures, including wall density index , strength index , and combined index . In order to compare the feasibility of the three indexes, One-way analysis of variance and Scheffé’s method were used for in-depth discussion. Based on the proposed assessment indexes, further analyses and recommendations were provided. Results show the combined index has a high potential to predict the damage levels of masonry structures. Based on the study, several recommendations were provided for the masonry structures in seismic-prone zones. Qiwang Su, Gaochuang Cai, and Hervé Degée Copyright © 2017 Qiwang Su et al. All rights reserved. Capacity Fast Prediction and Residual Useful Life Estimation of Valve Regulated Lead Acid Battery Mon, 20 Feb 2017 00:00:00 +0000 The usable capacity of acid lead batteries is often used as the degradation feature for online RUL (residual useful life) estimation. In engineering applications, the “standard” fully discharging method for capacity measure is quite time-consuming and harmful for the high-capacity batteries. In this paper, a data-driven framework providing capacity fast prediction and RUL estimation for high-capacity VRLA (valve regulated lead acid) batteries is presented. These batteries are used as backup power sources on the ships. The relationship between fully discharging time and partially discharging voltage curve is established for usable capacity extrapolation. Based on the predicted capacity, the particle filtering approach is utilized to obtain battery RUL distribution. A case study is conducted with the experimental data of GFM-200 battery. Results confirm that our method not only reduces the prediction time greatly but also performs quite well in prediction accuracy of battery capacity and RUL. Qin He, Yabing Zha, Quan Sun, Zhengqiang Pan, and Tianyu Liu Copyright © 2017 Qin He et al. All rights reserved. Time-Varying Identification Model for Crack Monitoring Data from Concrete Dams Based on Support Vector Regression and the Bayesian Framework Sun, 19 Feb 2017 11:41:08 +0000 The modeling of cracks and identification of dam behavior changes are difficult issues in dam health monitoring research. In this paper, a time-varying identification model for crack monitoring data is built using support vector regression (SVR) and the Bayesian evidence framework (BEF). First, the SVR method is adopted for better modeling of the nonlinear relationship between the crack opening displacement (COD) and its influencing factors. Second, the BEF approach is applied to determine the optimal SVR modeling parameters, including the penalty coefficient, the loss coefficient, and the width coefficient of the radial kernel function, under the principle that the prediction errors between the monitored and the model forecasted values are as small as possible. Then, considering the predicted COD, the historical maximum COD, and the time-dependent component, forewarning criteria are proposed for identifying the time-varying behavior of cracks and the degree of abnormality of dam health. Finally, an example of modeling and forewarning analysis is presented using two monitoring subsequences from a real structural crack in the Chencun concrete arch-gravity dam. The findings indicate that the proposed time-varying model can provide predicted results that are more accurately nonlinearity fitted and is suitable for use in evaluating the behavior of cracks in dams. Bo Chen, Zhongru Wu, Jiachen Liang, and Yanhong Dou Copyright © 2017 Bo Chen et al. All rights reserved. Back Analysis of Geomechanical Parameters of Rock Masses Based on Seepage-Stress Coupled Analysis Sun, 19 Feb 2017 08:04:15 +0000 Given that rock masses are complex, the geomechanical parameters of rock masses are hard to determine in underground engineering. In this paper, the inverse model and method are established to identify the parameters based on the coupled stress and fluid flow model combined with the finite element method and adaptive genetic algorithm. Moreover, the model and method are applied in the Lianghekou highway tunnel, and the initial permeability coefficients of the stratum and the lateral pressure coefficients of the initial ground stress are identified by the back analysis with relative errors of the measured and fitted values at measuring points below 5%. Results show that the inverse model and method are effective and sound. Xianghui Deng, Dongyang Yuan, Dongsheng Yang, and Changsheng Zhang Copyright © 2017 Xianghui Deng et al. All rights reserved. Dynamical Analysis and FPGA Implementation of a Novel Hyperchaotic System and Its Synchronization Using Adaptive Sliding Mode Control and Genetically Optimized PID Control Sun, 19 Feb 2017 07:43:41 +0000 We announce a new 4D hyperchaotic system with four parameters. The dynamic properties of the proposed hyperchaotic system are studied in detail; the Lyapunov exponents, Kaplan-Yorke dimension, bifurcation, and bicoherence contours of the novel hyperchaotic system are derived. Furthermore, control algorithms are designed for the complete synchronization of the identical hyperchaotic systems with unknown parameters using sliding mode controllers and genetically optimized PID controllers. The stabilities of the controllers and parameter update laws are proved using Lyapunov stability theory. Use of the optimized PID controllers ensures less time of convergence and fast synchronization speed. Finally the proposed novel hyperchaotic system is realized in FPGA. Karthikeyan Rajagopal, Laarem Guessas, Sundarapandian Vaidyanathan, Anitha Karthikeyan, and Ashokkumar Srinivasan Copyright © 2017 Karthikeyan Rajagopal et al. All rights reserved. Estimation of Crash Severity on Mountainous Freeways in Chongqing Sun, 19 Feb 2017 06:52:59 +0000 Mountainous freeways always suffer from accidents due to special terrain, weather conditions, driving environment, and so on. Based on the records of 898 accidents that occurred on mountainous freeways in Chongqing during the past 6 years, the partial proportional odds model is used to identify the factors affecting the accident severity. The time of the accident, season, involvement of trucks, accident characteristics, speeding, maximum driving experience of involved drivers, and weather and road conditions are found to be important for the levels of accident severity. Zero to 6 a.m. and 19 to 24 p.m. are the times prone to serious traffic accidents. The probability of serious traffic accidents in summer and autumn is greater than that in spring and winter. Once a truck is involved in an accident, the consequence is often more severe. Turnover and speeding will result in a grave accident. When there is an experienced driver, the probability of serious traffic accidents is low. The fog is extremely unfavorable weather conditions. The probability of serious accident happening in the downgrade, ramp, curve, bridge, and tunnel sections is greater than the others. The results aim to provide valuable reference for traffic safety on mountainous freeways. Yunwei Meng Copyright © 2017 Yunwei Meng. All rights reserved. Facial Expression Recognition from Video Sequences Based on Spatial-Temporal Motion Local Binary Pattern and Gabor Multiorientation Fusion Histogram Sun, 19 Feb 2017 00:00:00 +0000 This paper proposes novel framework for facial expressions analysis using dynamic and static information in video sequences. First, based on incremental formulation, discriminative deformable face alignment method is adapted to locate facial points to correct in-plane head rotation and break up facial region from background. Then, spatial-temporal motion local binary pattern (LBP) feature is extracted and integrated with Gabor multiorientation fusion histogram to give descriptors, which reflect static and dynamic texture information of facial expressions. Finally, a one-versus-one strategy based multiclass support vector machine (SVM) classifier is applied to classify facial expressions. Experiments on Cohn-Kanade (CK) + facial expression dataset illustrate that integrated framework outperforms methods using single descriptors. Compared with other state-of-the-art methods on CK+, MMI, and Oulu-CASIA VIS datasets, our proposed framework performs better. Lei Zhao, Zengcai Wang, and Guoxin Zhang Copyright © 2017 Lei Zhao et al. All rights reserved. Novel SINS Initial Alignment Method under Large Misalignment Angles and Uncertain Noise Based on Nonlinear Filter Sun, 19 Feb 2017 00:00:00 +0000 For the SINS initial alignment problem under large misalignment angles and uncertain noise, two novel nonlinear filters, referred to as transformed unscented quadrature Kalman filter (TUQKF) and robust transformed unscented quadrature Kalman filter (RTUQKF), are proposed in this paper, respectively. The TUQKF sets new deterministic sigma points to address the nonlocal sampling problem and improve the numerical accuracy. The RTUQKF is the combination of technique and TUQKF. It improves the accuracy and robustness of state estimation. Simulation results indicate that TUQKF performs better than traditional filters when misalignment angles are large. Turntable and vehicle experiments results indicate that, under the condition of uncertain noise, the performances of RTUQKF are better than other filters and more robust. These two methods can effectively further increase precision and convergence speed of SINS initial alignment. Bo Yang, Xiaosu Xu, Tao Zhang, Jin Sun, and Xinyu Liu Copyright © 2017 Bo Yang et al. All rights reserved. Decoupling Control for Dual-Winding Bearingless Switched Reluctance Motor Based on Improved Inverse System Method Thu, 16 Feb 2017 00:00:00 +0000 Dual-winding bearingless switched reluctance motor (BSRM) is a multivariable high-nonlinear system characterized by strong coupling, and it is not completely reversible. In this paper, a new decoupling control strategy based on improved inverse system method is proposed. Robust servo regulator is adopted for the decoupled plants to guarantee control performances and robustness. A phase dynamic compensation filter is also designed to improve system stability at high-speed. In order to explain the advantages of the proposed method, traditional methods are compared. The tracking and decoupling characteristics as well as disturbance rejection and robustness are deeply analyzed. Simulation and experiments results show that the decoupling control of dual-winding BSRM in both reversible and irreversible domains can be successfully resolved with the improved inverse system method. The stability and robustness problems induced by inverse controller can be effectively solved by introducing robust servo regulator and dynamic compensation filter. Zhiying Zhu, Yukun Sun, and Ye Yuan Copyright © 2017 Zhiying Zhu et al. All rights reserved. Practical Robust Optimization Method for Unit Commitment of a System with Integrated Wind Resource Thu, 16 Feb 2017 00:00:00 +0000 Unit commitment, one of the significant tasks in power system operations, faces new challenges as the system uncertainty increases dramatically due to the integration of time-varying resources, such as wind. To address these challenges, we propose the formulation and solution of a generalized unit commitment problem for a system with integrated wind resources. Given the prespecified interval information acquired from real central wind forecasting system for uncertainty representation of nodal wind injections with their correlation information, the proposed unit commitment problem solution is computationally tractable and robust against all uncertain wind power injection realizations. We provide a solution approach to tackle this problem with complex mathematical basics and illustrate the capabilities of the proposed mixed integer solution approach on the large-scale power system of the Northwest China Grid. The numerical results demonstrate that the approach is realistic and not overly conservative in terms of the resulting dispatch cost outcomes. Yuanchao Yang Copyright © 2017 Yuanchao Yang. All rights reserved. Procedure to Solve Network DEA Based on a Virtual Gap Measurement Model Wed, 15 Feb 2017 12:48:56 +0000 Network DEA models assess production systems that contain a set of network-structured subsystems. Each subsystem has input and output measures from and to the external network and has intermediate measures that link to other subsystems. Most published studies demonstrate how to employ DEA models to establish network DEA models. Neither static nor dynamic network DEA models adjust the links. This paper applies the virtual gap measurement (VGM) model to construct a mixed integer program to solve dynamic network DEA problems. The mixed integer program sets the total numbers of “as-input” and “as-output” equal to the total number of links in the objective function. To obtain the best-practice efficiency, each DMU determines a set of weights for inputs, outputs, and links. The links are played either “as-input” or “as-output.” Input and as-input measures reduce slack, whereas output and as-output measures increase slacks to attain their target on the production frontier. Fuh-hwa Franklin Liu and Yu-cheng Liu Copyright © 2017 Fuh-hwa Franklin Liu and Yu-cheng Liu. All rights reserved.