Mathematical Problems in Engineering The latest articles from Hindawi Publishing Corporation © 2014 , Hindawi Publishing Corporation . All rights reserved. A Novel Method Based on Oblique Projection Technology for Mixed Sources Estimation Thu, 23 Oct 2014 12:40:28 +0000 Reducing the computational complexity of the near-field sources and far-field sources localization algorithms has been considered as a serious problem in the field of array signal processing. A novel algorithm caring for mixed sources location estimation based on oblique projection is proposed in this paper. The sources are estimated at two different stages and the sensor noise power is estimated and eliminated from the covariance which improve the accuracy of the estimation of mixed sources. Using the idea of compress, the range information of near-field sources is obtained by searching the partial area instead of the whole Fresnel area which can reduce the processing time. Compared with the traditional algorithms, the proposed algorithm has the lower computation complexity and has the ability to solve the two closed-spaced sources with high resolution and accuracy. The duplication of range estimation is also avoided. Finally, simulation results are provided to demonstrate the performance of the proposed method. Weijian Si, Xiaolin Li, Yilin Jiang, and Liangtian Wan Copyright © 2014 Weijian Si et al. All rights reserved. Selection Ideal Coal Suppliers of Thermal Power Plants Using the Matter-Element Extension Model with Integrated Empowerment Method for Sustainability Thu, 23 Oct 2014 11:50:36 +0000 In order to reduce thermal power generation cost and improve its market competitiveness, considering fuel quality, cost, creditworthiness, and sustainable development capacity factors, this paper established the evaluation system for coal supplier selection of thermal power and put forward the coal supplier selection strategies for thermal power based on integrated empowering and ideal matter-element extension models. On the one hand, the integrated empowering model can overcome the limitations of subjective and objective methods to determine weights, better balance subjective, and objective information. On the other hand, since the evaluation results of the traditional element extension model may fall into the same class and only get part of the order results, in order to overcome this shortcoming, the idealistic matter-element extension model is constructed. It selects the ideal positive and negative matter-elements classical field and uses the closeness degree to replace traditional maximum degree of membership criterion and calculates the positive or negative distance between the matter-element to be evaluated and the ideal matter-element; then it can get the full order results of the evaluation schemes. Simulated and compared with the TOPSIS method, Romania selection method, and PROMETHEE method, numerical example results show that the method put forward by this paper is effective and reliable. Zhongfu Tan, Liwei Ju, Xiaobao Yu, Huijuan Zhang, and Chao Yu Copyright © 2014 Zhongfu Tan et al. All rights reserved. An Efficient Hierarchy Algorithm for Community Detection in Complex Networks Thu, 23 Oct 2014 09:16:26 +0000 Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time-varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine-grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too. Lili Zhang, Qing Ye, Yehong Shao, Chenming Li, and Hongmin Gao Copyright © 2014 Lili Zhang et al. All rights reserved. Modelling of Lime Kiln Using Subspace Method with New Order Selection Criterion Thu, 23 Oct 2014 06:20:37 +0000 This paper is taking actual control demand of rotary kiln as background and builds a calcining belt state space model using PO-Moesp subspace method. A novel order-delay double parameters error criterion (ODC) is presented to reduce the modeling order. The proposed subspace order identification method takes into account the influence of order and delay on model error criterion simultaneously. For the introduction of the delay factors, the order is reduced dramatically in the system modeling. Also, in the data processing part sliding-window method is adopted for stripping delay factor from historical data. For this, the parameters can be changed flexibly. Some practical problems in industrial kiln process modeling are also solved. Finally, it is applied to an industrial kiln case. Li Zhang, Chengjin Zhang, Qingyang Xu, and Chaoyang Wang Copyright © 2014 Li Zhang et al. All rights reserved. Vehicle Velocity and Roll Angle Estimation with Road and Friction Adaptation for Four-Wheel Independent Drive Electric Vehicle Wed, 22 Oct 2014 00:00:00 +0000 Vehicle velocity and roll angle are important information for active safety control systems of four-wheel independent drive electric vehicle. In order to obtain robustness estimation of vehicle velocity and roll angle, a novel method is proposed based on vehicle dynamics and the measurement information provided by the sensors equipped in modern cars. The method is robust with respect to different road and friction conditions. Firstly, the dynamic characteristics of four-wheel independent drive electric vehicle are analyzed, and a four-degree-of-freedom nonlinear dynamic model of vehicle and a tire longitudinal dynamic equation are established. The relationship between the longitudinal and lateral friction forces is derived based on Dugoff tire model. The unknown input reconstruction technique of sliding mode observer is used to achieve longitudinal tire friction force estimation. A simple observer is designed for the estimation of the roll angle of the vehicle. And then using the relationship, the estimated longitudinal friction forces and roll angle, a sliding mode observer for vehicle velocity estimation is provided, which does not need to know the tire-road friction coefficient and road angles. Finally, the proposed method is evaluated experimentally under a variety of maneuvers and road conditions. Linhui Zhao and Zhiyuan Liu Copyright © 2014 Linhui Zhao and Zhiyuan Liu. All rights reserved. Random Forest Based Coarse Locating and KPCA Feature Extraction for Indoor Positioning System Wed, 22 Oct 2014 00:00:00 +0000 With the fast developing of mobile terminals, positioning techniques based on fingerprinting method draw attention from many researchers even world famous companies. To conquer some shortcomings of the existing fingerprinting systems and further improve the system performance, on the one hand, in the paper, we propose a coarse positioning method based on random forest, which is able to customize several subregions, and classify test point to the region with an outstanding accuracy compared with some typical clustering algorithms. On the other hand, through the mathematical analysis in engineering, the proposed kernel principal component analysis algorithm is applied for radio map processing, which may provide better robustness and adaptability compared with linear feature extraction methods and manifold learning technique. We build both theoretical model and real environment for verifying the feasibility and reliability. The experimental results show that the proposed indoor positioning system could achieve 99% coarse locating accuracy and enhance 15% fine positioning accuracy on average in a strong noisy environment compared with some typical fingerprinting based methods. Yun Mo, Zhongzhao Zhang, Yang Lu, Weixiao Meng, and Gul Agha Copyright © 2014 Yun Mo et al. All rights reserved. Variational Level Set Method for Two-Stage Image Segmentation Based on Morphological Gradients Tue, 21 Oct 2014 13:48:09 +0000 We use variational level set method and transition region extraction techniques to achieve image segmentation task. The proposed scheme is done by two steps. We first develop a novel algorithm to extract transition region based on the morphological gradient. After this, we integrate the transition region into a variational level set framework and develop a novel geometric active contour model, which include an external energy based on transition region and fractional order edge indicator function. The external energy is used to drive the zero level set toward the desired image features, such as object boundaries. Due to this external energy, the proposed model allows for more flexible initialization. The fractional order edge indicator function is incorporated into the length regularization term to diminish the influence of noise. Moreover, internal energy is added into the proposed model to penalize the deviation of the level set function from a signed distance function. The results evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed model has been applied to both synthetic and real images with promising results. Zemin Ren Copyright © 2014 Zemin Ren. All rights reserved. An Efficient Approach for Solving Mesh Optimization Problems Using Newton’s Method Tue, 21 Oct 2014 13:45:04 +0000 We present an efficient approach for solving various mesh optimization problems. Our approach is based on Newton’s method, which uses both first-order (gradient) and second-order (Hessian) derivatives of the nonlinear objective function. The volume and surface mesh optimization algorithms are developed such that mesh validity and surface constraints are satisfied. We also propose several Hessian modification methods when the Hessian matrix is not positive definite. We demonstrate our approach by comparing our method with nonlinear conjugate gradient and steepest descent methods in terms of both efficiency and mesh quality. Jibum Kim Copyright © 2014 Jibum Kim. All rights reserved. Three-Dimensional Stability Analysis of a Homogeneous Slope Reinforced with Micropiles Tue, 21 Oct 2014 09:46:33 +0000 Micropiles are widely used to reinforce slopes due to their successful performance and fast construction. In this study, a simple nonlinear method is proposed to analyze the stability of a homogeneous slope reinforced with micropiles. This method is based on shear strength reduction technique, in which the soil behavior is described using the nonassociated Mohr-Coulomb criterion and micropiles are modeled as 3D pile elements. A series of slope stability analyses is performed to investigate the coupled mechanism of micropile system, and the optimum of pile position, depth of embedment, and length of truncation are analyzed. Results show that the position of micropile system plays an important role not only in the calculation of the safety factor, but also in locating the failure surface, which demonstrates the dominating coupled effect exists between micropiles and slope. The critical embedment depth of the micropile is about 2 times the length of micropile above the critical slip surface, and the micropiles flexure rather than rotation becomes increasingly prevalent as the depth of micropiles embedment increases. Truncation of micropiles may improve the capacity of the micropile system, and the largest truncation length of micropile is about 1/4 depth of critical slip surface in this study. Shu-Wei Sun, Wei Wang, and Fu Zhao Copyright © 2014 Shu-Wei Sun et al. All rights reserved. Classification Identification of Acoustic Emission Signals from Underground Metal Mine Rock by ICIMF Classifier Tue, 21 Oct 2014 09:46:15 +0000 To overcome the drawback that fuzzy classifier was sensitive to noises and outliers, Mamdani fuzzy classifier based on improved chaos immune algorithm was developed, in which bilateral Gaussian membership function parameters were set as constraint conditions and the indexes of fuzzy classification effectiveness and number of correct samples of fuzzy classification as the subgoal of fitness function. Moreover, Iris database was used for simulation experiment, classification, and recognition of acoustic emission signals and interference signals from stope wall rock of underground metal mines. The results showed that Mamdani fuzzy classifier based on improved chaos immune algorithm could effectively improve the prediction accuracy of classification of data sets with noises and outliers and the classification accuracy of acoustic emission signal and interference signal from stope wall rock of underground metal mines was 90.00%. It was obvious that the improved chaos immune Mamdani fuzzy (ICIMF) classifier was useful for accurate diagnosis of acoustic emission signal and interference signal from stope wall rock of underground metal mines. Hongyan Zuo, Zhouquan Luo, and Chao Wu Copyright © 2014 Hongyan Zuo et al. All rights reserved. Accurate Object Recognition with Assembling Appearance and Motion Information Tue, 21 Oct 2014 09:25:06 +0000 How to effectively detect object and accurately give out its visible parts is a major challenge for object detection. In this paper we propose an explicit occlusion model through integrating appearance and motion information. The model combines together two parts: part-level object detection with single frame and object occlusion estimation with continuous frames. It breaks through the performance bottleneck caused by lack of information and effectively improves object detection rate under severe occlusion. Through reevaluating the semantic parts, the detecting performance of partial object detectors is largely enhanced. The explicit model enables the partial detectors to have the capability of occlusion estimation. By discarding the geometric representation in rigid single-angle perspective and applying effective pattern of objective shape, our proposed approaches greatly improve the performance and robustness of similarity measurement. For validating the performance of proposed methods, we designed a comparative experiment on challenging pedestrian frame sequences database. The experimental results on challenging pedestrian frame sequence demonstrate that, compared to the traditional algorithms, the methods proposed in this paper have significantly improved the detection rate for severe occlusion. Furthermore, it also can achieve better localization of semantic parts and estimation of occluding. Yongxin Chang, Huapeng Yu, Zhiyong Xu, Jing Zhang, and Chunming Gao Copyright © 2014 Yongxin Chang et al. All rights reserved. A Greedy Multistage Convex Relaxation Algorithm Applied to Structured Group Sparse Reconstruction Problems Based on Iterative Support Detection Tue, 21 Oct 2014 09:02:43 +0000 We propose a new effective algorithm for recovering a group sparse signal from very limited observations or measured data. As we know that a better reconstruction quality can be achieved when encoding more structural information besides sparsity, the commonly employed -regularization incorporating the prior grouping information has a better performance than the plain -regularized models as expected. In this paper we make a further use of the prior grouping information as well as possibly other prior information by considering a weighted model. Specifically, we propose a multistage convex relaxation procedure to alternatively estimate weights and solve the resulted weighted problem. The procedure of estimating weights makes better use of the prior grouping information and is implemented based on the iterative support detection (Wang and Yin, 2010). Comprehensive numerical experiments show that our approach brings significant recovery enhancements compared with the plain model, solved via the alternating direction method (ADM) (Deng et al., 2013), either in noiseless or in noisy environments. Liangtian He and Yilun Wang Copyright © 2014 Liangtian He and Yilun Wang. All rights reserved. Green Clustering Implementation Based on DPS-MOPSO Tue, 21 Oct 2014 06:40:47 +0000 A green clustering implementation is proposed to be as the first method in the framework of an energy-efficient strategy for centralized enterprise high-density WLANs. Traditionally, to maintain the network coverage, all of the APs within the WLAN have to be powered on. Nevertheless, the new algorithm can power off a large proportion of APs while the coverage is maintained as the always-on counterpart. The proposed algorithm is composed of two parallel and concurrent procedures, which are the faster procedure based on -means and the more accurate procedure based on Dynamic Population Size Multiple Objective Particle Swarm Optimization (DPS-MOPSO). To implement green clustering efficiently and accurately, dynamic population size and mutational operators are introduced as complements for the classical MOPSO. In addition to the function of AP selection, the new green clustering algorithm has another new function as the reference and guidance for AP deployment. This paper also presents simulations in scenarios modeled with ray-tracing method and FDTD technique, and the results show that about 67% up to 90% of energy consumption can be saved while the original network coverage is maintained during periods when few users are online or when the traffic load is low. Yang Lu, Xuezhi Tan, Yun Mo, and Lin Ma Copyright © 2014 Yang Lu et al. All rights reserved. Effective Volumetric Feature Modeling and Coarse Correspondence via Improved 3DSIFT and Spectral Matching Mon, 20 Oct 2014 07:03:50 +0000 This paper presents a nonrigid coarse correspondence computation algorithm for volumetric images. Our matching algorithm first extracts then correlates image features based on a revised and improved 3DSIFT (I3DSIFT) algorithm. With a scale-related keypoint reorientation and descriptor construction, this feature correlation is less sensitive to image rotation and scaling. Then, we present an improved spectral matching (ISM) algorithm on correlated features to obtain a one-to-one mapping between corresponded features. One can effectively extend this feature correspondence to dense correspondence between volume images. Our algorithm can benefit nonrigid volumetric image registration in many tasks such as motion modeling in medical image analysis and processing. Peizhi Chen and Xin Li Copyright © 2014 Peizhi Chen and Xin Li. All rights reserved. Multiscale Probability Transformation of Basic Probability Assignment Mon, 20 Oct 2014 06:41:43 +0000 Decision making is still an open issue in the application of Dempster-Shafer evidence theory. A lot of works have been presented for it. In the transferable belief model (TBM), pignistic probabilities based on the basic probability assignments are used for decision making. In this paper, multiscale probability transformation of basic probability assignment based on the belief function and the plausibility function is proposed, which is a generalization of the pignistic probability transformation. In the multiscale probability function, a factor q based on the Tsallis entropy is used to make the multiscale probabilities diversified. An example showing that the multiscale probability transformation is more reasonable in the decision making is given. Meizhu Li, Xi Lu, Qi Zhang, and Yong Deng Copyright © 2014 Meizhu Li et al. All rights reserved. Identification of Nonlinear Dynamic Systems Using Hammerstein-Type Neural Network Sun, 19 Oct 2014 11:14:42 +0000 Hammerstein model has been popularly applied to identify the nonlinear systems. In this paper, a Hammerstein-type neural network (HTNN) is derived to formulate the well-known Hammerstein model. The HTNN consists of a nonlinear static gain in cascade with a linear dynamic part. First, the Lipschitz criterion for order determination is derived. Second, the backpropagation algorithm for updating the network weights is presented, and the stability analysis is also drawn. Finally, simulation results show that HTNN identification approach demonstrated identification performances. Hongshan Yu, Jinzhu Peng, and Yandong Tang Copyright © 2014 Hongshan Yu et al. All rights reserved. Facial Expression Recognition Based on Discriminant Neighborhood Preserving Nonnegative Tensor Factorization and ELM Sun, 19 Oct 2014 11:13:47 +0000 A novel facial expression recognition algorithm based on discriminant neighborhood preserving nonnegative tensor factorization (DNPNTF) and extreme learning machine (ELM) is proposed. A discriminant constraint is adopted according to the manifold learning and graph embedding theory. The constraint is useful to exploit the spatial neighborhood structure and the prior defined discriminant properties. The obtained parts-based representations by our algorithm vary smoothly along the geodesics of the data manifold and have good discriminant property. To guarantee the convergence, the project gradient method is used for optimization. Then features extracted by DNPNTF are fed into ELM which is a training method for the single hidden layer feed-forward networks (SLFNs). Experimental results on JAFFE database and Cohn-Kanade database demonstrate that our proposed algorithm could extract effective features and have good performance in facial expression recognition. Gaoyun An, Shuai Liu, Yi Jin, Qiuqi Ruan, and Shan Lu Copyright © 2014 Gaoyun An et al. All rights reserved. Study and Application on Stability Classification of Tunnel Surrounding Rock Based on Uncertainty Measure Theory Sun, 19 Oct 2014 00:00:00 +0000 Based on uncertainty measure theory, a stability classification and order-arranging model of surrounding rock was established. Considering the practical engineering geologic condition, 5 factors that influence surrounding rock stability were taken into account and uncertainty measure function was obtained based on the in situ data. In this model, uncertainty influence factors were analyzed quantitatively and qualitatively based on the real situation; the weight of index was given based on information entropy theory; surrounding rock stability level was judged based on credible degree recognition criterion; and surrounding rock was ordered based on order-arranging criterion. Furthermore, this model was employed to evaluate 5 sections surrounding rock in Dongshan tunnel of Huainan. The results show that uncertainty measure method is reasonable and can have significance for surrounding rock stability evaluation in the future. Hujun He, Yumei Yan, Cuixia Qu, and Yue Fan Copyright © 2014 Hujun He et al. All rights reserved. A Pan-Function Model for the Utilization of Bandwidth Improvement and PAPR Reduction Sun, 19 Oct 2014 00:00:00 +0000 Aiming at the digital quadrature modulation system, a mathematical Pan-function model of the optimized baseband symbol signals with a symbol length of was established in accordance with the minimum out-band energy radiation criterion. The intersymbol interference (ISI), symbol-correlated characteristics, and attenuation factor were introduced to establish the mathematical Pan-function model. The Pan-function was added to the constraints of boundary conditions, energy of a single baseband symbol signal, and constant-envelope conditions. Baseband symbol signals with the optimum efficient spectrum were obtained by introducing Fourier series and minimizing the Pan-function. The characteristics of the spectrum and peak-to-average power ratio (PAPR) of the obtained signals were analyzed and compared with the minimum shift keying (MSK) and quadrature phase-shift keying (QPSK) signals. The obtained signals have the characteristics of a higher spectral roll-off rate, less out-band radiation, and quasi-constant envelope. We simulated the performance of the obtained signals, and the simulation results demonstrate that the method is feasible. Yidong Xu, Wei Xue, and Wenjing Shang Copyright © 2014 Yidong Xu et al. All rights reserved. A Novel Mobile Personalized Recommended Method Based on Money Flow Model for Stock Exchange Thu, 16 Oct 2014 13:31:27 +0000 Personalized recommended method is widely used to recommend commodities for target customers in e-commerce sector. The core idea of merchandise personalized recommendation can be applied to financial field, which can also achieve stock personalized recommendation. This paper proposes a new recommended method using collaborative filtering based on user fuzzy clustering and predicts the trend of those stocks based on money flow. We use M/G/1 queue system with multiple vacations and server close-down time to measure practical money flow. Based on the indicated results of money flow, we can select the more valued stock to recommend to investors. The experimental results show that the proposed method provides investors with reliable practical investment guidance and receiving more returns. Qingzhen Xu, Jiayong Wu, and Qiang Chen Copyright © 2014 Qingzhen Xu et al. All rights reserved. Reinforced Ultra-Tightly Coupled GPS/INS System for Challenging Environment Thu, 16 Oct 2014 10:03:09 +0000 Among all integration levels currently available for Global Positioning System (GPS) and Inertial Navigation System (INS) Integrated System, ultra-tightly coupled (UTC) GPS/INS system is the best choice for accurate and reliable navigation. Nevertheless the performance of UTC GPS/INS system degrades in challenging environments, such as jamming, changing noise of GPS signals, and high dynamic maneuvers. When low-end Inertial Measurement Units (IMUs) based on MEMS sensors are employed, the performance degradation will be more severe. To solve this problem, a reinforced UTC GPS/INS system is proposed. Two techniques are adopted to deal with jamming and high dynamics. Firstly, adaptive integration Kalman filter (IKF) based on fuzzy logics is developed to reinforce the antijamming ability. The parameters of membership functions (MFs) are adjusted and optimized through self-developed neutral network. Secondly, a Doppler frequency error estimator based on Kalman filter is designed to improve the navigation performance under high dynamics. A complete simulation platform is established to evaluate the reinforced system. Results demonstrate that the proposed system architecture significantly improves navigation performance in challenging environments and it is a more advanced solution to accurate and reliable navigation than traditional UTC GPS/INS system. Xueyun Wang, Kui Li, Pengyu Gao, and Wei Wang Copyright © 2014 Xueyun Wang et al. All rights reserved. Adaptive Fuzzy Containment Control for Uncertain Nonlinear Multiagent Systems Thu, 16 Oct 2014 07:10:28 +0000 This paper considers the containment control problem for uncertain nonlinear multiagent systems under directed graphs. The followers are governed by nonlinear systems with unknown dynamics while the multiple leaders are neighbors of a subset of the followers. Fuzzy logic systems (FLSs) are used to identify the unknown dynamics and a distributed state feedback containment control protocol is proposed. This result is extended to the output feedback case, where observers are designed to estimate the unmeasurable states. Then, an output feedback containment control scheme is presented. The developed state feedback and output feedback containment controllers guarantee that the states of all followers converge to the convex hull spanned by the dynamic leaders. Based on Lyapunov stability theory, it is proved that the containment control errors are uniformly ultimately bounded (UUB). An example is provided to show the effectiveness of the proposed control method. Yang Yu and Kang-Hyun Jo Copyright © 2014 Yang Yu and Kang-Hyun Jo. All rights reserved. Indefinite LQ Problem for Irregular Singular Systems Thu, 16 Oct 2014 06:23:51 +0000 The indefinite LQ problem for irregular singular systems is investigated. Under some general conditions, the optimal control-state pair is obtained by solving an algebraic Riccati equation. The optimal control is synthesized as state feedback. All the finite poles of the closed-loop system are located on the left-half complex plane. An example is given to show the validity of the proposed conclusion. Qingxiang Fang, Jigen Peng, and Feilong Cao Copyright © 2014 Qingxiang Fang et al. All rights reserved. Filtering Based Recursive Least Squares Algorithm for Multi-Input Multioutput Hammerstein Models Thu, 16 Oct 2014 00:00:00 +0000 This paper considers the parameter estimation problem for Hammerstein multi-input multioutput finite impulse response (FIR-MA) systems. Filtered by the noise transfer function, the FIR-MA model is transformed into a controlled autoregressive model. The key-term variable separation principle is used to derive a data filtering based recursive least squares algorithm. The numerical examples confirm that the proposed algorithm can estimate parameters more accurately and has a higher computational efficiency compared with the recursive least squares algorithm. Ziyun Wang, Yan Wang, and Zhicheng Ji Copyright © 2014 Ziyun Wang et al. All rights reserved. Quadrant Dynamic with Automatic Plateau Limit Histogram Equalization for Image Enhancement Wed, 15 Oct 2014 07:43:57 +0000 The fundamental and important preprocessing stage in image processing is the image contrast enhancement technique. Histogram equalization is an effective contrast enhancement technique. In this paper, a histogram equalization based technique called quadrant dynamic with automatic plateau limit histogram equalization (QDAPLHE) is introduced. In this method, a hybrid of dynamic and clipped histogram equalization methods are used to increase the brightness preservation and to reduce the overenhancement. Initially, the proposed QDAPLHE algorithm passes the input image through a median filter to remove the noises present in the image. Then the histogram of the filtered image is divided into four subhistograms while maintaining second separated point as the mean brightness. Then the clipping process is implemented by calculating automatically the plateau limit as the clipped level. The clipped portion of the histogram is modified to reduce the loss of image intensity value. Finally the clipped portion is redistributed uniformly to the entire dynamic range and the conventional histogram equalization is executed in each subhistogram independently. Based on the qualitative and the quantitative analysis, the QDAPLHE method outperforms some existing methods in literature. P. Jagatheeswari, S. Suresh Kumar, and M. Mary Linda Copyright © 2014 P. Jagatheeswari et al. All rights reserved. Loss-Averse Retailer’s Optimal Ordering Policies for Perishable Products with Customer Returns Wed, 15 Oct 2014 06:06:11 +0000 We investigate the loss-averse retailer’s ordering policies for perishable product with customer returns. With the introduction of the segmental loss utility function, we depict the retailer’s loss aversion decision bias and establish the loss-averse retailer’s ordering policy model. We derive that the loss-averse retailer’s optimal order quantity with customer returns exists and is unique. By comparison, we obtain that both the risk-neutral and the loss-averse retailer’s optimal order quantities depend on the inventory holding cost and the marginal shortage cost. Through the sensitivity analysis, we also discuss the effect of loss-averse coefficient and the ratio of return on the loss-averse retailer’s optimal order quantity with customer returns. Xu Chen and Qian Zhou Copyright © 2014 Xu Chen and Qian Zhou. All rights reserved. Clustering Networks’ Heterogeneous Data in Defining a Comprehensive Closeness Centrality Index Wed, 15 Oct 2014 00:00:00 +0000 One of the most important applications of network analysis is detecting community structure, or clustering. Nearly all algorithms that are used to identify these structures use information derived from the topology of these networks, such as adjacency and distance relationships, and assume that there is only one type of relation in the network. However, in reality, there are multilayer networks, with each layer representing a particular type of relationship that contains nodes with individual characteristics that may influence the behavior of networks. This paper introduces a new, efficient spectral approach for detecting the communities in multilayer networks using the concept of hybrid clustering, which integrates multiple data sources, particularly the structure of relations and individual characteristics of nodes in a network, to improve the comprehension of the network and the clustering accuracy. Furthermore, we develop a new algorithm to define the closeness centrality measure in complex networks based on a combination of two approaches: social network analysis and traditional social science approach. We evaluate the performance of our proposed method using four benchmark datasets and a real-world network: oil global trade network. The experimental results indicated that our hybrid method is sufficiently effective at clustering using the node attributes and network structure. Farnaz Barzinpour, B. Hoda Ali-Ahmadi, Somayeh Alizadeh, and S. Golamreza Jalali Naini Copyright © 2014 Farnaz Barzinpour et al. All rights reserved. A Note about the General Meromorphic Solutions of the Fisher Equation Tue, 14 Oct 2014 09:03:00 +0000 We employ the complex method to obtain the general meromorphic solutions of the Fisher equation, which improves the corresponding results obtained by Ablowitz and Zeppetella and other authors (Ablowitz and Zeppetella, 1979; Feng and Li, 2006; Guo and Chen, 1991), and are new general meromorphic solutions of the Fisher equation for Our results show that the complex method provides a powerful mathematical tool for solving great many nonlinear partial differential equations in mathematical physics. Jian-ming Qi, Qiu-hui Chen, Wei-ling Xiong, and Wen-jun Yuan Copyright © 2014 Jian-ming Qi et al. All rights reserved. Boundary Value Problems of Potential Functions in Decagonal Quasicrystals Tue, 14 Oct 2014 08:23:56 +0000 A unified form of potential functions in decagonal quasicrystals (QCs) and conformal mappings are applied in a novel way to solve the boundary value problems emanating from the generalized theory of elasticity for decagonal QCs. By executing the reduction of boundary value problem to function equations, two crack problems are investigated. In the first one, an approximate analysis for bending specimen with a crack is given. In the other, a finite width strip with single edge crack of decagonal QCs is analytically estimated. Using the basic idea underlying Dugdale’s crack model, the extent of cohesive force zone in each of the two cases is analytically derived. Wu Li, Hao Xin, and Tianyou Fan Copyright © 2014 Wu Li et al. All rights reserved. Multiattribute Grey Target Decision Method Based on Soft Set Theory Tue, 14 Oct 2014 00:00:00 +0000 With respect to the Multiattribute decision-making problems in which the evaluation attribute sets are different and the evaluating values of alternatives are interval grey numbers, a multiattribute grey target decision-making method in which the attribute sets are different was proposed. The concept of grey soft set was defined, and its “AND” operation was assigned by combining the intersection operation of grey number. The expression approach of new grey soft set of attribute sets considering by all decision makers were gained by applying the “AND” operation of grey soft set, and the weights of synthesis attribute were proved. The alternatives were ranked according to the size of distance of bull’s eyes of each alternative under synthetic attribute sets. The green supplier selection was illustrated to demonstrate the effectiveness of proposed model. Xia Wang, Yaoguo Dang, and Diqing Hou Copyright © 2014 Xia Wang et al. All rights reserved.