Mathematical Problems in Engineering The latest articles from Hindawi Publishing Corporation © 2014 , Hindawi Publishing Corporation . All rights reserved. Local Stabilization of Time-Delay Nonlinear Discrete-Time Systems Using Takagi-Sugeno Models and Convex Optimization Wed, 20 Aug 2014 08:03:17 +0000 A convex condition in terms of linear matrix inequalities (LMIs) is developed for the synthesis of stabilizing fuzzy state feedback controllers for nonlinear discrete-time systems with time-varying delays. A Takagi-Sugeno (T-S) fuzzy model is used to represent exactly the nonlinear system in a restricted domain of the state space, called region of validity. The proposed stabilization condition is based on a Lyapunov-Krasovskii (L-K) function and it takes into account the region of validity to determine a set of initial conditions for which the actual closed-loop system trajectories are asymptotically stable and do not evolve outside the region of validity. This set of allowable initial conditions is determined from the level set associated to a fuzzy L-K function as a Cartesian product of two subsets: one characterizing the set of states at the initial instant and another for the delayed state sequence necessary to characterize the initial conditions. Finally, we propose a convex programming problem to design a fuzzy controller that maximizes the set of initial conditions taking into account the shape of the region of validity of the T-S fuzzy model. Numerical simulations are given to illustrate this proposal. Luís F. P. Silva, Valter J. S. Leite, Eugênio B. Castelan, and Michael Klug Copyright © 2014 Luís F. P. Silva et al. All rights reserved. Compression of Multispectral Images with Comparatively Few Bands Using Posttransform Tucker Decomposition Wed, 20 Aug 2014 07:28:24 +0000 Up to now, data compression for the multispectral charge-coupled device (CCD) images with comparatively few bands (MSCFBs) is done independently on each multispectral channel. This compression codec is called a “monospectral compressor.” The monospectral compressor does not have a removing spectral redundancy stage. To fill this gap, we propose an efficient compression approach for MSCFBs. In our approach, the one dimensional discrete cosine transform (1D-DCT) is performed on spectral dimension to exploit the spectral information, and the posttransform (PT) in 2D-DWT domain is performed on each spectral band to exploit the spatial information. A deep coupling approach between the PT and Tucker decomposition (TD) is proposed to remove residual spectral redundancy between bands and residual spatial redundancy of each band. Experimental results on multispectral CCD camera data set show that the proposed compression algorithm can obtain a better compression performance and significantly outperforms the traditional compression algorithm-based TD in 2D-DWT and 3D-DCT domain. Jin Li, Fei Xing, and Zheng You Copyright © 2014 Jin Li et al. All rights reserved. An Inversely Designed Model for Calculating Pull-In Limit and Position of Electrostatic Fixed-Fixed Beam Actuators Wed, 20 Aug 2014 07:23:04 +0000 This study presents an inverse approach to obtain a relation between applied voltage and displacement of the midpoint of fixed-fixed beam actuator. The approach has two main sections. The first one is the inverse design of a model to replace real action of upper beam under electrostatic force. The formula obtained from the first section does not comprise the residual stress and gives very small errors when there is no residual stress on the upper electrode. So, the second part was carried out to add this important system variable into the formula. Likewise, inverse solution was again applied in the later section. The final formula demonstrates that pull-in limit of clamped-clamped actuator is to be at around 40% of original spacing that is in agreement with simulation and previous experimental results. Its percentage errors are within 2% when compared with simulations that are based on finite element method (FEM). The results are comparable to numerical solutions received from diverse distributed models which require more calculation power in electrostatic and structural domains. On top of that, our formula is valid for all displacements from original position up to pull-in limit. Cevher Ak and Ali Yildiz Copyright © 2014 Cevher Ak and Ali Yildiz. All rights reserved. Risk Stratification with Extreme Learning Machine: A Retrospective Study on Emergency Department Patients Wed, 20 Aug 2014 06:48:28 +0000 This paper presents a novel risk stratification method using extreme learning machine (ELM). ELM was integrated into a scoring system to identify the risk of cardiac arrest in emergency department (ED) patients. The experiments were conducted on a cohort of 1025 critically ill patients presented to the ED of a tertiary hospital. ELM and voting based ELM (V-ELM) were evaluated. To enhance the prediction performance, we proposed a selective V-ELM (SV-ELM) algorithm. The results showed that ELM based scoring methods outperformed support vector machine (SVM) based scoring method in the receiver operation characteristic analysis. Nan Liu, Jiuwen Cao, Zhi Xiong Koh, Pin Pin Pek, and Marcus Eng Hock Ong Copyright © 2014 Nan Liu et al. All rights reserved. Grain Emergency Vehicle Scheduling Problem with Time and Demand Uncertainty Wed, 20 Aug 2014 05:22:32 +0000 Grain transportation plays an important role in many relief and emergency supply chains. In this paper, we take the grain emergency vehicle scheduling model between multiwarehouses as the research object. Under the emergency environment, the aim of the problem is to maximize the utilization of vehicles and minimize the delay time. The randomness of the key parameters in grain emergency vehicle scheduling, such as time and demand, is determined through statistical analysis and the model is solved through robust optimization method. Besides, we apply the numerical examples for experimental analysis. We compare the robust optimization model with classic model to illustrate the differences and similarities between them. The results show that the uncertainty of both time and demand has great influence on the efficiency of grain emergency vehicle scheduling problem. Jiang DongQing and Zhu QunXiong Copyright © 2014 Jiang DongQing and Zhu QunXiong. All rights reserved. A Novel Approach to Developing a Supervised Spatial Decision Support System for Image Classification: A Study of Paddy Rice Investigation Wed, 20 Aug 2014 00:00:00 +0000 Paddy rice area estimation via remote sensing techniques has been well established in recent years. Texture information and vegetation indicators are widely used to improve the classification accuracy of satellite images. Accordingly, this study employs texture information and vegetation indicators as ancillary information for classifying paddy rice through remote sensing images. In the first stage, the images are attained using a remote sensing technique and ancillary information is employed to increase the accuracy of classification. In the second stage, we decide to construct an efficient supervised classifier, which is used to evaluate the ancillary information. In the third stage, linear discriminant analysis (LDA) is introduced. LDA is a well-known method for classifying images to various categories. Also, the particle swarm optimization (PSO) algorithm is employed to optimize the LDA classification outcomes and increase classification performance. In the fourth stage, we discuss the strategy of selecting different window sizes and analyze particle numbers and iteration numbers with corresponding accuracy. Accordingly, a rational strategy for the combination of ancillary information is introduced. Afterwards, the PSO algorithm improves the accuracy rate from 82.26% to 89.31%. The improved accuracy results in a much lower salt-and-pepper effect in the thematic map. Shih-Hsun Chang Copyright © 2014 Shih-Hsun Chang. All rights reserved. Classification System of Pathological Voices Using Correntropy Tue, 19 Aug 2014 12:47:53 +0000 This paper proposes the use of a similarity measure based on information theory called correntropy for the automatic classification of pathological voices. By using correntropy, it is possible to obtain descriptors that aggregate distinct spectral characteristics for healthy and pathological voices. Experiments using computational simulation demonstrate that such descriptors are very efficient in the characterization of vocal dysfunctions, leading to a success rate of 97% in the classification. With this new architecture, the classification process of vocal pathologies becomes much more simple and efficient. Aluisio I. R. Fontes, Pedro T. V. Souza, Adrião D. D. Neto, Allan de M. Martins, and Luiz F. Q. Silveira Copyright © 2014 Aluisio I. R. Fontes et al. All rights reserved. Ubi-RKE: A Rhythm Key Based Encryption Scheme for Ubiquitous Devices Tue, 19 Aug 2014 08:36:07 +0000 As intelligent ubiquitous devices become more popular, security threats targeting them are increasing; security is seen as one of the major challenges of the ubiquitous computing. Now a days, applying ubiquitous computing in number of fields for human safety and convenience was immensely increased in recent years. The popularity of the technology is rising day by day, and hence the security is becoming the main focused point with the advent and rising popularity of the applications. In particular, the number of wireless networks based on ubiquitous devices has increased rapidly; these devices support transmission for many types of data traffic. The convenient portability of ubiquitous devices makes them vulnerable to security threats, such as loss, theft, data modification, and wiretapping. Developers and users should seriously consider employing data encryption to protect data from such vulnerabilities. In this paper, we propose a Rhythm Key based Encryption scheme for ubiquitous devices (Ubi-RKE). The concept of Rhythm Key based Encryption has been applied to numerous real world applications in different domains. It provides key memorability and secure encryption through user touching rhythm on ubiquitous devices. Our proposed scheme is more efficient for users than existing schemes, by providing a strong cipher. Jae Dong Lee, Hyung Jin Im, Won Min Kang, and Jong Hyuk Park Copyright © 2014 Jae Dong Lee et al. All rights reserved. Solving Nonstiff Higher Order Odes Using Variable Order Step Size Backward Difference Directly Tue, 19 Aug 2014 07:16:43 +0000 The current numerical techniques for solving a system of higher order ordinary differential equations (ODEs) directly calculate the integration coefficients at every step. Here, we propose a method to solve higher order ODEs directly by calculating the integration coefficients only once at the beginning of the integration and if required once more at the end. The formulae will be derived in terms of backward difference in a constant step size formulation. The method developed will be validated by solving some higher order ODEs directly using variable order step size. To simplify the evaluations of the integration coefficients, we find the relationship between various orders. The results presented confirmed our hypothesis. Ahmad Fadly Nurullah Rasedee, Mohamed bin Suleiman, and Zarina Bibi Ibrahim Copyright © 2014 Ahmad Fadly Nurullah Rasedee et al. All rights reserved. Intelligent Multiobjective Slip and Speed Ratio Control of a Novel Dual-Belt Continuously Variable Transmission for Automobiles Tue, 19 Aug 2014 07:14:27 +0000 Van Doorne’s continuously variable transmission (CVT) is the most popular CVT design for automotive transmission, but it is only applicable to low-power passenger cars because of its low torque capacity. To overcome this limitation of traditional single-belt CVT, a novel dual-belt Van Doorne’s CVT (DBVCVT) system, which is applicable to heavy-duty vehicles, has been previously proposed by the authors. This paper, based on the published analytical model and test rig of DBVCVT, further proposes an intelligent multiobjective fuzzy controller for slip and speed ratio control of DBVCVT. The controller aims to safely control the clamping forces of both the primary and the secondary pulleys in order to improve the transmission efficiency, achieve the accurate speed ratio, and avoid the belt slip under different engine loads and vehicle speeds. The slip, speed ratio, and transmission efficiency dynamics of DBVCVT are firstly analyzed and modeled in this paper. With the aid of a flexible objective function, the analytical model, and fuzzy logic, a Pareto rule base for fuzzy controller is developed for multiobjective DBVCVT control. Experimental results show that the proposed controller for slip and speed ratio regulation of DBVCVT is effective and performs well under different user-defined weights. Zhengchao Xie, Pak Kin Wong, Yueqiao Chen, and Ka In Wong Copyright © 2014 Zhengchao Xie et al. All rights reserved. Pressure Pulsation Signal Analysis for Centrifugal Compressor Blade Crack Determination Tue, 19 Aug 2014 00:00:00 +0000 Blade is a key piece of component for centrifugal compressor. But blade crack could usually occur as blade suffers from the effect of centrifugal forces, gas pressure, friction force, and so on. It could lead to blade failure and centrifugal compressor closing down. Therefore, it is important for blade crack early warning. It is difficult to determine blade crack as the information is weak. In this research, a pressure pulsation (PP) sensor installed in vicinity to the crack area is used to determine blade crack according to blade vibration transfer process analysis. As it cannot show the blade crack information clearly, signal analysis and empirical mode decomposition (EMD) are investigated for feature extraction and early warning. Firstly, signal filter is carried on PP signal around blade passing frequency (BPF) based on working process analysis. Then, envelope analysis is carried on to filter the BPF. In the end, EMD is carried on to determine the characteristic frequency (CF) for blade crack. Dynamic strain sensor is installed on the blade to determine the crack CF. Simulation and experimental investigation are carried on to verify the effectiveness of this method. The results show that this method can be helpful for blade crack classification for centrifugal compressors. Hongkun Li, Xuefeng Zhang, Xiaowen Zhang, Shuhua Yang, and Fujian Xu Copyright © 2014 Hongkun Li et al. All rights reserved. A Novel Design and Optimization Software for Autonomous PV/Wind/Battery Hybrid Power Systems Mon, 18 Aug 2014 12:11:22 +0000 This paper introduces a design and optimization computer simulation program for autonomous hybrid PV/wind/battery energy system. The main function of the new proposed computer program is to determine the optimum size of each component of the hybrid energy system for the lowest price of kWh generated and the best loss of load probability at highest reliability. This computer program uses the hourly wind speed, hourly radiation, and hourly load power with several numbers of wind turbine (WT) and PV module types. The proposed computer program changes the penetration ratio of wind/PV with certain increments and calculates the required size of all components and the optimum battery size to get the predefined lowest acceptable probability. This computer program has been designed in flexible fashion that is not available in market available software like HOMER and RETScreen. Actual data for Saudi sites have been used with this computer program. The data obtained have been compared with these market available software. The comparison shows the superiority of this computer program in the optimal design of the autonomous PV/wind/battery hybrid system. The proposed computer program performed the optimal design steps in very short time and with accurate results. Many valuable results can be extracted from this computer program that can help researchers and decision makers. Ali M. Eltamaly and Mohamed A. Mohamed Copyright © 2014 Ali M. Eltamaly and Mohamed A. Mohamed. All rights reserved. Robust Fuzzy Control for Nonlinear Discrete-Time Stochastic Systems with Markovian Jump and Parametric Uncertainties Mon, 18 Aug 2014 11:17:47 +0000 The paper mainly investigates the fuzzy control problem for a class of nonlinear discrete-time stochastic systems with Markovian jump and parametric uncertainties. The class of systems is modeled by a state space Takagi-Sugeno (T-S) fuzzy model that has linear nominal parts and norm-bounded parameter uncertainties in the state and output equations. An control design method is developed by using the Lyapunov function. The decoupling technique makes the Lyapunov matrices and the system matrices separated, which makes the control design feasible. Then, some strict linear matrix inequalities are derived on robust norm conditions in which both robust stability and performance are required to be achieved. Finally, a computer-simulated truck-trailer example is given to verify the feasibility and effectiveness of the proposed design method. Huiying Sun and Long Yan Copyright © 2014 Huiying Sun and Long Yan. All rights reserved. A United Method for Sensitivity Analysis of the Locational Marginal Price Based on the Optimal Power Flow Mon, 18 Aug 2014 11:16:52 +0000 Locational marginal prices (LMPs) are influenced by various factors in the electricity market; knowing the sensitivity information of LMPs is very important for both the purchase and the consumer. This paper presents a united method to compute the sensitivities of LMPs based on the optimal power flow (OPF). The Karush-Kuhn-Tucher (KKT) system to solve LMPs can be transferred into an equation system by using an NCP function, and then by using the properties of the derivative of the semismooth NCP function, this paper provides a simultaneous obtention of the sensitivities of LMPs with respect to power demands, the cost of production, voltage boundary, and so forth. Numerical examples illustrate the concepts presented and the proposed methodology by a 6-bus electric energy system. Some relevant conclusions are drawn in the end. Liu Yang and Chunlin Deng Copyright © 2014 Liu Yang and Chunlin Deng. All rights reserved. Existence and Global Uniform Asymptotic Stability of Pseudo Almost Periodic Solutions for Cohen-Grossberg Neural Networks with Discrete and Distributed Delays Mon, 18 Aug 2014 11:14:32 +0000 This paper studies the existence and uniform asymptotic stability of pseudo almost periodic solutions to Cohen-Grossberg neural networks (CGNNs) with discrete and distributed delays by applying Schauder fixed point theorem and constructing a suitable Lyapunov functional. An example is given to show the effectiveness of the main results. Hongying Zhu and Chunhua Feng Copyright © 2014 Hongying Zhu and Chunhua Feng. All rights reserved. Dual-Channel Particle Filter Based Track-Before-Detect for Monopulse Radar Mon, 18 Aug 2014 11:08:48 +0000 A particle filter based track-before-detect (PF-TBD) algorithm is proposed for the monopulse high pulse repetition frequency (PRF) pulse Doppler radar. The actual measurement model is adopted, in which the range is highly ambiguous and the sum and difference channels exist in parallel. A quantization method is used to approximate the point spread function to reduce the computation load. The detection decisions of the PF-TBD are fed to a binary integrator to further improve the detection performance. Simulation results show that the proposed algorithm can detect and track the low SNR target efficiently. The detection performance is improved significantly for both the single frame and the multiframe detection compared with the classical detector. A performance comparison with the PF-TBD using sum channel only is also supplied. Fei Cai, Hongqi Fan, and Qiang Fu Copyright © 2014 Fei Cai et al. All rights reserved. Correlated Analytic Hierarchy Process Mon, 18 Aug 2014 09:55:52 +0000 The analytic hierarchy process (AHP) has been the most popular tool for the field of decision making in the past 30 years, because of its simplicity and rationality. Construct a hierarchy system for evaluation by decision makers. Hence, only the effect of outer-dependence can be considered in the AHP. However, besides outer-dependence, correlation is another common effect between criteria which cannot be accounted for neither by the AHP nor by the analytic network process (ANP). Hence, in this paper, we extend the AHP to consider the correlation effect. In addition, a biobjective programming model is proposed to derive the result. Furthermore, the traditional AHP can be considered as the special case of the proposed model when the correlation effect between criteria is ignored. Finally, a numerical example is given to justify the proposed method and compare the result with the AHP. Hsiang-Hsi Liu, Yeong-Yuh Yeh, and Jih-Jeng Huang Copyright © 2014 Hsiang-Hsi Liu et al. All rights reserved. Research on Short-Term Traffic Flow Prediction Method Based on Similarity Search of Time Series Mon, 18 Aug 2014 08:42:25 +0000 Short-time traffic flow prediction is necessary for advanced traffic management system (ATMS) and advanced traveler information system (ATIS). In order to improve the effect of short-term traffic flow prediction, this paper presents a short-term traffic flow multistep prediction method based on similarity search of time series. Firstly, the landmark model is used to represent time series of traffic flow data. Then the input data of prediction model are determined through searching similar time series. Finally, the echo state networks model is used for traffic flow multistep prediction. The performance of the proposed method is measured with expressway traffic flow data collected from loop detectors in Shanghai, China. The experimental results demonstrate that the proposed method can achieve better multistep prediction performance than conventional methods. Zhaosheng Yang, Qichun Bing, Ciyun Lin, Nan Yang, and Duo Mei Copyright © 2014 Zhaosheng Yang et al. All rights reserved. The Synergy between City Human Resources and City Economy Development Based on the City Marketing: The Case of Chengdu Mon, 18 Aug 2014 08:41:25 +0000 City human resources and the city economic development have a synergistic effect to attract high-quality talent and to encourage the sustainable development of the urban economy in the city marketing. Based on synergetics, we find out the evaluation indexes between the city human resources subsystem and urban economic development subsystem and constructed the evaluation system and model, and then used the yearbook data of Chengdu human resources and economic development from 2002 to 2012 and carried on empirical research. The results show that the level of coordinated development is weak between city human resources and city economic development at Chengdu, but it keeps rising slowly. The strong policy support shall be provided to Chengdu human resources and economic development by Chengdu government. Bo Pu and Yanjun Qiu Copyright © 2014 Bo Pu and Yanjun Qiu. All rights reserved. Applying Hybrid Heuristic Approach to Identify Contaminant Source Information in Transient Groundwater Flow Systems Mon, 18 Aug 2014 07:42:39 +0000 Simultaneous identification of the source location and release history in aquifers is complicated and time-consuming if the release of groundwater contaminant source varies in time. This paper presents an approach called SATSO-GWT to solve complicated source release problems which contain the unknowns of three location coordinates and several irregular release periods and concentrations. The SATSO-GWT combines with ordinal optimization algorithm (OOA), roulette wheel approach, and a source identification algorithm called SATS-GWT. The SATS-GWT was developed based on simulated annealing, tabu search, and three-dimensional groundwater flow and solute transport model MD2K-GWT. The OOA and roulette wheel method are utilized mainly to reduce the size of feasible solution domain and accelerate the identification of the source information. A hypothetic site with one contaminant source location and two release periods is designed to assess the applicability of the present approach. The results indicate that the performance of SATSO-GWT is superior to that of SATS-GWT. In addition, the present approach works very effectively in dealing with the cases which have different initial guesses of source location and measurement errors in the monitoring points as well as problems with large suspicious areas and several source release periods and concentrations. Hund-Der Yeh, Chao-Chih Lin, and Bo-Jei Yang Copyright © 2014 Hund-Der Yeh et al. All rights reserved. On Fractional Order Dengue Epidemic Model Mon, 18 Aug 2014 06:59:45 +0000 This paper deals with the fractional order dengue epidemic model. The stability of disease-free and positive fixed points is studied. Adams-Bashforth-Moulton algorithm has been used to solve and simulate the system of differential equations. Hamed Al-Sulami, Moustafa El-Shahed, Juan J. Nieto, and Wafa Shammakh Copyright © 2014 Hamed Al-Sulami et al. All rights reserved. Transformation Matrix for Time Discretization Based on Tustin’s Method Mon, 18 Aug 2014 00:00:00 +0000 This paper studies rules in transformation of transfer function through time discretization. A method of using transformation matrix to realize bilinear transform (also known as Tustin’s method) is presented. This method can be described as the conversion between the coefficients of transfer functions, which are expressed as transform by certain matrix. For a polynomial of degree n, the corresponding transformation matrix of order n exists and is unique. Furthermore, the transformation matrix can be decomposed into an upper triangular matrix multiplied with another lower triangular matrix. And both have obvious regularity. The proposed method can achieve rapid bilinear transform used in automatic design of digital filter. The result of numerical simulation verifies the correctness of the theoretical results. Moreover, it also can be extended to other similar problems. Example in the last throws light on this point. Yiming Jiang, Xiaodong Hu, and Sen Wu Copyright © 2014 Yiming Jiang et al. All rights reserved. Automatic Extraction System for Common Artifacts in EEG Signals Based on Evolutionary Stone’s BSS Algorithm Mon, 18 Aug 2014 00:00:00 +0000 An automatic artifact extraction system is proposed based on a hybridization of Stone’s BSS and genetic algorithm. This hybridization is called evolutionary Stone’s BSS algorithm (ESBSS). Original Stone’s BSS used short- and long-term half-life parameters as constant values, and the changes in these parameters will be affecting directly the separated signals; also there is no way to determine the best parameters. The genetic algorithm is a suitable technique to overcome this problem by finding randomly the optimum half-life parameters in Stone’s BSS. The proposed system is used to extract automatically the common artifacts such as ocular and heart beat artifacts from EEG mixtures without prejudice to the data; also there is no notch filter used in the proposed system in order not to lose any useful information. Ahmed Kareem Abdullah, Chao Zhu Zhang, Ali Abdul Abbas Abdullah, and Siyao Lian Copyright © 2014 Ahmed Kareem Abdullah et al. All rights reserved. Research of Impact Load in Large Electrohydraulic Load Simulator Mon, 18 Aug 2014 00:00:00 +0000 The stronger impact load will appear in the initial phase when the large electric cylinder is tested in the hardware-in-loop simulation. In this paper, the mathematical model is built based on AMESim, and then the reason of the impact load is investigated through analyzing the changing tendency of parameters in the simulation results. The inhibition methods of impact load are presented according to the structural invariability principle and applied to the actual system. The final experimental result indicates that the impact load is inhibited, which provides a good experimental condition for the electric cylinder and promotes the study of large load simulator. Yongguang Liu, Xiaohui Gao, and Zhongcai Pei Copyright © 2014 Yongguang Liu et al. All rights reserved. Mechanical Decoupling Algorithm Applied to Electric Drive Test Bed Sun, 17 Aug 2014 13:13:21 +0000 New approach and analysis are proposed in this paper to enhance the steady and rapidity of the electric drive test bed. Based on a basic drive motor dynamometer system (DMDS) test bed, detailed mathematical model and process control are established and analyzed. Relative gain array (RGA) method and diagonal matrix method are used to analyze the mechanical coupling caused by mechanical connection on the DMDS test bed, and the structure and algorithm of dynamic decoupling are proposed. Simulation and experiment all indicate that the designed decoupling method can efficiently improve the control accuracy and response speed. Song Qiang and Luo Lin Copyright © 2014 Song Qiang and Luo Lin. All rights reserved. Subsurface Scattering-Based Object Rendering Techniques for Real-Time Smartphone Games Sun, 17 Aug 2014 12:52:34 +0000 Subsurface scattering that simulates the path of a light through the material in a scene is one of the advanced rendering techniques in the field of computer graphics society. Since it takes a number of long operations, it cannot be easily implemented in real-time smartphone games. In this paper, we propose a subsurface scattering-based object rendering technique that is optimized for smartphone games. We employ our subsurface scattering method that is utilized for a real-time smartphone game. And an example game is designed to validate how the proposed method can be operated seamlessly in real time. Finally, we show the comparison results between bidirectional reflectance distribution function, bidirectional scattering distribution function, and our proposed subsurface scattering method on a smartphone game. Won-Sun Lee, Seung-Do Kim, and Seongah Chin Copyright © 2014 Won-Sun Lee et al. All rights reserved. Software Quality Evaluation Model Based on Weighted Mutation Rate Correction Incompletion G1 Combination Weights Sun, 17 Aug 2014 11:22:52 +0000 Aiming at the common problems of quality evaluation method, this paper first establishes a fuzzy software quality evaluation model according to the relationship of software quality subcharacteristics and indicators; furthermore, considering the uncertainty and individual deviations of expert judgment results, this paper corrects and tests the consistency of the incomplete information sorting given by the experts and obtains an integration sorting of gathering different expert opinions through the idea of circling modification; at last, this paper proposes the weighted mutation rate which is used to measure the development balance degree and determines weights of evaluation indicators via weighted mutation rate correction incompletion G1 method, which avoids the problem of integration of subjective and objective weights. Chuanyang Ruan and Jianhui Yang Copyright © 2014 Chuanyang Ruan and Jianhui Yang. All rights reserved. Approximate Sparse Regularized Hyperspectral Unmixing Sun, 17 Aug 2014 08:23:32 +0000 Sparse regression based unmixing has been recently proposed to estimate the abundance of materials present in hyperspectral image pixel. In this paper, a novel sparse unmixing optimization model based on approximate sparsity, namely, approximate sparse unmixing (ASU), is firstly proposed to perform the unmixing task for hyperspectral remote sensing imagery. And then, a variable splitting and augmented Lagrangian algorithm is introduced to tackle the optimization problem. In ASU, approximate sparsity is used as a regularizer for sparse unmixing, which is sparser than regularizer and much easier to be solved than regularizer. Three simulated and one real hyperspectral images were used to evaluate the performance of the proposed algorithm in comparison to regularizer. Experimental results demonstrate that the proposed algorithm is more effective and accurate for hyperspectral unmixing than state-of-the-art regularizer. Chengzhi Deng, Yaning Zhang, Shengqian Wang, Shaoquan Zhang, Wei Tian, Zhaoming Wu, and Saifeng Hu Copyright © 2014 Chengzhi Deng et al. All rights reserved. Algorithms to Solve Stochastic Control with State-Dependent Noise Sun, 17 Aug 2014 07:33:55 +0000 This paper is concerned with the algorithms which solve control problems of stochastic systems with state-dependent noise. Firstly, the algorithms for the finite and infinite horizon control of discrete-time stochastic systems are reviewed and studied. Secondly, two algorithms are proposed for the finite and infinite horizon control of continuous-time stochastic systems, respectively. Finally, several numerical examples are presented to show the effectiveness of the algorithms. Ming Gao, Changdi Fu, and Weihai Zhang Copyright © 2014 Ming Gao et al. All rights reserved. Fingerprint Classification Combining Curvelet Transform and Gray-Level Cooccurrence Matrix Sun, 17 Aug 2014 07:10:55 +0000 Fingerprint classification is an important indexing scheme to reduce fingerprint matching time for a large database for efficient large-scale identification. The abilities of Curvelet transform capturing directional edges of fingerprint images make the fingerprint suitable to be classified for higher classification accuracy. This paper presents an efficient algorithm for fingerprint classification combining Curvelet transform (CT) and gray-level cooccurrence matrix (GLCM). Firstly, we use fast discrete Curvelet transform warping (FDCT_WARPING) to decompose the original image into five scales Curvelet coefficients and construct the Curvelet filter by Curvelet coefficients relationship at adjacent scales to remove the noise from signals. Secondly, we compute the GLCMs of Curvelet coefficients at the coarsest scale and calculate 16 texture features based on 4 GLCMs. Thirdly, we construct 49 direction features of Curvelet coefficients at the other four scales. Finally, fingerprint classification is accomplished by -nearest neighbor classifiers. Extensive experiments were performed on 4000 images in the NIST-4 database. The proposed algorithm achieves the classification accuracy of 94.6 percent for the five-class classification problem and 96.8 percent for the four-class classification problem with 1.8 percent rejection, respectively. The experimental results verify that proposed algorithm has higher recognition rate than that of wavelet-based techniques. Jing Luo, Dan Song, Chunbo Xiu, Shuze Geng, and Tingting Dong Copyright © 2014 Jing Luo et al. All rights reserved.