Mathematical Problems in Engineering The latest articles from Hindawi Publishing Corporation © 2016 , Hindawi Publishing Corporation . All rights reserved. A Multikernel-Like Learning Algorithm Based on Data Probability Distribution Thu, 23 Jun 2016 14:53:08 +0000 In the machine learning based on kernel tricks, people often put one variable of a kernel function on the given samples to produce the basic functions of a solution space of learning problem. If the collection of the given samples deviates from the data distribution, the solution space spanned by these basic functions will also deviate from the real solution space of learning problem. In this paper a multikernel-like learning algorithm based on data probability distribution (MKDPD) is proposed, in which the parameters of a kernel function are locally adjusted according to the data probability distribution, and thus produces different kernel functions. These different kernel functions will generate different Reproducing Kernel Hilbert Spaces (RKHS). The direct sum of the subspaces of these RKHS constitutes the solution space of learning problem. Furthermore, based on the proposed MKDPD algorithm, a new algorithm for labeling new coming data is proposed, in which the basic functions are retrained according to the new coming data, while the coefficients of the retrained basic functions remained unchanged to label the new coming data. The experimental results presented in this paper show the effectiveness of the proposed algorithms. Guo Niu, Zhengming Ma, and Shuyu Liu Copyright © 2016 Guo Niu et al. All rights reserved. Seismic Performance Evaluations of Mega-Sub Isolation System Thu, 23 Jun 2016 08:30:58 +0000 This paper presents mega-sub isolation system. Shaking table test of the mega-sub isolation system is carried out in this paper. Three test models have been developed. One is called aseismic model, in which all the substructures are fixedly connected with the megastructures. The second one is known as isolated model, where the substructures are connected with the megastructures with isolators, and the last one is called the lower substructure consolidated (LSC) model, in which all the substructures except for the substructures at the lowest level, in other words, substructures at the second mega floor, are isolated from the megastructures. Nonlinear dynamic time analysis of the test models is conducted by SAP2000. Acceleration responses of the megastructure, story drift responses of the megastructure and the substructure, and the deformations of the isolation layer are compared between experimental and numerical simulation results. The results show that the experimental results and numerical simulation results agree well with each other, and the isolated model and LSC model perform better than the counterpart aseismic model. The structures with isolation devices can reduce the structural responses effectively and are much safer than the structure without isolation devices. Xiangxiu Li, Ping Tan, Xiaojun Li, and Aiwen Liu Copyright © 2016 Xiangxiu Li et al. All rights reserved. Necessary and Sufficient Conditions for Circle Formations of Mobile Agents with Coupling Delay via Sampled-Data Control Wed, 22 Jun 2016 14:23:49 +0000 A circle forming problem for a group of mobile agents governed by first-order system is investigated, where each agent can only sense the relative angular positions of its neighboring two agents with time delay and move on the one-dimensional space of a given circle. To solve this problem, a novel decentralized sampled-data control law is proposed. By combining algebraic graph theory with control theory, some necessary and sufficient conditions are established to guarantee that all the mobile agents form a pregiven circle formation asymptotically. Moreover, the ranges of the sampling period and the coupling delay are determined, respectively. Finally, the theoretical results are demonstrated by numerical simulations. Jianwei Zhao, Hongxiang Hu, Chen Wang, and Guangming Xie Copyright © 2016 Jianwei Zhao et al. All rights reserved. Coherent RAKE Receiver for CPM-Based Direct Sequence Spread Spectrum Wed, 22 Jun 2016 12:07:11 +0000 Direct sequence spread spectrum (DSSS) using continuous phase modulation (CPM) inherits the techniques’ benefits, constant envelope, anti-interference, and spectral efficiency. To get diversity gains over a Rayleigh-fading multipath channel as in conventional direct sequence spread-spectrum binary phase shift keying (DSSS-BPSK) system, a new class of coherent RAKE receivers is proposed in this work. By introducing chip branch metric to the receiver scheme, despreading and data detection can be done meanwhile based on Maximum Likelihood Sequence Detection (MLSD). Compared to the conventional RAKE receiver which sums decision metrics symbol-by-symbol, the proposed DSSS-CPM RAKE receiver accumulates symbol branch metric increments over every phase state of multiple paths after chip phase synchronization. Numerical results show that DSSS-CPM using the synchronous despreading and demodulation algorithm has no performance loss compared to CPM system that employs MLSD algorithm under the same test conditions. Moreover, the proposed RAKE receiver outperforms conventional RAKE receiver and achieves a remarkable diversity gain of bit error rate (BER) under the Rayleigh-fading multipath channel. Ke Zhou, Shilian Wang, and Eryang Zhang Copyright © 2016 Ke Zhou et al. All rights reserved. Application of Recursive Subspace Method in Vehicle Lateral Dynamics Model Identification Wed, 22 Jun 2016 10:13:25 +0000 Modeling of vehicle behavior based on the identification method has received a renewed attention in recent years. In order to improve the linear time-invariant vehicle identification model, a more general identifiable vehicle model structure is proposed, in which time-varying characteristics of vehicle speed and cornering stiffness are taken into consideration. To identify the proposed linear time-varying vehicle model, a well-established data-driven method, named recursive optimized version of predictor-based subspace identification, is introduced. Before vehicle model identification, the influences of four parameters in the subspace algorithm are studied based on pulse input road test. And then a set of practical optimal parameters are chosen and used for the vehicle model identification. Through a series of standard road tests under different maneuvers, the linear time-varying vehicle model can be identified in real-time. It is demonstrated by comparison that the predicted outputs of the proposed vehicle model are much closer to the real vehicle outputs and the model has a wider range of application. Tengyue Ba, Xiqiang Guan, Jian W. Zhang, and Sanzhou Wang Copyright © 2016 Tengyue Ba et al. All rights reserved. The Chaotic Attractor Analysis of DJIA Based on Manifold Embedding and Laplacian Eigenmaps Wed, 22 Jun 2016 08:49:25 +0000 By using the techniques of Manifold Embedding and Laplacian Eigenmaps, a novel strategy has been proposed in this paper to detect the chaos of Dow Jones Industrial Average. Firstly, the chaotic attractor of financial time series is assumed to lie on a low-dimensional manifold that is embedded into a high-dimensional Euclidean space. Then, an improved phase space reconstruction method and a nonlinear dimensionality reduction method are introduced to help reveal the structure of the chaotic attractor. Next, the empirical study on the financial time series of Dow Jones Industrial Average shows that there exists an attractor which lies on a manifold constructed by the time sequence of Moving average convergence divergence; finally, Determinism Test, Poincaré section, and translation analysis are used as test approaches to prove both whether it is a chaos and how it works. Xiaohua Song, Dongxiao Niu, and Yulin Zhang Copyright © 2016 Xiaohua Song et al. All rights reserved. Analysis of Public Bus Transportation of a Brazilian City Based on the Theory of Complex Networks Using the P-Space Wed, 22 Jun 2016 08:39:58 +0000 The city of Curitiba, located at Southern Brazil, is recognized by its urban planning structured on three pillars: land use, collective transportation, and traffic. With 3.8 million people in its metropolitan area, the public transport system deals with approximately 2.5 million passengers daily. The structure and properties of such a transportation system have substantial implications for the urban planning and public politics for sustainable development of Curitiba. Therefore, this paper analyzes the structure of the public transportation system of Curitiba through the theory of complex networks in a static approach of network topology and presents a comparative analysis of the results from Curitiba, three cities from China (Shanghai, Beijing, and Guangzhou), and three cities from Poland (GOP, Warszawa, and Łódź). The transportation network was modeled as a complex network with exact geographical coordinates of its bus stops. In all bus lines, the method used was the P-Space. The results show that this bus network has characteristics of both small-world and scale-free networks. A. A. De Bona, K. V. O. Fonseca, M. O. Rosa, R. Lüders, and M. R. B. S. Delgado Copyright © 2016 A. A. De Bona et al. All rights reserved. Numerical Implementation of Spatial Elastoplastic Damage Model of Concrete in the Framework of Isogeometric Analysis Approach Wed, 22 Jun 2016 08:03:21 +0000 This paper is a study of the numerical implementation of the spatial elastoplastic damage model of concrete by isogeometric analysis (IGA) method from three perspectives: the geometric modeling and the numerical formulation via IGA method, the constitutive model of concrete, and the solution algorithms for the local and global problems. The plasticity of concrete is considered on the basis of a nonassociated flow rule, where a three-parameter Barcelona yield surface and a modified Drucker-Prager plastic potential are used. The damage evolution of concrete driven by the internal variables is expressed by a piecewise function. In the study, the return-mapping algorithm and the substepping strategy are used for stress updating, and a new dissipation-based arc-length method with constraint path that considers the combined contribution of plasticity and damage to the energy dissipation is employed to trace the equilibrium path. After comparisons between simulation results and experimental data, the use of the elastoplastic damage model in the framework of IGA approach is proven to be practical in reflecting material properties of concrete. Cheng Ma, Wei-zhen Chen, and Jian-yuan Sun Copyright © 2016 Cheng Ma et al. All rights reserved. A Corotational Formulation for Large Displacement Analysis of Functionally Graded Sandwich Beam and Frame Structures Tue, 21 Jun 2016 15:23:42 +0000 A corotational finite element formulation for large displacement analysis of planar functionally graded sandwich (FGSW) beam and frame structures is presented. The beams and frames are assumed to be formed from a metallic soft core and two symmetric functionally graded skin layers. The Euler-Bernoulli beam theory and von Kármán nonlinear strain-displacement relationship are adopted for the local strain. Exact solution of nonlinear equilibrium equations for a beam segment is employed to interpolate the displacement field for avoiding the membrane locking. An incremental-iterative procedure is used in combination with the arc-length control method to compute the equilibrium paths. Numerical examples show that the proposed formulation is capable of evaluating accurately the large displacement response with just several elements. A parametric study is carried out to highlight the effect of the material distribution, the core thickness to height ratio on the large displacement behaviour of the FGSW beam, and frame structures. Dinh Kien Nguyen and Thi Thom Tran Copyright © 2016 Dinh Kien Nguyen and Thi Thom Tran. All rights reserved. A Sparse Signal Reconstruction Algorithm in Wireless Sensor Networks Tue, 21 Jun 2016 09:16:38 +0000 We study reconstruction of time-varying sparse signals in a wireless sensor network, where the bandwidth and energy constraints are considered severely. A novel particle filter algorithm is proposed to deal with the coarsely quantized innovation. To recover the sparse pattern of estimate by particle filter, we impose the sparsity constraint on the filter estimate by means of two methods. Simulation results demonstrate that the proposed algorithms provide performance which is comparable to that of the full information (i.e., unquantized) filtering schemes even in the case where only 1 bit is transmitted to the fusion center. Zhi Zhao and Jiuchao Feng Copyright © 2016 Zhi Zhao and Jiuchao Feng. All rights reserved. An Efficient Approach for Energy Consumption Optimization and Management in Residential Building Using Artificial Bee Colony and Fuzzy Logic Tue, 21 Jun 2016 06:33:35 +0000 The energy management in residential buildings according to occupant’s requirement and comfort is of vital importance. There are many proposals in the literature addressing the issue of user’s comfort and energy consumption (management) with keeping different parameters in consideration. In this paper, we have utilized artificial bee colony (ABC) optimization algorithm for maximizing user comfort and minimizing energy consumption simultaneously. We propose a complete user friendly and energy efficient model with different components. The user set parameters and the environmental parameters are inputs of the ABC, and the optimized parameters are the output of the ABC. The error differences between the environmental parameters and the ABC optimized parameters are inputs of fuzzy controllers, which give the required energy as the outputs. The purpose of the optimization algorithm is to maximize the comfort index and minimize the error difference between the user set parameters and the environmental parameters, which ultimately decreases the power consumption. The experimental results show that the proposed model is efficient in achieving high comfort index along with minimized energy consumption. Fazli Wahid and Do Hyeun Kim Copyright © 2016 Fazli Wahid and Do Hyeun Kim. All rights reserved. Advanced Fireworks Algorithm and Its Application Research in PID Parameters Tuning Mon, 20 Jun 2016 13:56:56 +0000 Proportional-Integral-Derivative (PID) controller is one of the most widely used controllers for its property of simplicity and practicability. In order to design high-quality performances PID controllers, an Advanced Fireworks (AFW) algorithm based on self-adaption principle and bimodal Gaussian function is proposed, which is built to optimize the PID controller by parameters tuning. Firstly, a compound index of optimization performance is formulated, and then the extremal optimization method of PID control system is proposed. Secondly, a PID parameters tuning model combined with AFW is built. At last, 5 typical transfer functions are simulated to obtain optimal parameters by AFW and contrast tuning method, such as Ziegler-Nichols method, Enhanced Fireworks (EFW) algorithm, and Particle Swarm Optimization (PSO). Simulation results show that AFW are effective and are easily implemented methods to solve PID control problems of different transfer functions. Jun-jie Xue, Ying Wang, Hao Li, Xiang-fei Meng, and Ji-yang Xiao Copyright © 2016 Jun-jie Xue et al. All rights reserved. Adaptive Robust Posture Control of a 3-RPS Pneumatic Parallel Platform with Unknown Deadzone Mon, 20 Jun 2016 11:25:04 +0000 An adaptive robust controller integrated with online deadzone estimation is proposed. This controller provides trajectory tracking control for pneumatic parallel mechanisms. Due to the air compressibility and nonlinear characteristics of the pneumatic system, unknown parameters in the model are selected to build online estimation matrices with the robust parts considered in the design. As each proportional valve has specific values of deadzone boundary points, the deadzone parts are integrated into the online estimator, and an inverse deadzone compensator is used to overcome nonlinear limitations. The effectiveness of the method was verified by simulation and experiment, and theoretical stability was demonstrated using the Lyapunov method. Experiments in an actual plant with the proposed controller indicated that the performance of the pneumatic platform can be as good as that of ideal deadzone inverse compensation. The deadzone estimated parameters converged to the real values quickly. Additionally, this algorithm was effective under a compound reference input trajectory; thus, the controller is expected to perform well in actual working situations. Guoliang Tao, Ce Shang, and Deyuan Meng Copyright © 2016 Guoliang Tao et al. All rights reserved. The Effects of the Emission Cost on Route Choices of International Container Ships Mon, 20 Jun 2016 11:18:42 +0000 Maritime freight shipping has increased significantly and air pollution from international ships has grown accordingly, having serious environmental effects all over the world. This paper analyzes the effects of the emission cost on ocean route choices, focusing on international container ships. First, the paper formulates a freight network model that captures decisions and interactions of ocean carriers and port terminal operators in the maritime freight transport system. Then, the emission cost is calculated based on an activity-based approach as a component of the ocean transportation cost function. A case study is examined to find if the emission cost affects ocean route choices. The results indicate that the optimal ocean route and transportation cost are changed distinctively due to the emission cost. The research discusses how the emission cost plays a role in route changes and why ocean carriers have to consider these costs in their routing decisions. Hyangsook Lee, Kang-Dae Lee, and Sangho Choo Copyright © 2016 Hyangsook Lee et al. All rights reserved. An Efficient Cost-Sensitive Feature Selection Using Chaos Genetic Algorithm for Class Imbalance Problem Mon, 20 Jun 2016 09:19:18 +0000 In the era of big data, feature selection is an essential process in machine learning. Although the class imbalance problem has recently attracted a great deal of attention, little effort has been undertaken to develop feature selection techniques. In addition, most applications involving feature selection focus on classification accuracy but not cost, although costs are important. To cope with imbalance problems, we developed a cost-sensitive feature selection algorithm that adds the cost-based evaluation function of a filter feature selection using a chaos genetic algorithm, referred to as CSFSG. The evaluation function considers both feature-acquiring costs (test costs) and misclassification costs in the field of network security, thereby weakening the influence of many instances from the majority of classes in large-scale datasets. The CSFSG algorithm reduces the total cost of feature selection and trades off both factors. The behavior of the CSFSG algorithm is tested on a large-scale dataset of network security, using two kinds of classifiers: C4.5 and -nearest neighbor (KNN). The results of the experimental research show that the approach is efficient and able to effectively improve classification accuracy and to decrease classification time. In addition, the results of our method are more promising than the results of other cost-sensitive feature selection algorithms. Jing Bian, Xin-guang Peng, Ying Wang, and Hai Zhang Copyright © 2016 Jing Bian et al. All rights reserved. Grey Weighted Sum Model for Evaluating Business Environment in West Africa Mon, 20 Jun 2016 09:17:36 +0000 As West Africa investments grow, the decision in which country to begin investment is of great importance to investors. The complexity of the criteria involved draws us to use a Multicriteria Decision-Making (MCDM) approach to address this problem. In this paper, we use grey numbers in representing ranges of data and propose Grey Weighted Sum Model (GWSM) for evaluating and ranking of alternatives. Sensitivity analysis is carried out considering wide ranges of uncertainties to verify the changes that can affect the results. The Gambia is ranked the best country in West Africa. The GWSM is highly recommended for long-term investors because GWSM considers the uncertainty of a business environment over a period of years. Finally, GWSM can be used in conjunction with various weighting techniques putting the preferences of the investors into consideration. Moses Olabhele Esangbedo and Ada Che Copyright © 2016 Moses Olabhele Esangbedo and Ada Che. All rights reserved. Hand Gesture Recognition Using Particle Swarm Movement Mon, 20 Jun 2016 09:06:23 +0000 We present a gesture recognition method derived from particle swarm movement for free-air hand gesture recognition. Online gesture recognition remains a difficult problem due to uncertainty in vision-based gesture boundary detection methods. We suggest an automated process of segmenting meaningful gesture trajectories based on particle swarm movement. A subgesture detection and reasoning method is incorporated in the proposed recognizer to avoid premature gesture spotting. Evaluation of the proposed method shows promising recognition results: 97.6% on preisolated gestures, 94.9% on stream gestures with assistive boundary indicators, and 94.2% for blind gesture spotting on digit gesture vocabulary. The proposed recognizer requires fewer computation resources; thus it is a good candidate for real-time applications. Clementine Nyirarugira, Hyo-rim Choi, and TaeYong Kim Copyright © 2016 Clementine Nyirarugira et al. All rights reserved. Integrated Power Flow and Short Circuit Calculation Method for Distribution Network with Inverter Based Distributed Generation Mon, 20 Jun 2016 07:17:27 +0000 Power flow calculation and short circuit calculation are the basis of theoretical research for distribution network with inverter based distributed generation. The similarity of equivalent model for inverter based distributed generation during normal and fault conditions of distribution network and the differences between power flow and short circuit calculation are analyzed in this paper. Then an integrated power flow and short circuit calculation method for distribution network with inverter based distributed generation is proposed. The proposed method let the inverter based distributed generation be equivalent to bus, which makes it suitable to calculate the power flow of distribution network with a current limited inverter based distributed generation. And the low voltage ride through capability of inverter based distributed generation can be considered as well in this paper. Finally, some tests of power flow and short circuit current calculation are performed on a 33-bus distribution network. The calculated results from the proposed method in this paper are contrasted with those by the traditional method and the simulation method, whose results have verified the effectiveness of the integrated method suggested in this paper. Shan Yang and Xiangqian Tong Copyright © 2016 Shan Yang and Xiangqian Tong. All rights reserved. Application of the Multitype Strauss Point Model for Characterizing the Spatial Distribution of Landslides Sun, 19 Jun 2016 12:27:30 +0000 Landslides are common but complex natural hazards. They occur on the Earth’s surface following a mass movement process. This study applies the multitype Strauss point process model to analyze the spatial distributions of small and large landslides along with geoenvironmental covariates. It addresses landslides as a set of irregularly distributed point-type locations within a spatial region. Their intensity and spatial interactions are analyzed by means of the distance correlation functions, model fitting, and simulation. We use as a dataset the landslide occurrences for 28 years from a landslide prone road corridor in the Indian Himalayas. The landslides are investigated for their spatial character, that is, whether they show inhibition or occur as a regular or a clustered point pattern, and for their interaction with landslides in the neighbourhood. Results show that the covariates lithology, land cover, road buffer, drainage density, and terrain units significantly improved model fitting. A comparison of the output made with logistic regression model output showed a superior prediction performance for the multitype Strauss model. We compared results of this model with the multitype/hard core Strauss point process model that further improved the modeling. Results from the study can be used to generate landslide susceptibility scenarios. The paper concludes that a multitype Strauss point process model enriches the set of statistical tools that can comprehensively analyze landslide data. Iswar Das and Alfred Stein Copyright © 2016 Iswar Das and Alfred Stein. All rights reserved. Predicting Modeling Method of Ship Radiated Noise Based on Genetic Algorithm Sun, 19 Jun 2016 12:11:44 +0000 Because the forming mechanism of underwater acoustic signal is complex, it is difficult to establish the accurate predicting model. In this paper, we propose a nonlinear predicting modeling method of ship radiated noise based on genetic algorithm. Three types of ship radiated noise are taken as real underwater acoustic signal. First of all, a basic model framework is chosen. Secondly, each possible model is done with genetic coding. Thirdly, model evaluation standard is established. Fourthly, the operation of genetic algorithm such as crossover, reproduction, and mutation is designed. Finally, a prediction model of real underwater acoustic signal is established by genetic algorithm. By calculating the root mean square error and signal error ratio of underwater acoustic signal predicting model, the satisfactory results are obtained. The results show that the proposed method can establish the accurate predicting model with high prediction accuracy and may play an important role in the further processing of underwater acoustic signal such as noise reduction and feature extraction and classification. Guohui Li and Hong Yang Copyright © 2016 Guohui Li and Hong Yang. All rights reserved. Quantification of Margins and Uncertainties Approach for Structure Analysis Based on Evidence Theory Sun, 19 Jun 2016 12:08:43 +0000 Quantification of Margins and Uncertainties (QMU) is a decision-support methodology for complex technical decisions centering on performance thresholds and associated margins for engineering systems. Uncertainty propagation is a key element in QMU process for structure reliability analysis at the presence of both aleatory uncertainty and epistemic uncertainty. In order to reduce the computational cost of Monte Carlo method, a mixed uncertainty propagation approach is proposed by integrated Kriging surrogate model under the framework of evidence theory for QMU analysis in this paper. The approach is demonstrated by a numerical example to show the effectiveness of the mixed uncertainty propagation method. Chaoyang Xie and Guijie Li Copyright © 2016 Chaoyang Xie and Guijie Li. All rights reserved. Investigation of Lab Fire Prevention Management System of Combining Root Cause Analysis and Analytic Hierarchy Process with Event Tree Analysis Sun, 19 Jun 2016 12:06:43 +0000 This paper proposed a new approach, combining root cause analysis (RCA), analytic hierarchy process (AHP), and event tree analysis (ETA) in a loop to systematically evaluate various laboratory safety prevention strategies. First, 139 fire accidents were reviewed to identify the root causes and draw out prevention strategies. Most fires were caused due to runaway reactions, operation error and equipment failure, and flammable material release. These mostly occurred in working places of no prompt fire protection. We also used AHP to evaluate the priority of these strategies and found that chemical fire prevention strategy is the most important control element, and strengthening maintenance and safety inspection intensity is the most important action. Also together with our surveys results, we proposed that equipment design is also critical for fire prevention. Therefore a technical improvement was propounded: installing fire detector, automatic sprinkler, and manual extinguisher in the lab hood as proactive fire protections. ETA was then used as a tool to evaluate laboratory fire risks. The results indicated that the total risk of a fire occurring decreases from 0.0351 to 0.0042 without/with equipment taking actions. Establishing such system can make Environment, Health and Safety (EH&S) office not only analyze and prioritize fire prevention policies more practically, but also demonstrate how effective protective equipment improvement can achieve and the probabilities of the initiating event developing into a serious accident or controlled by the existing safety system. Cheng-Chan Shih, Richard S. Horng, and Shin-Ku Lee Copyright © 2016 Cheng-Chan Shih et al. All rights reserved. Service Radius Model and Service Scope Optimization of City Public Parking Garage Sun, 19 Jun 2016 11:41:25 +0000 The service radius of public parking garage is related to the supply of parking spots and parking behavior characteristics of drivers. However, the empirical and statistical methods in the optimization of public parking garage have limitations. Based on the theory of value engineering and satisfaction, an optimization model for public parking garage service radius is established, which satisfies the requirements of both drivers and owners. Then, an amended model is proposed by using accessibility theory and the principle of moment balance. This model, in consideration of city resistance and walking impedance, is modified from the circular service scope to an irregular polygon, which is more suitable for the actual situation. Finally, the method is verified by a practical example. The results suggest that the optimization model of the service radius and the optimization method of service scope can not only balance the needs of drivers and public parking garages’ owners, but also improve the operation efficiency of parking garages, so that they are more fit for the actual situation of parking service areas. This paper provides new ideas and methods to determine public parking garage service radius and service scope. Chao Zeng, Boming Tang, and Tangzhi Liu Copyright © 2016 Chao Zeng et al. All rights reserved. On a Gradient-Based Algorithm for Sparse Signal Reconstruction in the Signal/Measurements Domain Sun, 19 Jun 2016 11:27:18 +0000 Sparse signals can be recovered from a reduced set of samples by using compressive sensing algorithms. In common compressive sensing methods the signal is recovered in the sparsity domain. A method for the reconstruction of sparse signals which reconstructs the missing/unavailable samples/measurements is recently proposed. This method can be efficiently used in signal processing applications where a complete set of signal samples exists. The missing samples are considered as the minimization variables, while the available samples are fixed. Reconstruction of the unavailable signal samples/measurements is preformed using a gradient-based algorithm in the time domain, with an adaptive step. Performance of this algorithm with respect to the step-size and convergence are analyzed and a criterion for the step-size adaptation is proposed in this paper. The step adaptation is based on the gradient direction angles. Illustrative examples and statistical study are presented. Computational efficiency of this algorithm is compared with other two commonly used gradient algorithms that reconstruct signal in the sparsity domain. Uniqueness of the recovered signal is checked using a recently introduced theorem. The algorithm application to the reconstruction of highly corrupted images is presented as well. Ljubiša Stanković and Miloš Daković Copyright © 2016 Ljubiša Stanković and Miloš Daković. All rights reserved. Optimal Consumption and Portfolio Decision with Convertible Bond in Affine Interest Rate and Heston’s SV Framework Sun, 19 Jun 2016 11:02:11 +0000 We are concerned with an optimal investment-consumption problem with stochastic affine interest rate and stochastic volatility, in which interest rate dynamics are described by the affine interest rate model including the Cox-Ingersoll-Ross model and the Vasicek model as special cases, while stock price is driven by Heston’s stochastic volatility (SV) model. Assume that the financial market consists of a risk-free asset, a zero-coupon bond (or a convertible bond), and a risky asset. By using stochastic dynamic programming principle and the technique of separation of variables, we get the HJB equation of the corresponding value function and the explicit expressions of the optimal investment-consumption strategies under power utility and logarithmic utility. Finally, we analyze the impact of market parameters on the optimal investment-consumption strategies by giving a numerical example. Hao Chang and Xue-Yan Li Copyright © 2016 Hao Chang and Xue-Yan Li. All rights reserved. A Classification Model to Evaluate the Security Level in a City Based on GIS-MCDA Sun, 19 Jun 2016 08:43:45 +0000 The aim of this paper is to map the most favorable locations for the occurrence of robberies in the Brazilian city through the multicriteria method Dominance-Based Rough Set Approach. Considering the city divisions with alternatives and evaluating by several spatial criteria, a decision-maker is building a preference model with based previous knowledge. Next, decision rules induced from preference information are introduced to the spatial environment to get the results. The decision rules can be seen as conditional part (represented by criteria) and decision part (assignment to decision classes). The rules classify all the alternatives according to security level. Moreover, the rules help to understand the social dynamics of the city and to assist in the proposition of strategies against violence. Ciro José Jardim de Figueiredo and Caroline Maria de Miranda Mota Copyright © 2016 Ciro José Jardim de Figueiredo and Caroline Maria de Miranda Mota. All rights reserved. A General Solution to Least Squares Problems with Box Constraints and Its Applications Sun, 19 Jun 2016 07:03:07 +0000 The main contribution of this paper is presenting a flexible solution to the box-constrained least squares problems. This solution is applicable to many existing problems, such as nonnegative matrix factorization, support vector machine, signal deconvolution, and computed tomography reconstruction. The key concept of the proposed algorithm is to replace the minimization of the cost function at each iteration by the minimization of a surrogate, leading to a guaranteed decrease in the cost function. In addition to the monotonicity, the proposed algorithm also owns a few good features including the self-constraint in the feasible region and the absence of a predetermined step size. This paper theoretically proves the global convergence for a special case of below-bounded constraints. Using the proposed mechanism, some valuable algorithms can be derived. The simulation results demonstrate that the proposed algorithm provides performance that is comparable to that of other commonly used methods in numerical experiment and computed tomography reconstruction. Yueyang Teng, Shouliang Qi, Dayu Xiao, Lisheng Xu, Jianhua Li, and Yan Kang Copyright © 2016 Yueyang Teng et al. All rights reserved. Multidisciplinary Design Optimization of Crankshaft Structure Based on Cooptimization and Multi-Island Genetic Algorithm Sun, 19 Jun 2016 06:54:42 +0000 The feasibility design method with multidisciplinary and multiobjective optimization is applied in the research of lightweight design and NVH performances of crankshaft in high-power marine reciprocating compressor. Opt-LHD is explored to obtain the experimental scheme and perform data sampling. The elliptical basis function neural network (EBFNN) model considering modal frequency, static strength, torsional vibration angular displacement, and lightweight design of crankshaft is built. Deterministic optimization and reliability optimization for lightweight design of crankshaft are operated separately. Multi-island genetic algorithm (MIGA) combined with multidisciplinary cooptimization method is used to carry out the multiobjective optimization of crankshaft structure. Pareto optimal set is obtained. Optimization results demonstrate that the reliability optimization which considers the uncertainties of production process can ensure product stability compared with deterministic optimization. The coupling and decoupling of structure mechanical properties, NVH, and lightweight design are considered during the multiobjective optimization of crankshaft structure. Designers can choose the optimization results according to their demands, which means the production development cycle and the costs can be significantly reduced. Jian Liu, Gaoyuan Yu, Yao Li, Hongmin Wang, and Wensheng Xiao Copyright © 2016 Jian Liu et al. All rights reserved. Study of the Dynamic Characteristics of Ball Screw with a Load Disturbance Thu, 16 Jun 2016 11:47:46 +0000 The dynamic character of ball screw is the key factor that influences the machining accuracy of numerical control (NC) machine tool. To improve the dynamic characteristics of the NC machine tool, it is necessary to study the dynamic characteristics of a ball screw. In this paper, the kinematics of a ball screw mechanism (BSM) are studied to expound the dynamic process of the drive, and the load disturbance is considered to analyze the contact deformation based on the Hertzian contact theory. The velocity relationships among the ball, screw, and nut are analyzed, and the influence of the contact deformation on the dynamic characteristics is simulated and investigated experimentally. The results show that the relationships between the contact deformation, which is affected by the material characteristics, the contact angle, and the load of nut are nonlinear. The contact deformation is a factor that cannot be ignored when considering the dynamic machining error of high-speed and high-precision machine tools. Zhe Du, Xiao-Lan Zhang, and Tao Tao Copyright © 2016 Zhe Du et al. All rights reserved. Implementation of Real-Time Machining Process Control Based on Fuzzy Logic in a New STEP-NC Compatible System Thu, 16 Jun 2016 09:58:01 +0000 Implementing real-time machining process control at shop floor has great significance on raising the efficiency and quality of product manufacturing. A framework and implementation methods of real-time machining process control based on STEP-NC are presented in this paper. Data model compatible with ISO 14649 standard is built to transfer high-level real-time machining process control information between CAPP systems and CNC systems, in which EXPRESS language is used to define new STEP-NC entities. Methods for implementing real-time machining process control at shop floor are studied and realized on an open STEP-NC controller, which is developed using object-oriented, multithread, and shared memory technologies conjunctively. Cutting force at specific direction of machining feature in side mill is chosen to be controlled object, and a fuzzy control algorithm with self-adjusting factor is designed and embedded in the software CNC kernel of STEP-NC controller. Experiments are carried out to verify the proposed framework, STEP-NC data model, and implementation methods for real-time machining process control. The results of experiments prove that real-time machining process control tasks can be interpreted and executed correctly by the STEP-NC controller at shop floor, in which actual cutting force is kept around ideal value, whether axial cutting depth changes suddenly or continuously. Po Hu, Zhenyu Han, Yunzhong Fu, and Hongya Fu Copyright © 2016 Po Hu et al. All rights reserved.