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  • Articles  (5,055)
  • Hindawi  (4,473)
  • Institute of Electrical and Electronics Engineers (IEEE)
  • 2015-2019  (5,055)
  • 1990-1994
  • 1945-1949
  • 2018  (5,055)
  • Mathematics  (4,018)
  • Computer Science  (1,502)
  • Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics  (314)
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  • Articles  (5,055)
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  • 2015-2019  (5,055)
  • 1990-1994
  • 1945-1949
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  • 1
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    Improved Interference Cancelation Channel Estimation Method in OFDM/OQAM System (2018)
    Hindawi
    Details
    Publication Date: 2018
    Description: To the significant amount of pilot overhead of the interference cancelation methods in orthogonal frequency division multiplexing (OFDM) based on offset quadrature amplitude modulation (OFDM/OQAM) system, we proposed an improved interference cancelation method (ICM) for OFDM/OQAM system in this paper. In this method, we use the auxiliary pilot (AP) to eliminate the influence of the intersymbol interference on channel estimation, which can reduce the pilot overhead of OFDM/OQAM system significantly. At the same time, to improve the channel estimation performance, we analyze the source of the intrinsic interference of system and its distribution in time and frequency domain, then, we reset the interference cancelation range of AP, which can cancel more intrinsic interference for OFDM/OQAM system. According to the results of performance analysis, compared to the conventional interference cancelation methods, the proposed method performs better in terms of energy efficiency and spectral efficiency. Also, the simulation results of the proposed method show that the proposed method can outperform traditional interference cancelation methods in channel estimation performance.
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    Topics: Mathematics , Technology
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  • 2
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    Postbuckling and Free Nonlinear Vibration of Microbeams Based on Nonlinear Elastic Foundation (2018)
    Hindawi
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    Publication Date: 2018
    Description: In this paper, post-buckling and free nonlinear vibration of microbeams resting on nonlinear elastic foundation subjected to axial force are investigated. The equations of motion of microbeams are derived by using the modified couple stress theory. Using Galerkin’s method, the equation of motion of microbeams is reduced to the nonlinear ordinary differential equation. By using the equivalent linearization in which the averaging value is calculated in a new way called the weighted averaging value, approximate analytical expressions for the nonlinear frequency of microbeams with pinned–pinned and clamped–clamped end conditions are obtained in closed-forms. Comparisons with previous solutions are showed accuracy of the present solutions. Effects of the material length scale parameter and the axial compressive force on the frequency ratios of microbeams; and effect of the material length scale parameter on the buckling load ratios of microbeams are investigated in this paper.
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  • 3
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    Numerical Investigation of Combustion Characteristics of a Wave Rotor Combustor Based on a Reduced Reaction Mechanism of Ethylene (2018)
    Hindawi
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    Publication Date: 2018
    Description: To improve simulations of the flame and pressure wave propagation process and investigate the combustion characteristics of a wave rotor combustor (WRC), direct relation graphs with error propagation (DRGEP), quasi-steady-state assumption (QSSA), and sensitivity analysis were used to establish a reduced reaction mechanism comprised of 23 species and 55 elementary reactions, based on the LLNL N-Butane mechanism. The reduced reaction mechanism of ethylene was combined with an eddy dissipation concept (EDC) model to simulate the flame propagation characteristics in a simplified WRC channel. The effects of spoilers with different blockage ratios and hot-jets of different species on combustion characteristics of flame propagation and pressure rise in the WRC channel were investigated. When the heated inert air was used as hot-jet, the ignition delay time of WRC would increase, which indicated that the activity of the burned gas from the hot-jet igniter would affect the ignition delay time. The spoiler facilitates the coupling of flame and shock waves to reduce the coupling time and distance. With the blockage ratio of the spoiler increasing, the coupling time and distance would be reduced.
    Print ISSN: 1687-5966
    Electronic ISSN: 1687-5974
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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  • 4
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    A New Special Function and Its Application in Probability (2018)
    Hindawi
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    Publication Date: 2018
    Description: In this note we present a new special function that behaves like the error function and we provide an approximated accurate closed form for its CDF in terms of both Chèbyshev polynomials of the first kind and the error function. Also we provide its series representation using Padé approximant. We show a convincing numerical evidence about an accuracy of for the approximants in the sense of the quadratic mean norm. A similar approach may be applied to other probability distributions, for example, Maxwell–Boltzmann distribution and normal distribution, such that we show its application using both of those distributions.
    Print ISSN: 0161-1712
    Electronic ISSN: 1687-0425
    Topics: Mathematics
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  • 5
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    Constructions of Algebras and Their Field Theory Realizations (2018)
    Hindawi
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    Publication Date: 2018
    Description: We construct algebras for general “initial data” given by a vector space equipped with an antisymmetric bracket not necessarily satisfying the Jacobi identity. We prove that any such bracket can be extended to a 2-term algebra on a graded vector space of twice the dimension, with the 3-bracket being related to the Jacobiator. While these algebras always exist, they generally do not realize a nontrivial symmetry in a field theory. In order to define algebras with genuine field theory realizations, we prove the significantly more general theorem that if the Jacobiator takes values in the image of any linear map that defines an ideal there is a 3-term algebra with a generally nontrivial 4-bracket. We discuss special cases such as the commutator algebra of octonions, its contraction to the “R-flux algebra,” and the Courant algebroid.
    Print ISSN: 1687-9120
    Electronic ISSN: 1687-9139
    Topics: Mathematics , Physics
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  • 6
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    Vortex Structures inside Spherical Mesoscopic Superconductor Plus Magnetic Dipole (2018)
    Hindawi
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    Publication Date: 2018
    Description: We investigate the existence of multivortex states in a superconducting mesoscopic sphere with a magnetic dipole placed at the center. We obtain analytic solutions for the order parameter inside the sphere through the linearized Ginzburg-Landau (GL) model, coupled with mixed boundary conditions, and under regularity conditions and decoupling coordinates approximation. The solutions of the linear GL equation are obtained in terms of Heun double confluent functions, in dipole coordinates symmetry. The analyticity of the solutions and the associated eigenproblem are discussed thoroughly. We minimize the free energy for the fully nonlinear GL system by using linear combinations of linear analytic solutions, and we provide the conditions of occurring multivortex states. The results are not restricted to the particular spherical geometry, since the present formalism can be extended for large samples, up to infinite superconducting space plus magnetic dipole.
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  • 7
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    Explicit Solutions to the (3+1)-Dimensional Kudryashov-Sinelshchikov Equations in Bubbly Flow Dynamics (2018)
    Hindawi
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    Publication Date: 2018
    Description: A modified tanh-coth method with Riccati equation is used to construct several explicit solutions of (3+1)-dimensional Kudryashov-Sinelshchikov equations in bubble gas liquid flow. The solutions include solitons and periodic solutions. The method applied can be used in further works to obtain entirely new solutions to many other nonlinear evolution equations.
    Print ISSN: 1110-757X
    Electronic ISSN: 1687-0042
    Topics: Mathematics
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  • 8
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    Influences of Flow Attack Angles and Flow Directions on Heat Transfer Rate, Pressure Loss, and Thermal Performance in Heat Exchanger Tube with V-Wavy Surface (2018)
    Hindawi
    Details
    Publication Date: 2018
    Description: Numerical investigations on flow and heat transfer characteristics in the heat exchanger tube with the V-wavy surface are presented. The finite volume method with the SIMPLE algorithm is selected to solve the present problem. The effects of flow attack angles (α = 15°, 20°, 25°, 30°, 35°, 40°, 45°, 50°, 55°, and 60°) and flow directions (V-tip pointing downstream known as “V-Downstream” and V-tip pointing upstream known as “V-Upstream”) for the V-wavy surface on flow and heat transfer patterns are considered for both laminar and turbulent regions. The laminar regime is studied in the range Re = 100–1200, while the turbulent region is investigated in the range Re = 3000–10,000. The mechanisms on flow and heat transfer in the test section are reported. The numerical results reveal that the V-wavy surface changes the flow structure in the test section. The vortex flow is produced by the V-wavy surface. The vortex flow disturbs the thermal boundary layer on the heat transfer surface that is the reason for heat transfer and thermal performance enhancements. The optimum flow attack angles of the V-wavy surface for laminar and turbulent regimes are concluded.
    Print ISSN: 1687-5591
    Electronic ISSN: 1687-5605
    Topics: Computer Science , Technology
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  • 9
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    Implementation Flexibility of Multiperiod Rail Line Design with Consideration of Uncertainties in Population Distribution (2018)
    Hindawi
    Details
    Publication Date: 2018
    Description: This paper aims to investigate the implementation flexibility of multiperiod rail line design in a linear monocentric city. Three alternatives (fast-tracking, deferring, and do-nothing-alternative (DNA) of a candidate rail line project) are examined, based on an in-depth uncertainties analysis of the demand side for this candidate rail line project. Conditions for the three alternatives of fast-tracking, deferring, and DNA are analytically explored and an illustrative example is given to demonstrate the application of the proposed models. Insightful findings are reported on the interrelationship between the rail line length and spatial and temporal correlation of population distribution as well as the implication of the correlation in practice. Sensitivity analyses are carried out in several scenarios in another numerical example to show the proposed conditions of three alternatives.
    Print ISSN: 1026-0226
    Electronic ISSN: 1607-887X
    Topics: Mathematics
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  • 10
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    Optimization of Vehicle Routing with Pickup Based on Multibatch Production (2018)
    Hindawi
    Details
    Publication Date: 2018
    Description: To reduce the inventory cost and ensure product quality while meeting the diverse demands of customers, manufacturers yield products in batches. However, the raw materials required for manufacturing need to be obtained from suppliers in advance, making it necessary to understand beforehand how to best structure the pickup routes so as to reduce the cost of picking up and stocking while also ensuring the supply of raw materials required for each batch of production. To reduce the transportation and inventory costs, therefore, this paper establishes a mixed integer programming model for the joint optimization of multibatch production and vehicle routing problems involving a pickup. Following this, a two-stage hybrid heuristic algorithm is proposed to solve this model. In the first stage, an integrated algorithm, combining the Clarke-Wright (CW) algorithm and the Record to Record (RTR) travel algorithm, was used to solve vehicle routing problem. In the second stage, the Particle Swarm Optimization (PSO) algorithm was used to allocate vehicles to each production batch. Multiple sets of numerical experiments were then performed to validate the effectiveness of the proposed model and the performance efficiency of the two-stage hybrid heuristic algorithm.
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  • 11
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    Predicting Drivers’ Eyes-Off-Road Duration in Different Driving Scenarios (2018)
    Hindawi
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    Publication Date: 2018
    Description: Drivers consecutively direct their gaze to various areas to select relevant information from the traffic environment. The rate of crash risk increases with different off-road glance durations in different driving scenarios. This paper proposed an approach to identify current driving scenarios and predict driver’s eyes-off-road durations using Hidden Markov Model (HMM). A moving base driving simulator study with 26 participants driving in three driving scenarios (urban, rural, and motorway) was conducted. Three different fixed occlusion durations (0-s, 1-s, and 2-s) were applied to quantify eyes-off-road durations. Participants could initiate each occlusion for certain duration by pressing a microswitch on a finger. They were instructed to occlude their vision as often as possible while still driving safely. Drivers’ visual behavior and occlusion behavior were captured and analyzed based on manually frame by frame coding. Visual behaviors in terms of glance duration and glance location in time series were used as input to train HMMs. The results showed that current driving scenarios could be identified ideally using glance location sequences, the accuracy achieving up to 89.3%. And motorway was relatively distinguishable easily with over 90% accuracy. Moreover, HMM-based algorithms that fed up with both glance duration and glance location sequences resulted in a highest accuracy of 92.7% in driver’s eyes-off-road durations prediction. And higher accuracy achieved in longer eyes-off-road durations prediction. It indicates that time series of glance allocations could be used to predict driving behavior and indentify driving environment. The developed models in this study could contribute to the development of scenario sensitive visual inattention prewarning system.
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  • 12
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    Network Design towards Sustainability of Chinese Baijiu Industry from a Supply Chain Perspective (2018)
    Hindawi
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    Publication Date: 2018
    Description: Sustainable supply chain network design has attracted great attention of academia and industry in recent years. Baijiu is one of the world’s oldest distilled alcoholic beverages and plays a significant role in Chinese culture and Chinese people’s daily life. As the production and consumption of Baijiu have a significant influence on the economic, environmental, and social performance of supply chain management, sustainable supply chain network design decisions are critical to the long-term success of the industry. In concert with the rapidly growing Chinese economy, there is a growing demand for a sustainable Baijiu industry. Therefore, this paper constructs and optimizes a network decision-support model for a sustainable Baijiu industry network design. To achieve this, the Baijiu supply chain is examined and a model is proposed for a design that encompasses economic (costs), environmental (carbon emissions), and social (local employment and regional per capita GDP) dimensions. R language programming is then applied to solve the model. A case example indicated that S1 was the optimal decision for reducing costs, S2 was the optimal solution for minimizing carbon emissions, and S3 was the best for maximizing the social impact. Considering the situation of the Baijiu industry and the focal enterprise, it was concluded that S1 would be the best solution for the case company. And the results verified the effectiveness of the framework. This paper develops a systematic and effective approach that decision-makers can use to conduct sustainable network design for Baijiu enterprises.
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  • 13
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    An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester (2018)
    Hindawi
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    Publication Date: 2018
    Description: This paper proposes a new evolutionary multiobjective optimization technique for a linear compliant mechanism of nanoindentation tester. The mechanism design is inspired by the elastic deformation of flexure hinge. To improve overall static performances, a multiobjective optimization design was carried out. An efficient hybrid optimization approach of central composite design (CDD), finite element method (FEM), artificial neural network (ANN), and multiobjective genetic algorithm (MOGA) is developed to solve the optimization problem. In this procedure, the CDD is used to lay out the experimental data. The FEM is developed to retrieve the quality performances. And then, the ANN is developed as black box to call the pseudo-objective functions. Unlike previous studies on multiobjective evolutionary algorithms, most of which generating only one Pareto-optimal solution, this proposed approach can generate more than three Pareto-optimal solutions. Based on the user’s real-work problem, one of the best optimal solutions is chosen. The results showed that the optimal results were found at the displacement of 330.68 μm, stress of 140.65 MPa, and safety factor of 3.6. The statistical analysis is conducted to investigate the behavior of the MOGA. The sensitivity analysis was carried out to determine the significant contribution of each factor. The results revealed that the lengths and thickness almost significantly affect both responses. It confirms that the proposed hybrid optimization approach gains high robustness and effectiveness with flexible decision maker rules to solve complex optimization engineering problems.
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  • 14
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    The Secure Transmission of Videos Using the Karhunen-Loéve (K-L) Decomposition and the Synchronization of the Unified Chaotic System with the Hyperchaotic Chen System (2018)
    Hindawi
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    Publication Date: 2018
    Description: A unique secure communication scheme that can be used for the transmission of gray-scale and color videos is presented in this paper. The proposed scheme is developed by using the Karhunen-Loéve (K-L) decomposition and the synchronization of the unified chaotic system with the hyperchaotic Chen system. First, the gray-scale or color video is represented by a set of frames. In order to reduce the data, the K-L decomposition is used to come up with data coefficients and eigenfunctions that optimally obtain the crux of the frames. Using only the most energetic eigenfunctions to approximate the original frames results in computational savings. The data coefficients corresponding to the most energetic eigenfunctions are encrypted and transmitted using a master system composed of a combination of the unified chaotic system and the hyperchaotic Chen system. At the receiver end, these coefficients are recovered and a controller of the sliding mode type is utilized forcing the master and slave systems to synchronize. Simulation results illustrate how the proposed control law is able to synchronize the master and the slave systems. In addition, a demonstration of the recovery of the original frames using the decrypted data coefficients along with the eigenfunctions of the frame is provided. The presented simulations indicate that the proposed scheme results in an excellent performance.
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  • 15
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    Evaluation of Heat Irreversibility in a Thin Film Flow of Couple Stress Fluid on a Moving Belt (2018)
    Hindawi
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    Publication Date: 2018
    Description: This article addresses the inherent heat irreversibility in the flow of a couple stress thin film along a moving vertical belt subjected to free and adiabatic surface. Mathematical analysis for the fluid-governing-equations is performed in detail. For maximum thermal performance and efficiency, the present analysis follows the second law of thermodynamics approach for the evaluation of entropy generation rate in the moving film. With this thermodynamic process, the interconnectivity between variables responsible for energy wastage is accounted for in the thermo-fluid equipment. Results of the analysis revealed the fluid properties that contribute more to energy loss and how the exergy of the system can be restored.
    Print ISSN: 1687-9120
    Electronic ISSN: 1687-9139
    Topics: Mathematics , Physics
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  • 16
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    Local Well-Posedness and Blow-Up for the Solutions to the Axisymmetric Inviscid Hall-MHD Equations (2018)
    Hindawi
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    Publication Date: 2018
    Description: In this paper, we consider the regularity problem of the solutions to the axisymmetric, inviscid, and incompressible Hall-magnetohydrodynamics (Hall-MHD) equations. First, we obtain the local-in-time existence of sufficiently regular solutions to the axisymmetric inviscid Hall-MHD equations without resistivity. Second, we consider the inviscid axisymmetric Hall equations without fluids and prove that there exists a finite time blow-up of a classical solution due to the Hall term. Finally, we obtain some blow-up criteria for the axisymmetric resistive and inviscid Hall-MHD equations.
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  • 17
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    Continuous Approximation for Interaction Energy Transfer of DNA through Lipid Bilayers (2018)
    Hindawi
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    Publication Date: 2018
    Description: In this study the interaction energies for single-stranded DNA and double-stranded DNA molecules with a lipid bilayer are investigated. The 6-12 Lennard-Jones potential and continuous approximation are used to derive analytical expressions for these interaction energies. Assuming that there is a circular gap in the lipid bilayer, we determine the relationship of the molecular interaction energy, including the circular gap radius and the perpendicular distance of the single-stranded DNA and double-stranded DNA molecules from the gap. For both single-stranded and double-stranded DNA molecules, the relationship between the minimum energy location and the hole radius is calculated; in the case of the double-stranded DNA molecule, we assume that the helical phase angle is equal to . By minimizing the total interaction energies, the results demonstrate that the single-stranded DNA and double-stranded DNA molecules move through a lipid bilayer when the gap radius 10 Å and 13.8 Å, respectively. The results present in this project can be leveraged to understand the interactions between cell-penetrating peptides and biomembranes, which may improve gene and drug delivery.
    Print ISSN: 1026-0226
    Electronic ISSN: 1607-887X
    Topics: Mathematics
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  • 18
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    Basic Properties and Qualitative Dynamics of a Vector-Borne Disease Model with Vector Stages and Vertical Transmission (2018)
    Hindawi
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    Publication Date: 2018
    Description: This work systematically discusses basic properties and qualitative dynamics of vector-borne disease models, particularly those with vertical transmission in the vector population. Examples of disease include Dengue and Rift Valley fever which are endemic in Sub-Saharan Africa, and understanding of the dynamics underlying their transmission is central for providing critical informative indicators useful for guiding control strategies. Of particular interest is the applicability and derivation of relevant population and epidemic thresholds and their relationships with vertical infection. This study demonstrates how the failure of derived using the next-generation method compounds itself when varying vertical transmission efficiency, and it shows that the host type reproductive number gives the correct . Further, novel relationships between the host type reproductive number, vertical infection, and ratio of female mosquitoes to host are established and discussed. Analytical results of the model with vector stages show that the quantities ,, and , which represent the vector colonization threshold, the average number of female mosquitoes produced by a single infected mosquito, and effective reproductive number, respectively, provide threshold conditions that determine the establishment of the vector population and invasion of the disease. Numerical simulations are also conducted to confirm and extend the analytical results. The findings imply that while vertical infection increases the size of an epidemic, it reduces its duration, and control efforts aimed at reducing the critical thresholds ,, and to below unity are viable control strategies.
    Print ISSN: 1110-757X
    Electronic ISSN: 1687-0042
    Topics: Mathematics
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  • 19
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    Comment on “Storage and Dissipation Limits in Resonant Switched-Capacitor Converters” (2018)
    Hindawi
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    Publication Date: 2018
    Description: The purpose of this note is (i) to point to a reference missing in the paper (Mayo-Maldonado et al., 2018) and (ii) to show that some of its content is covered in a more general setting by the results in that reference (Göknar, 1972).
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  • 20
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    Response to: Comment on “Storage and Dissipation Limits in Resonant Switched-Capacitor Converters” (2018)
    Hindawi
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    Publication Date: 2018
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  • 21
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    Dynamic Characteristics and Load Sharing of Herringbone Wind Power Gearbox (2018)
    Hindawi
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    Publication Date: 2018
    Description: In this study, the dynamic model for the herringbone planetary gear transmission system is established by the lumped parameter method based on the system dynamics and the Lagrange equation, and the impact of the support stiffness and the torsional stiffness on dynamic characteristics is studied. The research results have a guiding significance for the design of the herringbone gear transmission system. In this model, the herringbone gear is treated as a special gear coupled by 2 opposite helical gears, where the stagger angle, comprehensive meshing error, support stiffness, support damping, and load inertia are considered in the analysis of dynamics. Moreover, the dynamic characteristic of the carrier is considered as well. By calculating the meshing force curve of the transmission system, the impact of the stagger angle, supporting stiffness, and the torsional stiffness on meshing force and load sharing coefficient is analyzed. The results show that the stagger angle has an obvious impact on load sharing coefficient while it has little impact on maximum meshing force. And the support stiffness has a more obvious impact on the dynamic characteristics of the system. The recommendary support stiffness of the system is that all of the support stiffness of the sun gear, planetary gear, ring gear, and carrier is 107 N/m. The torsional stiffness has little impact on the dynamic characteristics of transmission system, except the torsional stiffness of planetary gear, and carrier has an obvious impact on load sharing coefficient. The commercial software ADAMS carried out dynamics analysis of the transmission system to verify the necessity validity of the theoretical analysis.
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  • 22
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    Transient Pressure and Rate Decline Analysis for Horizontal Well in Stress-Sensitive Composite Reservoir (2018)
    Hindawi
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    Publication Date: 2018
    Description: The existence of stress sensitivity effect made the percolation mechanism of low-permeability reservoirs significantly complex. Further, numerous reservoirs have composite stratum properties in actual development procedure. This paper based on the concept of permeability stress sensitivity presents an unsteady flow model for horizontal well taking both stress sensitivity and composite reservoir into account. Analytic solutions for the transient pressure and the rate decline behaviors are obtained by comprehensive utilization of regular perturbation method, Laplace transformation, orthogonal transformation, and Stehfest numerical inversion. The example analysis verifies that the proposed model is reliable and practical. Likewise, there is a discussion of the influence of permeability modulus and other relevant parameters on the transient pressure and the rate decline for horizontal well in stress-sensitive composite reservoir. The work of this paper improved the previous researches and provided a more accurate basis for transient flow analysis and formation evaluation of this typical reservoir.
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  • 23
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    Binary Particle Swarm Optimization-Based Association Rule Mining for Discovering Relationships between Machine Capabilities and Product Features (2018)
    Hindawi
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    Publication Date: 2018
    Description: An effective data mining method to automatically extract association rules between manufacturing capabilities and product features from the available historical data is essential for an efficient and cost-effective product development and production. This paper proposes a new binary particle swarm optimization- (BPSO-) based association rule mining (BPSO-ARM) method for discovering the hidden relationships between machine capabilities and product features. In particular, BPSO-ARM does not need to predefine thresholds of minimum support and confidence, which improves its applicability in real-world industrial cases. Moreover, a novel overlapping measure indication is further proposed to eliminate those lower quality rules to further improve the applicability of BPSO-ARM. The effectiveness of BPSO-ARM is demonstrated on a benchmark case and an industrial case about the automotive part manufacturing. The performance comparison indicates that BPSO-ARM outperforms other regular methods (e.g., Apriori) for ARM. The experimental results indicate that BPSO-ARM is capable of discovering important association rules between machine capabilities and product features. This will help support planners and engineers for the new product design and manufacturing.
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  • 24
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    The Aerodynamic Behavioral Study of Tandem Fan Wing Configuration (2018)
    Hindawi
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    Publication Date: 2018
    Description: The fan wing aircraft is a new concept based on a new principle, especially its wing which is based on a unique aerodynamic principle. A fan wing can simultaneously generate lift and thrust. In order to further improve its aerodynamic characteristics without changing its basic geometric parameters, two fan wings are installed along the longitudinal body, which is the composition of a tandem fan wing aircraft. Through numerical simulation, the lift and thrust of the fan wings were calculated with the distance, height, and installation angle of the front and rear fan wings changed, and the aerodynamic characteristic interaction rule between the front and rear fan wings was analyzed. In addition, the wind test model of a tandem fan wing was designed, and the results of the wind tunnel test and numerical calculation results were compared to verify the preliminary setup. The results show that at a certain height, distance, and installation angle, aerodynamic characteristics of a tandem fan wing have more advantages compared to the single fan wing. Therefore, the tandem fan wing aircraft’s advantages have good prospects for development and application.
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    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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    Preliminary Thermal Design and Analysis of Lunar Lander for Night Survival (2018)
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    Publication Date: 2018
    Description: A lunar lander is exposed to extreme lunar thermal environments with a nighttime of 14.75 earth days. Thus, a proper thermal design is an important task to guarantee a successful lunar mission. This paper describes a preliminary thermal design and analysis results of a lunar lander to ensure its survivability during lunar night. The effectiveness of the thermal designs of a lunar lander with various thermal hardwares was numerically investigated according to the landing candidate areas to determine which design is the most feasible for night survival. In addition, we analyzed the mechanical safety of the solder joint of electronic components in accordance with the operating temperature range, because it is an important factor for reducing the system power budget during night survival.
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    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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    Research on Prediction Method of Performance Degradation of Flexible Optoelectronic Film Material Processing Equipment Based on Adaptive Fuzzy Clustering (2018)
    Hindawi
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    Publication Date: 2018
    Description: Flexible photoelectric film is an anisotropic material. The slight change of equipment performance during processing is prone to cause deformation of the material. Therefore, it is important to predict the degradation of processing equipment performance. Since the performance degradation of flexible photoelectric film material Roll-to-Roll (R2R) processing equipment is a nonlinear process, this paper introduces an adaptive fuzzy clustering method to construct a fuzzy membership function model for calculating the performance degradation index of R2R processing equipment and studies the parameter solving method such as the AFCM division of the roller vibration data, the category center value of the fuzzy membership function, and the input data division area width. Finally, the performance degradation index calculation algorithm is designed. The roller shaft accelerated life test was carried out using self-made equipment. The test data were 1000 sets. The results showed that the root mean square eigenvalues and the kurtosis eigenvalues of the roller vibration data are sensitive to the performance degradation. The equipment performance curve described by the first and second types of performance degradation indicators was very stable in the early stage. After the group, the curve continued to decrease, and the change was more severe, indicating that the performance degradation of the equipment is more serious. In the group, the longer-lasting roller shaft was damaged, and the performance index value was about zero, which proved the correctness of the performance degradation prediction method proposed in this paper in calculating the performance degradation value of the equipment.
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    Pattern Recognition: Recent Advances and Applications (2018)
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    Publication Date: 2018
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    Detection of Broken Rotor Bars Fault in Induction Motors by Using an Improved MUSIC and Least-Squares Amplitude Estimation (2018)
    Hindawi
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    Publication Date: 2018
    Description: The frequencies and amplitudes of the broken rotor bar (BRB) fault features are the basis for the accurate diagnosis of the BRB fault. However, how to accurately detect their frequency and amplitudes has always been a difficult problem for induction motor fault detection. For this problem, a new fault detection method based on an improved multiple signal classification (MUSIC) and least-squares magnitude estimation is proposed. First, since the fixed-step traversal search reduces the computational efficiency of MUSIC, a niche bare-bones particle swarm optimization (NBPSO) for multimodal peaks search is proposed to improve MUSIC, which is used to compute the frequency values of fault-related and fundamental components in stator current signal. Second, using these frequency values, a fault current signal model is established to convert the magnitude estimation problem into a linear least-squares problem. On this basis, the amplitudes and phases of fault-related and fundamental components could be estimated accurately with the singular value decomposition (SVD). A simulation signal is used to test the new method and the results show that the proposed method not only has higher frequency resolution, but also improves estimation accuracy of parameters greatly even with short data window. Finally, experiments for a real induction motor are performed, and the effectiveness and superiority of the proposed method are proved again.
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    A Node Selection Paradigm for Crowdsourcing Service Based on Region Feature in Crowd Sensing (2018)
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    Publication Date: 2018
    Description: Crowd sensing is a human-centered sensing model. Through the cooperation of multiple nodes, an entire sensing task is completed. To improve the efficiency of sensing missions, a cost-effective set of service nodes, which is easy to fit in performing different tasks, is needed. In this paper, we propose a low-cost service node selection method based on region features, which builds on the relationship between task requirements and geographical locations. The method uses Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm to cluster service nodes and calculate the center point of each cluster. The area then is divided into regions according to rules of Voronoi diagrams. Local feature vectors are constructed according to the historical records in each divided region. When a particular sensing task arrives, Analytic Hierarchy Process (AHP) is used to match the feature vector of each region to mission requirements to get a certain number of service nodes satisfying the characteristics. To get a lower cost output, a revised Greedy Algorithm is designed to filter the exported service nodes to get the required low-cost service nodes. Experimental results suggest that the proposed method shows promise in improving service node selection accuracy and the timeliness of finishing tasks.
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    Exponential Stability of Antiperiodic Solution for BAM Neural Networks with Time-Varying Delays (2018)
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    Publication Date: 2018
    Description: In this paper, a kind of BAM neural networks with leakage delays in the negative feedback terms and time-varying delays in activation functions was considered. By constructing a suitable Lyapunov function and using inequality techniques, some sufficient conditions to ensure the existence and exponential stability of antiperiodic solutions of these neural networks were derived. These conditions extend some results recently appearing in recent papers. Lastly, an example is given to show the feasibility of these conditions.
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    Traffic Signal Coordination for Tramlines with Passive Priority Strategy (2018)
    Hindawi
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    Publication Date: 2018
    Description: Prioritizing traffic signals for trams crossing intersections without stops can increase the service punctuality and travel speed of trams, but it may also increase the delays of other vehicles at intersections. This paper presents a model on coordinated control of traffic signals among successive intersections along the tramline, taking into account driving characteristics of trams and vehicles. The objective is maximizing the valid bandwidth of vehicle green wave to reduce vehicle delays, while the trams cross intersections without stops. Linear Interactive and General Optimizer (LINGO) is applied to solve the proposed model and VISSIM simulation software is adopted to assess the solutions attained by the proposed model and the previous TRAMBAND model. Case studies show that the solutions given by the proposed model facilitate trams to go through all intersections along the tramline without stops. In comparison with the TRAMBAND model, the proposed model reduces tram delay by 13.14 s/pcu and increases the throughput of vehicles at intersections by 4.45% and reduces vehicle delays by 2.22%. Extensive simulations have verified that the performance of the proposed model is stable under different tram headways, dwell time, and traffic volumes. It is also found that the tram headway must be multiple of traffic signal cycle time to completely realize green wave control of all trams at all intersections along the tramline.
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    Measuring Sustainable Development Efficiency of Urban Logistics Industry (2018)
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    Publication Date: 2018
    Description: Logistics plays a basic supporting role in the growth of national economy. However, tail gas, noise, and traffic congestion caused by logistics have a negative impact on the environment. An effective evaluation mechanism for sustainable development of urban logistics industry is necessary. Data envelopment analysis (DEA) is a common tool for efficiency evaluation. But, DEA has a limited effect on resource allocation in advance because it is ex-post evaluation. It requires input-output indications and the output is after-the-fact data. This defect is particularly prominent in the evaluation of ecological logistics because pollution indicators belong to ex-post output data that threaten the human environment. First prediction and then evaluation is a possible idea. In addition, DEA efficiency ranking does not have a good discrimination due to its coarse granularity. To solve the issues, combining DEA with the Bayes method, we propose an efficiency evaluation model without after-the-fact data, where an efficiency level is predicted and an evaluation value is calculated according to different investment combinations. Then, it is applied to logistics industries of Jiangsu province in China. The results show that our DEA-Bayes method has good discrimination and is easy to operate; a city with geographical advantage and environmental awareness generally gets a higher efficiency score. So the method can help decision makers to allocate resources rationally and further promote the coordinated development of logistics industry.
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    A Phase-Based Adaptive Differential Evolution Algorithm for the Economic Load Dispatch Considering Valve-Point Effects and Transmission Losses (2018)
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    Publication Date: 2018
    Description: A phase-based adaptive differential evolution (PADE) algorithm is proposed to solve the economic load dispatch (ELD) considering valve-point effects (VPE) and transmission losses. To a great extent, PADE makes up for the drawbacks of the traditional differential evolution (DE) through three improvements. First, we establish an archive of storing successful individuals to improve the quality of offspring. Second, to balance the exploring and exploiting ability of the algorithm, a phase-based mutation operation is carried out. Third, two control parameters are adaptively adjusted, which is helpful for enhancing the robustness of the algorithm. In addition, two types of repair methods of constraint handling are employed for the ELD without or with transmission losses to help PADE find feasible solutions more efficiently. A performance comparison between PADE and other DE approaches from the literature was carried out on six ELD test cases which consider a set of operating constraints including the VPE and transmission losses. Results show a competitive PADE performance in all test cases regarding the compared DE approaches. Compared to methods from the literature, the costs obtained by PADE are lower in most cases while the corresponding constraint violations reach a lower level.
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    Short-Term Traffic Flow Forecasting Method Based on LSSVM Model Optimized by GA-PSO Hybrid Algorithm (2018)
    Hindawi
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    Publication Date: 2018
    Description: Short-term traffic flow forecasting is one of the key issues in the field of dynamic traffic control and management. Because of the uncertainty and nonlinearity, short-term traffic flow forecasting remains a challenging task. In order to improve the accuracy of short-term traffic flow forecasting, a short-term traffic flow forecasting method based on LSSVM model optimized by GA-PSO hybrid algorithm is put forward. Firstly, the LSSVM model is constructed with combined kernel function. Then the GA-PSO hybrid optimization algorithm is designed to optimize the kernel function parameters efficiently and effectively. Finally, case validation is carried out using inductive loop data collected from the north-south viaduct in Shanghai. The experimental results demonstrate that the proposed GA-PSO-LSSVM model is superior to comparative method.
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    Optimal Control Strategy for a Discrete Time Smoking Model with Specific Saturated Incidence Rate (2018)
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    Publication Date: 2018
    Description: The aim of this paper is to study and investigate the optimal control strategy of a discrete mathematical model of smoking with specific saturated incidence rate. The population that we are going to study is divided into five compartments: potential smokers, light smokers, heavy smokers, temporary quitters of smoking, and permanent quitters of smoking. Our objective is to find the best strategy to reduce the number of light smokers, heavy smokers, and temporary quitters of smoking. We use three control strategies which are awareness programs through media and education, treatment, and psychological support with follow-up. Pontryagins maximum principle in discrete time is used to characterize the optimal controls. The numerical simulation is carried out using MATLAB. Consequently, the obtained results confirm the performance of the optimization strategy.
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    Tolerance Analysis of Over-Constrained Assembly Considering Gravity Influence: Constraints of Multiple Planar Hole-Pin-Hole Pairs (2018)
    Hindawi
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    Publication Date: 2018
    Description: Over-constrained assembly of rigid parts is widely adopted in aircraft assembly to yield higher stiffness and accuracy of assembly. Unfortunately, the quantitative tolerance analysis of over-constrained assembly is challenging, subject to the coupling effect of geometrical and physical factors. Especially, gravity will affect the geometrical gaps in mechanical joints between different parts, and thus influence the deviations of assembled product. In the existing studies, the influence of gravity is not considered in the tolerance analysis of over-constrained assembly. This paper proposes a novel tolerance analysis method for over-constrained assembly of rigid parts, considering the gravity influence. This method is applied to a typical over-constrained assembly with constraints of multiple planar hole-pin-hole pairs. This type of constraints is non-linear, which makes the tolerance analysis more challenging. Firstly, the deviation propagation analysis of an over-constrained assembly is conducted. The feasibility of assembly is predicted, and for a feasible assembly, the assembly deviations are determined with the principle of minimum potential energy. Then, the statistical tolerance analysis is performed. The probabilities of assembly feasibility and quality feasibility are computed, and the distribution of assembly deviations is estimated. Two case studies are presented to show the applicability of the proposed method.
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    Identification of a Time-Dependent Coefficient in Heat Conduction Problem by New Iteration Method (2018)
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    Publication Date: 2018
    Description: This paper investigates the problem of identifying unknown coefficient of time dependent in heat conduction equation by new iteration method. In order to use new iteration method, we should convert the parabolic heat conductive equation into an integral equation by integral calculus and initial condition. This method constructs a convergent sequence of function, which approximates the exact solution with a few iterations and does not need complex calculation. Illustrative examples are given to demonstrate the efficiency and validity.
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    Modified Empirical Eigenfunctions and Its Applications for Model Reduction of Nonlinear Spatiotemporal Systems (2018)
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    Publication Date: 2018
    Description: Model reduction can greatly reduce complexity and difficulty of control design for spatiotemporal systems (STS) in engineering applications. Empirical eigenfunctions (EEFs) are widely used for the model reduction of spatiotemporal systems, however, truncation of higher modes may describe the behaviours of nonlinear spatiotemporal systems inaccurately. In this paper, modified EEFs are proposed and applied to model reduction of nonlinear spatiotemporal systems. Modified EEFs are obtained via modifying the weights matrix in the method of snapshots, which can be rewritten as linear combinations of initial EEFs. The coefficient matrix for combinations is computed according to the nonlinear temporal dynamics of STSs. Thus, the effects of higher modes are considered into modified EEFs with less computational requirements. The reduced model can give a more accurate description for behaviours of the system. The performance of the proposed method is further proved theoretically, and a numerical example demonstrates the effectiveness of the proposed method.
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    A Compound Structure for Wind Speed Forecasting Using MKLSSVM with Feature Selection and Parameter Optimization (2018)
    Hindawi
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    Publication Date: 2018
    Description: The aims of this study contribute to a new hybrid model by combining ensemble empirical mode decomposition (EEMD) with multikernel function least square support vector machine (MKLSSVM) optimized by hybrid gravitation search algorithm (HGSA) for short-term wind speed prediction. In the forecasting process, EEMD is adopted to make the original wind speed data decomposed into intrinsic mode functions (IMFs) and one residual firstly. Then, partial autocorrelation function (PACF) is applied to identify the correlation between the corresponding decomposed components. Subsequently, the MKLSSVM using multikernel function of radial basis function (RBF) and polynomial (Poly) kernel function by weight coefficient is exploited as core forecasting engine to make the short-term wind speed prediction. To improve the regression performance, the binary-value GSA (BGSA) in HGSA is utilized as feature selection approach to remove the ineffective candidates and reconstruct the most relevant feature input-matrix for the forecasting engine, while real-value GSA (RGSA) makes the parameter combination optimization of MKLSSVM model. In the end, these respective decomposed subseries forecasting results are combined into the final forecasting values by aggregate calculation. Numerical results and comparable analysis illustrate the excellent performance of the EEMD-HGSA-MKLSSVM model when applied in the short-term wind speed forecasting.
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    Speed Control for a Marine Diesel Engine Based on the Combined Linear-Nonlinear Active Disturbance Rejection Control (2018)
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    Publication Date: 2018
    Description: In this paper, a compound control scheme with linear active disturbance rejection control (LADRC) and nonlinear active disturbance rejection control (NLADRC) is designed to stabilize the speed control system of the marine engine. To deal with the high nonlinearity and the complex disturbance and noise conditions in marine engines, the advantages of both LADRC and NLADRC are employed. As the extended state observer (ESO) is affected severely by the inherent characteristics (cyclic speed fluctuation, cylinder-to-cylinder deviations, etc.) of the reciprocating engines, a cycle-detailed hybrid nonlinear engine model is adopted to analyze the impact of such characteristics. Hence, the controller can be evaluated based on the modified engine model to achieve more reliable performance. Considering the mentioned natural properties in reciprocating engines, the parameters of linear ESO (LESO), nonlinear ESO (NLESO), and the switching strategy between LADRC and NLADRC are designed. Finally, various comparative simulations are carried out to show the effectiveness of the proposed control scheme and the superiority of switching strategy. The simulation results demonstrate that the proposed control scheme has prominent control effects both under the speed tracking mode and the condition with different types and levels of load disturbance. This study also reveals that when ADRC related approaches are employed to the reciprocating engine, the impact of the inherent characteristics of such engine on the ESO should be considered well.
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    Model-Based Testing Applied to Software Components of Satellite Simulators (2018)
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    Publication Date: 2018
    Description: Operational simulators have a fundamental role in space programs. During a satellite operation, these simulators are essential for validating critical manoeuvres, testing new on-board software versions, and supporting the diagnosis of anomalies. With the purpose of reusing the operational simulators, the Brazilian National Institute for Space Research has proposed a new standard for the specification of the components that must be integrated in their in-house developed simulators. The new standard describes the behaviour of satellite subsystems using cause-effect tables that relate telecommands, electrical switches, equipment working states, energy consumption, telemetries, and operating modes of the subsystem. Using this new standard as input, this work proposes an approach that merges model-based testing and model checking to verify the correct implementation of new components in the satellite simulator. The verification approach consists of extracting state machines from the cause-effect tables and used it to automatically derive a test case suite. In order to validate the proposal, we applied it to three different satellite subsystems and assessed the results obtained from the test campaigns. In all the three cases, the proposed approach identified errors in the simulator components that were not initially detected by the traditional testing approach used at the Brazilian National Institute for Space Research.
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    Multi-Parameter Dominant Grouping of Discontinuities in Rock Mass Using Improved ISODATA Algorithm (2018)
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    Publication Date: 2018
    Description: The dominant grouping of the discontinuities in a rock mass is crucial to investigating the rock structure and stability. The traditional grouping methods are mostly based on the discontinuity orientation. However, other discontinuity parameters nonnegligibly impact the properties of a rock mass. If two discontinuities have the same orientation but differ otherwise, their mechanical and hydraulic properties would differ. In the present study, orientation, trace length, opening degree, and undulation of discontinuities were used to develop a multi-parameter dominant discontinuity grouping method that utilizes an improved ISODATA algorithm. The developed method uses several indicators, such as the weighted Euclidean distance and standard deviation, to iteratively update the clustering centers of the discontinuities. A clustering validity index was introduced for assessment and optimization of the discontinuity grouping results, and an adaptive grouping model that considers the weight of each grouping parameter was developed. By grouping discontinuities generated by Monte Carlo stochastic simulation, defects existing in the grouping based on the orientation only were illustrated, and the rationality of the established adaptive grouping model was verified. The engineering practicability of the method was further verified by using it to group discontinuities measured in the Dongsheng Quarry in Jingyuetan, Changchun, China.
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    Existence of Positive Ground State Solution for the Nonlinear Schrödinger-Poisson System with Potentials (2018)
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    Publication Date: 2018
    Description: In the present paper we study the existence of positive ground state solutions for the nonautonomous Schrödinger-Poisson system with competing potentials. Under some assumptions for the potentials we prove the existence of positive ground state solution.
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    A Novel Ensemble Wind Speed Forecasting Model in the Longdong Area of Loess Plateau in China (2018)
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    Publication Date: 2018
    Description: Energy is the lifeline and the base of development of social economy in every country or area. However, with the increasing depletion of fossil energy, it is imperative for business managers and government policy makers to seek and utilize new energy resources for keeping the national economy development sustained, rapid, and healthy. As a new energy resource, wind energy is developing with a high speed in the world for the reasons that it is an abundant natural resource with the characteristics of renewable, low cost, and no pollution. But in reality, forecasting wind speed accurately is continuously a challenging subject in the field of the wind energy development for a long time. In this paper, a novel ensemble wind speed forecasting model based on machine leaning models and hybrid models with data preprocessing technology is proposed to forecast the wind speed effectively in the Longdong area of Loess Plateau in China; numerical results show that the ensemble model has better precision, adaptability, and robustness.
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    A Disruption Recovery Problem with Time Windows Change in the Last Mile Delivery of Online Shopping (2018)
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    Publication Date: 2018
    Description: Frequent time window changing disruptions result in high secondary delivery rates in the last mile delivery. With the rapid growth of parcel volumes in online shopping, the time window changing disruptions could translate to substantial delivery cost-wastes. In recent years, customer pickup (CP), a new delivery mode that allows customers to pick up their parcels from shared delivery facilities, has provided a new way to deal with such disruptions. This study proposed a disruption recovery problem with time windows change in the last mile delivery in which customers can be served through home delivery (HD) or CP. A variant variable neighborhood descent (VVND) algorithm was presented to solve the problem. Computational experiments based on a set of instances were tested, and results were compared with other heuristics in the literature, which have affirmed the competitiveness of the model and algorithm.
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    Forecasting the Direction of Short-Term Crude Oil Price Changes with Genetic-Fuzzy Information Distribution (2018)
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    Publication Date: 2018
    Description: This paper proposes a novel approach to the directional forecasting problem of short-term oil price changes. In this approach, the short-term oil price series is associated with incomplete fuzzy information, and a new fused genetic-fuzzy information distribution method is developed to process such a fuzzy incomplete information set; then a feasible coding method of multidimensional information controlling points is adopted to fit genetic-fuzzy information distribution to time series forecasting. Using the crude oil spot prices of West Texas Intermediate (WTI) and Brent as sample data, the empirical analysis results demonstrate that the novel fused genetic-fuzzy information distribution method statistically outperforms the benchmark of logistic regression model in prediction accuracy. The results indicate that this new approach is effective in direction accuracy.
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    Stability Analysis and Control Optimization of a Prey-Predator Model with Linear Feedback Control (2018)
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    Description: The application of pest management involves two thresholds when the chemical control and biological control are adopted, respectively. Our purpose is to provide an appropriate balance between the chemical control and biological control. Therefore, a Smith predator-prey system for integrated pest management is established in this paper. In this model, the intensity of implementation of biological control and chemical control depends linearly on the selected control level (threshold). Firstly, the existence and uniqueness of the order-one periodic solution (i.e., OOPS) are proved by means of the subsequent function method to confirm the feasibility of the biological and chemical control strategy of pest management. Secondly, the stability of system is proved by the limit method of the successor points’ sequences and the analogue of the Poincaré criterion. Moreover, an optimization strategy is formulated to reduce the total cost and obtain the best level of pest control. Finally, the numerical simulation of a specific model is performed.
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    Design and Simulation of Eight-Rotor Unmanned Aerial Vehicle Based on Hybrid Control System (2018)
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    Publication Date: 2018
    Description: In order to control the position and attitude of unmanned aerial vehicle (UAV) better in different environments, this study proposed a hybrid control system with backstepping and PID method for eight-rotor UAV in different flight conditions and designed a switching method based on altitude and attitude angle of UAV. The switched process of hybrid controller while UAV taking off, landing, and disturbance under the gust is verified in MATLAB/Simulink. A set of appropriate controllers always matches to the flight of UAV in different circumstances, which can speed up the system response and reduce the steady-state error to improve stability. The simulation results show that the hybrid control system can suppress the drift efficiently under gusts, enhance the dynamic performance and stability of the system, and meet the position and attitude of flight control requirements.
    Print ISSN: 1687-5966
    Electronic ISSN: 1687-5974
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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    Health Status Assessment for Wind Turbine with Recurrent Neural Networks (2018)
    Hindawi
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    Publication Date: 2018
    Description: In order to improve the safety, efficiency, and reliability in large scale wind turbines, a great deal of statistical and machine-learning models for wind turbine health monitoring system (WTHMS) are proposed based on SCADA variables. The data-driven WTHMS have been performed widely with the attentions on predicting the failures of the wind turbine or primary components. However, the health status of wind turbine often degrades gradually rather than suddenly. Thus, the SCADA variables change continuously to the occurrence of certain faults. Inspired by the ability of recurrent neural network (RNN) in redefining the raw sensory data, we introduce a hybrid methodology that combines the analysis of variance for each sequential SCADA variable with RNN to assess the health status of wind turbine. First, each original sequence is split by different variance ranges into several categories to improve the generalized ability of the RNN. Then, the long short-term memory (LSTM) is procured on the normal running sequence to learn the gradually changing situations. Finally, a weighted assessment method incorporating the health of primary components is applied to judge the health level of the wind turbine. Experiments on real-world datasets from two wind turbines demonstrate the effectiveness and generalization of the proposed model.
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    Classical and Quantum Exact Solutions for a FRW Multiscalar Field Cosmology with an Exponential Potential Driven Inflation (2018)
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    Publication Date: 2018
    Description: A flat Friedmann-Robertson-Walker (FRW) multiscalar field cosmology is studied with a particular potential of the form , which emerges as a relation between the time derivatives of the scalars field momenta. Classically, by employing the Hamiltonian formalism of two scalar fields with standard kinetic energy, exact solutions are found for the Einstein-Klein-Gordon (EKG) system for different scenarios specified by the parameter , as well as the e-folding function which is also computed. For the quantum scheme of this model, the corresponding Wheeler-DeWitt (WDW) equation is solved by applying an appropriate change of variables.
    Print ISSN: 1687-9120
    Electronic ISSN: 1687-9139
    Topics: Mathematics , Physics
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    Automatic Modulation Classification Exploiting Hybrid Machine Learning Network (2018)
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    Publication Date: 2018
    Description: It is a research hot spot in cognitive electronic warfare systems to classify the electromagnetic signals of a radar or communication system according to their modulation characteristics. We construct a multilayer hybrid machine learning network for the classification of seven types of signals in different modulation. We extract the signal modulation features exploiting a set of algorithms such as time-frequency analysis, discrete Fourier transform, and instantaneous autocorrelation and accomplish automatic modulation classification using naive Bayesian and support vector machine in a hybrid manner. The parameters in the network for classification are determined automatically in the training process. The numerical simulation results indicate that the proposed network accomplishes the classification accurately.
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    A Novel Multi-Input AlexNet Prediction Model for Oil and Gas Production (2018)
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    Publication Date: 2018
    Description: In the process of oilfield development, it is important to predict the oil and gas production. The predicted value of oil production is the amount of oil that may be obtained within a certain area over a certain period. Because of the current demand for oil and gas production prediction, a prediction model using a multi-input convolutional neural network based on AlexNet is proposed in this paper. The model predicts real oilfield data and achieves good results: increasing prediction accuracy by 17.5%, 20.8%, 11.6%, 8.9%, 6.9%, and 14.9% with respect to the backpropagation neural network, support vector machine, artificial neural network, radial basis function neural network, K-nearest neighbor, and decision tree methods, respectively. It addresses the uncertainty of oil and gas production caused by the change in parameter values during the process of petroleum exploitation and has far-reaching application significance.
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    Data Augmentation-Assisted Makeup-Invariant Face Recognition (2018)
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    Publication Date: 2018
    Description: Recently, face datasets containing celebrities photos with facial makeup are growing at exponential rates, making their recognition very challenging. Existing face recognition methods rely on feature extraction and reference reranking to improve the performance. However face images with facial makeup carry inherent ambiguity due to artificial colors, shading, contouring, and varying skin tones, making recognition task more difficult. The problem becomes more confound as the makeup alters the bilateral size and symmetry of the certain face components such as eyes and lips affecting the distinctiveness of faces. The ambiguity becomes even worse when different days bring different facial makeup for celebrities owing to the context of interpersonal situations and current societal makeup trends. To cope with these artificial effects, we propose to use a deep convolutional neural network (dCNN) using augmented face dataset to extract discriminative features from face images containing synthetic makeup variations. The augmented dataset containing original face images and those with synthetic make up variations allows dCNN to learn face features in a variety of facial makeup. We also evaluate the role of partial and full makeup in face images to improve the recognition performance. The experimental results on two challenging face datasets show that the proposed approach can compete with the state of the art.
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    A MEMS-IMU Assisted BDS Triple-Frequency Ambiguity Resolution Method in Complex Environments (2018)
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    Publication Date: 2018
    Description: Emerging technologies such as smart cities and unmanned vehicles all need Global Navigation Satellite Systems (GNSS) to provide high-precision positioning and navigation services. Fast and reliable carrier phase ambiguity resolution (AR) is a prerequisite for high-precision positioning. The poor satellite geometry and severe multipath effect caused by Beidou Navigation Satellite System (BDS) signal occlusion and reflection in complex environments will degrade the AR performance. In this contribution, a fast triple-frequency AR method combining Microelectromechanical System-Inertial Measurement Unit (MEMS-IMU) and BDS is proposed. First, the Extra-Wide Lane (EWL) ambiguity is fixed with the positioning parameters of MEMS-IMU instead of the pseudorange. Then, the phase noise variance of Narrow Lane (NL) observation is obtained from ambiguity-fixed EWL observation to reduce the total noise level of NL observation, and the NL ambiguity can be reliably fixed, and the BDS positioning result is obtained. Finally, the BDS positioning result is used as the posterior measurement of the extended Kalman filter to update the MEMS-IMU positioning parameters to form the coupling loop of MEMS-IMU and BDS. The data of urban road vehicle experiments were collected to verify the feasibility and effectiveness of the proposed algorithm. Results show that MEMS-IMU can speed up AR, and reduction of total noise level can significantly improve the reliability of AR.
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    Weak Target Detection Method of Passive Bistatic Radar Based on Probability Histogram (2018)
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    Publication Date: 2018
    Description: Passive bistatic radar (PBR) has attracted widespread attention for its capabilities in dealing with the threat of electronic countermeasure, stealth technology, and antiradiation missile. However, passive detection methods are limited by unknown characteristics of the uncooperative illuminators, and conventional radar signal processing algorithms cannot be conducted accurately, especially when the carrier frequency of the transmitting signal is agile and the signal-to-noise ratio (SNR) in the scattered wave of target is low. To address the above problems, this paper presents a novel weak target detection method based on probability histogram, which is then tested by a field experiment. Preliminary results indicate the feasibility of the proposed method in weak target detection.
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    Steady-State Performance Analysis of Tracking Filter Using LFM Waveforms and Range-Rate Measurement (2018)
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    Publication Date: 2018
    Description: The steady-state performance of a moving-object tracking filter is theoretically analyzed, assuming the simultaneous measurement of the range and range-rate (RRM system), and the use of linear frequency modulated (LFM) waveforms (RRM-LFM filter). An efficient analytical steady-state performance index, called an RMS index, is derived for the RRM-LFM filter to clarify the steady-state range prediction errors, theoretically. Using the derived RMS index, the optimal performance of the RRM-LFM filter is analyzed. The performance variation due to the use of LFM waveforms is clarified for the RRM tracking system. The theoretical performance analysis verifies that the measured range-rate significantly improves the tracking accuracy, compared to the conventional range-only measuring LFM tracking filter. Furthermore, the quantitative relationships among the measurement accuracy, degree of target maneuvering, and steady-state range prediction errors are clarified to validate the effectiveness of the RRM-LFM filter.
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    Valuation of the Vulnerable Option Price Based on Mixed Fractional Brownian Motion (2018)
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    Publication Date: 2018
    Description: The pricing problem of a kind of European vulnerable option was studied. The mixed fractional Brownian motion and the jump process were used to characterize the evolution of stock prices. The closed-form solution to European option pricing was obtained by applying martingale measure transformation method. At the end of this paper, some numerical experiments were adopted to compare the new pricing formula introduced in this paper with the classical Black-Scholes pricing formula. The result showed that the new pricing formula conformed to the actual financial market. In fact, the option value is positively correlated with the underlying asset price and the company’s asset price and the jump process has significant influence on the value of option.
    Print ISSN: 1026-0226
    Electronic ISSN: 1607-887X
    Topics: Mathematics
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    Study on Single Cycle Production Allocation and Supply Strategy for DCEs Based on the CVaR Criterion (2018)
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    Publication Date: 2018
    Description: Direct chain enterprises (DCEs) face a decision-making issue as to how to allocate and supply their products to their stores for sales with the minimum losses and maximum profits for the manufacturers. This paper presents a single-cycle optimal allocation model for DCEs under the given total production amount and conditional value at risk loss. The optimal strategy for production allocation and supply is derived. Subsequently, an approximate algorithm for solving the optimal total production amount is presented. The optimal allocation and supply strategy, the minimum total production amount, the minimum allocation strategy, and the discount pricing strategy are obtained for the single cycle. Finally, with the sales data of a food DCE, numerical results corroborate that adopting different production and supply strategies reduces the risk of expected losses and increases the expected return. It is of an important theoretical significance in guiding the production and operation of direct chain enterprises.
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    Egocentric Video Summarization Based on People Interaction Using Deep Learning (2018)
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    Publication Date: 2018
    Description: The availability of wearable cameras in the consumer market has motivated the users to record their daily life activities and post them on the social media. This exponential growth of egocentric videos demand to develop automated techniques to effectively summarizes the first-person video data. Egocentric videos are commonly used to record lifelogs these days due to the availability of low cost wearable cameras. However, egocentric videos are challenging to process due to the fact that placement of camera results in a video which presents great deal of variation in object appearance, illumination conditions, and movement. This paper presents an egocentric video summarization framework based on detecting important people in the video. The proposed method generates a compact summary of egocentric videos that contains information of the people whom the camera wearer interacts with. Our proposed approach focuses on identifying the interaction of camera wearer with important people. We have used AlexNet convolutional neural network to filter the key-frames (frames where camera wearer interacts closely with the people). We used five convolutional layers and two completely connected hidden layers and an output layer. Dropout regularization method is used to reduce the overfitting problem in completely connected layers. Performance of the proposed method is evaluated on UT Ego standard dataset. Experimental results signify the effectiveness of the proposed method in terms of summarizing the egocentric videos.
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    An RSSD-Based Fingerprint Positioning Method for Detection of an Unknown Radio Transmitter Using WLS and Factor Graph (2018)
    Hindawi
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    Publication Date: 2018
    Description: Realizing accurate detection of an unknown radio transmitter (URT) has become a challenge problem due to its unknown parameter information. A method based on received signal strength difference (RSSD) fingerprint positioning technique and using factor graph (FG) has been successfully developed to achieve the localization of an URT. However, the RSSD-based FG model is not accurate enough to express the relationship between the RSSD and the corresponding location coordinates since the RSSD variances of reference points are different in practice. This paper proposes an enhanced RSSD-based FG algorithm using weighted least square (WLS) to effectively reduce the impact of RSSD measurement variance difference on positioning accuracy. By the use of stochastic RSSD errors between the measured value and the estimated value of the selected reference points, we utilize the error weight matrix to establish a new WLSFG model. Then, the positioning process of proposed RSSD-WLSFG algorithm is derived with the sum-product principle. In addition, the paper also explores the effects of different access point (AP) numbers and grid distances on positioning accuracy. The simulation experiment results show that the proposed algorithm can obtain the best positioning performance compared with the conventional RSSD-based K nearest neighbor (RSSD-KNN) and RSSD-FG algorithms in the case of different AP numbers and grid distances.
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    Deep Residual Bidir-LSTM for Human Activity Recognition Using Wearable Sensors (2018)
    Hindawi
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    Publication Date: 2018
    Description: Human activity recognition (HAR) has become a popular topic in research because of its wide application. With the development of deep learning, new ideas have appeared to address HAR problems. Here, a deep network architecture using residual bidirectional long short-term memory (LSTM) is proposed. The advantages of the new network include that a bidirectional connection can concatenate the positive time direction (forward state) and the negative time direction (backward state). Second, residual connections between stacked cells act as shortcut for gradients, effectively avoiding the gradient vanishing problem. Generally, the proposed network shows improvements on both the temporal (using bidirectional cells) and the spatial (residual connections stacked) dimensions, aiming to enhance the recognition rate. When testing with the Opportunity dataset and the public domain UCI dataset, the accuracy is significantly improved compared with previous results.
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    Modeling and Analysis of Effective Case Depth on Meshing Strength of Internal Gear Transmissions (2018)
    Hindawi
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    Publication Date: 2018
    Description: The effective case depth (ECD) plays an important role in the meshing strength of internal gear transmissions. Carburizing quenching heat treatment is commonly used to enhance gear strength and wear resistance. However, the different ECDs in internal and external gears caused by heat treatment significantly affect the meshing strength, causing vibration, reducing gear service life, and hastening malfunction in internal gear transmission. In this study, we conducted an investigation of different ECDs by the heat treatment of carburized gear pairs by numerical simulation with the finite element method (FEM) and experiment tests. We analyzed three different carburized layer models, with the ECD in the internal gear being greater than, less than, and equal to the ECD in the external gear. In addition, we investigated the ability to distinguish between hardness gradients in gear teeth by dividing the carburized depth into seven layers to improve modeling accuracy. Results revealed that the meshing strength of internal gear transmission could be significantly enhanced by adopting the model with the ECD in the internal gear being less than the ECD in the external gear, and moreover, the shear stress of carburized gears initially increased and then decreased along with depth direction, and the maximum value appeared in the middle of the lower surface.
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    The Robust Consensus of a Noisy Deffuant-Weisbuch Model (2018)
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    Publication Date: 2018
    Description: We construct a new opinion formation of the Deffuant-Weisbuch model with the interference of the outer noise, where there are finite agents and the evolution is discrete-time. The opinion interaction occurs by one randomly chosen pair at each time step. The difference to the original Deffuant-Weisbuch model is that communications of any selected pairs will be affected by noises. The aim of this paper is to study the robust consensus of this noisy Deffuant-Weisbuch model. We first define the noise strength as the maximum noise absolute value. We will then show that when the noise strength is less than a certain threshold, this noisy model will achieve robust consensus when is sufficiently large; next we prove that the noisy model achieves robust consensus with a positive probability; finally, we demonstrate these results and provide numerical relations among the noise strength and some model parameters.
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    Hierarchical Production Planning and Real-Time Control for Parallel Batch Machines in a Flow Shop with Incompatible Jobs (2018)
    Hindawi
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    Publication Date: 2018
    Description: Effective control of the heat-treatment operation is essential to reducing manufacturing cost in mould manufacturing. The heat-treatment shop floor is a flow shop with parallel batch processors and incompatible jobs. The jobs differ from each other in product types, sizes, release times, and due-dates. The scheduling objective is to minimize manufacturing cost, including energy cost, subcontracting cost, and jobs’ tardiness penalties cost. A hierarchical production planning structure is proposed, which contains three decision-making levels: (1) balancing capacity and demand, (2) machining at the quenching stage, and (3) machining at the tempering stage. At the first level, the periodic rolling scheduling heuristic is proposed for the purpose of balancing the capacity and the demand in the coming period in the heat-treatment shop floor. At the second and third levels, two new look-ahead batching heuristics are proposed. An extensive computational experiment is conducted to verify the effectiveness of the proposed heuristics.
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    Numerical Solution of a Class of Nonlinear Partial Differential Equations by Using Barycentric Interpolation Collocation Method (2018)
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    Publication Date: 2018
    Description: Partial differential equations (PDEs) are widely used in mechanics, control processes, ecological and economic systems, chemical cycling systems, and epidemiology. Although there are some numerical methods for solving PDEs, simple and efficient methods have always been the direction that scholars strive to pursue. Based on this problem, we give the meshless barycentric interpolation collocation method (MBICM) for solving a class of PDEs. Four numerical experiments are carried out and compared with other methods; the accuracy of the numerical solution obtained by the present method is obviously improved.
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    Advanced Observer-Based Control for Benchmark Control Problems: From Mathematical Modeling to Control Design (2018)
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    Publication Date: 2018
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    Pseudosatellite Dynamic Positioning of UAV Pod Based on an Improved SR-UKF Algorithm (2018)
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    Publication Date: 2018
    Description: In view of the practical engineering problem of dynamic positioning of rotor UAV pod and the strong nonlinear problem in dynamic operation of UAV, a real-time estimation of the dynamic position of the rotor UAV pod is proposed by using the SR-UKF algorithm. This algorithm uses the nonlinear propagation of UT transform to generate the point set to maintain the mean and covariance information and thus achieves higher precision. Moreover, it uses the square root of covariance instead of covariance to participate in the recursive operation, thus improving the numerical stability of the filter and reducing the amount of computation. In this work, a pseudosatellite positioning platform was constructed in a field site in Nanjing. Based on evaluation of the space geometry of pseudosatellite base station, the accuracy of several nonlinear filtering algorithms was analyzed and evaluated using GPS RTK positioning results. It was found that the SR-UKF algorithm was the most accurate and efficient algorithm. It can meet the requirements of dynamic positioning of the rotor-wing UAV pod. The experiment results of this algorithm provide a more efficient positioning algorithm and implementation means for the actual engineering of UAV pod positioning using pseudosatellite system, which has high application value.
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    Sliding Mode Control with Adaptive Fuzzy Compensation for Uncertain Nonlinear System (2018)
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    Publication Date: 2018
    Description: Fuzzy sliding mode control as a robust and intelligent nonlinear control technique is proposed to control processes with severe nonlinearity and unknown models. This paper proposes a new adaptive tracking fuzzy sliding mode controller for nonlinear systems in the presence of fuzzy compensation. The main contribution of the proposed method is that the fuzzy system is used to realize the adaptive approximation of the unknown part of the model, and the fuzzy gain can be reduced effectively. The fuzzy self-adaptive rate is derived through the Lyapunov method, and the stability and convergence of the whole closed-loop system are guaranteed by adjusting the adaptive weight value. The performance of the proposed approach is evaluated for double joint rigid manipulator problems. The simulation results illustrate the effectiveness of our proposed controller.
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    Joint Transportation and Inventory Strategy for Perishable Items with Weibull Distribution under Carbon Emission Regulations (2018)
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    Publication Date: 2018
    Description: This paper studies the optimal transportation and inventory strategy for perishable items under carbon cap-and-trade and carbon tax regulations. Nonlinear optimization models are constructed to maximize the total profits per unit time when the deterioration rate satisfies a two-parameter Weibull distribution and the demand rate is a linear function with respect to the current inventory level. The existence conditions of the optimal replenishment cycles under two carbon emission policies are proved. The characteristics of the optimal replenishment cycles, maximal total profits, and carbon emissions per unit time under two carbon emission policies are compared. Finally, a numerical test is provided to illustrate the theoretical results and Taguchi method is employed to analyze the sensitivity of total profits and carbon emissions per unit time with respect to the parameters of carbon emission policies, transportation time, and Weibull parameters. The results show that parameters of carbon emission regulations have greater effect on total profits per unit time, and the transportation time has the greatest effect on carbon emissions per unit time.
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    From Antenna Design to High Fidelity, Full Physics Automotive Radar Sensor Corner Case Simulation (2018)
    Hindawi
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    Publication Date: 2018
    Description: Advanced driver assistance systems (ADAS) have recently been thrust into the spotlight in the automotive industry as carmakers and technology companies pursue effective active safety systems and fully autonomous vehicles. Various sensors such as lidar (light detection and ranging), radar (radio detection and ranging), ultrasonic, and optical cameras are employed to provide situational awareness to vehicles in a highly dynamic environment. Radar has emerged as a primary sensor technology for both active/passive safety and comfort-advanced driver-assistance systems. Physically building and testing radar systems to demonstrate reliability is an expensive and time-consuming process. Simulation emerges as the most practical solution to designing and testing radar systems. This paper provides a complete, full physics simulation workflow for automotive radar using finite element method and asymptotic ray tracing electromagnetic solvers. The design and optimization of both transmitter and receiver antennas is presented. Antenna interaction with vehicle bumper and fascia is also investigated. A full physics-based radar scene corner case is modelled to obtain high-fidelity range-Doppler maps. Finally, this paper investigates the effects of inclined roads on late pedestrian detection and the effects of construction metal plate radar returns on false target identification. Possible solutions are suggested and validated. Results from this study show how pedestrian radar returns can be increased by over 16 dB for early detection along with a 27 dB reduction in road construction plate radar returns to suppress false target identification. Both solutions to the above corner cases can potentially save pedestrian lives and prevent future accidents.
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    Corrigendum to “Quantitative Entropy Weight TOPSIS Evaluation of Sustainable Chinese Wind Power Developments” (2018)
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    Publication Date: 2018
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    A Max-Plus Algebra Approach to Study Time Disturbance Propagation within a Robustness Improvement Context (2018)
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    Publication Date: 2018
    Description: Industry 4.0 aims to ensure the future competitiveness of the manufacturing industry, where one of the major challenges faced by its implementation is the manufacturing/production system robustness (that is, able to perform in the presence of noise), as they may not be able to absorb input disruptions without bending or breaking. In this paper we propose to use the Max-Plus algebra approach to study the propagation of manufacturing disturbances (i.e., processing time variations), presenting a case study and performing a sensitivity analysis, with the idea of understanding under which conditions disturbance propagation takes place. Findings show that the impact propagation depends on where the variation source is located within the manufacturing system. Two are the main original contributions of this paper: the use of Max-Plus algebra to study the impact propagation of processing time variations and a four-step methodology to derive the equations representing the deterministic manufacturing system.
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    Analytical Synthesis of Regulators for Nonlinear Systems with a Terminal State Method on Examples of Motion Control of a Wheeled Robot and a Vessel (2018)
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    Publication Date: 2018
    Description: The paper is devoted to several examples of control algorithm development for two-wheeled double-track robot and low-tonnage vessel-catamaran with two Azipods that show practical aspects of the application of one nonlinear system control method — terminal state method. This method, developed by the authors of the present paper, belongs to the class of methods for inverse dynamics problem solving. Mathematical models of control objects in the form of normal systems of third-order nonlinear differential equations for the wheeled robot and seventh-order ones for the vessel are presented. Design formulas of the method in general form for terminal and stabilizing controls are shown. A routine of obtaining calculation expressions for control actions is shown. Results of computer simulation of bringing the robot to a given point in a given time, as well as bringing the vessel to a given course during a “strong” maneuver, are described.
    Print ISSN: 1110-757X
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    A Simple Alternating Direction Method for the Conic Trust Region Subproblem (2018)
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    Publication Date: 2018
    Description: A simple alternating direction method is used to solve the conic trust region subproblem of unconstrained optimization. By use of the new method, the subproblem is solved by two steps in a descent direction and its orthogonal direction, the original conic trust domain subproblem into a one-dimensional subproblem and a low-dimensional quadratic model subproblem, both of which are very easy to solve. Then the global convergence of the method under some reasonable conditions is established. Numerical experiment shows that the new method seems simple and effective.
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    Intelligent Prediction of Transmission Line Project Cost Based on Least Squares Support Vector Machine Optimized by Particle Swarm Optimization (2018)
    Hindawi
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    Publication Date: 2018
    Description: In order to meet the demand of power supply, the construction of transmission line projects is constantly advancing, and the level of cost control is constantly improving, which puts forward higher requirements for the accuracy of cost prediction. This paper proposes an intelligent cost prediction model based on least squares support vector machine (LSSVM) optimized by particle swarm optimization (PSO). Originally extracting natural, technological, and economic indexes from the perspective of cost composition, principal component analysis (PCA) is used to reduce the dimension of indexes. And PSO is innovatively introduced to optimize the parameters of LSSVM model to obtain the optimal parameters. The obtained principal component data are imported into empirical parameter LSSVM prediction model and the optimized parameter PSO-LSSVM prediction model, respectively, for modeling and prediction, and then comparing the prediction results to analyze the effect of model optimization. The results show that the absolute deviation of the optimized parameter prediction model is less than 9%. And the prediction accuracy of the optimized parameter prediction model is better than that of the empirical parameter model, which can provide a reliable basis for investment decision-making of transmission line projects.
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    CciMST: A Clustering Algorithm Based on Minimum Spanning Tree and Cluster Centers (2018)
    Hindawi
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    Publication Date: 2018
    Description: The minimum spanning tree- (MST-) based clustering method can identify clusters of arbitrary shape by removing inconsistent edges. The definition of the inconsistent edges is a major issue that has to be addressed in all MST-based clustering algorithms. In this paper, we propose a novel MST-based clustering algorithm through the cluster center initialization algorithm, called cciMST. First, in order to capture the intrinsic structure of the data sets, we propose the cluster center initialization algorithm based on geodesic distance and dual densities of the points. Second, we propose and demonstrate that the inconsistent edge is located on the shortest path between the cluster centers, so we can find the inconsistent edge with the length of the edges as well as the densities of their endpoints on the shortest path. Correspondingly, we obtain two groups of clustering results. Third, we propose a novel intercluster separation by computing the distance between the points at the intersection of clusters. Furthermore, we propose a new internal clustering validation measure to select the best clustering result. The experimental results on the synthetic data sets, real data sets, and image data sets demonstrate the good performance of the proposed MST-based method.
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    New Extension of Beta Function and Its Applications (2018)
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    Publication Date: 2018
    Description: In the present paper, new type of extension of classical beta function is introduced and its convergence is proved. Further it is used to introduce the extension of Gauss hypergeometric function and confluent hypergeometric functions. Then we study their properties, integral representation, certain fractional derivatives, and fractional integral formulas and application of these functions.
    Print ISSN: 0161-1712
    Electronic ISSN: 1687-0425
    Topics: Mathematics
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    A Modified Artificial Bee Colony Algorithm with Firefly Algorithm Strategy for Continuous Optimization Problems (2018)
    Hindawi
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    Publication Date: 2018
    Description: Artificial Bee Colony (ABC) algorithm is one of the efficient nature-inspired optimization algorithms for solving continuous problems. It has no sensitive control parameters and has been shown to be competitive with other well-known algorithms. However, the slow convergence, premature convergence, and being trapped within the local solutions may occur during the search. In this paper, we propose a new Modified Artificial Bee Colony (MABC) algorithm to overcome these problems. All phases of ABC are determined for improving the exploration and exploitation processes. We use a new search equation in employed bee phase, increase the probabilities for onlooker bees to find better positions, and replace some worst positions by the new ones in onlooker bee phase. Moreover, we use the Firefly algorithm strategy to generate a new position replacing an unupdated position in scout bee phase. Its performance is tested on selected benchmark functions. Experimental results show that MABC is more effective than ABC and some other modifications of ABC.
    Print ISSN: 1110-757X
    Electronic ISSN: 1687-0042
    Topics: Mathematics
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    The Entropy of Weighted Graphs with Atomic Bond Connectivity Edge Weights (2018)
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    Publication Date: 2018
    Description: The aim of this report to solve the open problem suggested by Chen et al. We study the graph entropy with ABC edge weights and present bounds of it for connected graphs, regular graphs, complete bipartite graphs, chemical graphs, tree, unicyclic graphs, and star graphs. Moreover, we compute the graph entropy for some families of dendrimers.
    Print ISSN: 1026-0226
    Electronic ISSN: 1607-887X
    Topics: Mathematics
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    An Improved Kernelized Correlation Filter Based Visual Tracking Method (2018)
    Hindawi
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    Publication Date: 2018
    Description: Correlation filter based trackers have received great attention in the field of visual target tracking, which have shown impressive advantages in terms of accuracy, robustness, and speed. However, there are still some challenges that exist in the correlation filter based methods, such as target scale variation and occlusion. To deal with these problems, an improved kernelized correlation filter (KCF) tracker is proposed, by employing the GM(1,1) grey model, the interval template matching method, and multiblock scheme. In addition, a strict template update strategy is presented in the proposed method to accommodate the appearance change and avoid template corruption. Finally, some experiments are conducted. The proposed method is compared with the top state-of-the-art trackers, and all the tracking algorithms are evaluated on the object tracking benchmark. The experimental results demonstrate obvious improvements of the proposed KCF-based visual tracking method.
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    Optimizational Mathematical Modeling Methods of DC Traction Power Supply System for Urban Mass Transit (2018)
    Hindawi
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    Publication Date: 2018
    Description: Time-varying characteristics of DC traction power supply system network structure are the key technical problem in its mathematical modeling. Based on node admittance network equation theory, this paper puts forward an optimizational mathematical modeling method of DC traction power supply system for urban mass transit, and that is to conduct automatic sequencing firstly for all the nodes on both ends of traction substation and the train according to the given rules, then arrange the nodes according to the position coordinates and save them into the arrays, and finally generate the node admittance network equation of DC traction power supply system according to the self-adaptive real-time dynamics of node arrays and input parameter documents. Simulation study indicates the rationality and correctness of optimizational mathematical modeling method of DC traction power supply system for urban mass transit.
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    A Reliable Leakage Reduction Technique for Approximate Full Adder with Reduced Ground Bounce Noise (2018)
    Hindawi
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    Publication Date: 2018
    Description: In this paper, an effective and reliable sleep circuit is proposed, which not only reduces leakage power but also shows significant reduction in ground bounce noise (GBN) in approximate full adder (FA) circuits. Four 1-bit approximate FA circuits are modified using proposed sleep circuit which uses one NMOS and one PMOS transistor. The design metrics such as average power, delay, power delay product (PDP), leakage power, and GBN are compared with nine other 1-bit FA circuits reported till date. All the comparisons are done using post-layout netlist at 45nm technology. The modified designs achieve reduction in leakage power and GBN up to 60% and 80%, respectively, as compared to the best reported approximate FA circuits. The modified approximate FA also achieves 83% reduction in leakage power as compared to conventional FA. Finally, application level metrics such as peak signal to noise ratio (PSNR) are considered to measure the performance of all the proposed approximate FAs.
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    Match-Mode Autoregressive Method for Moving Source Depth Estimation in Shallow Water Waveguides (2018)
    Hindawi
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    Publication Date: 2018
    Description: Source depth estimation is always a problem in underwater acoustic area, because depth estimation is a nonlinear problem. Traditional depth estimation methods use a vertical line array, which has disadvantage of poor mobility due to the size of sensor array. In order to estimate source depth with a horizontal line array, we propose a matched-mode depth estimation method based on autoregressive (AR) wavenumber estimation for a moving source in shallow water waveguides. First, we estimate the mode wavenumbers using the improved AR modal wavenumber spectrum. Second, according to the mode wavenumber estimation, we estimate the mode amplitudes by the wavenumber spectrum, which is obtained by generalized Hankel transform. Finally, we estimate source depth estimation by the peak of source depth function wherein the data mode best matches the replica mode that is calculated using a propagation model. Compared with synthetic aperture beamforming, the proposed method exhibits a better performance in source depth estimation under low signal-to-noise ratio or the small range span. The robustness of the proposed method is illustrated by simulating the performance in mismatched environment.
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    Numerical Study on Diffusion of Chloride and Induced Rebar Corrosion by Two-Dimensional Multiscale Approach (2018)
    Hindawi
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    Publication Date: 2018
    Description: Modeling approach for mesoscopic model of concrete depicting mass transportation and physicochemical reaction is important since there is growing demand for accuracy and computational efficiency of numerical simulation. Mesoscopic numerical simulation considering binder, aggregate, and interfacial transition zone (ITZ) generally produces huge number of DOFs, which is inapplicable for full structure. In this paper, a two-dimensional multiscale approach describing three-phase structure of concrete was discussed numerically. An effective approach generating random aggregate in polygon based on checking centroid distance and intersection of line segment was introduced. Moreover, ITZ elements were built by parallel expanding the edge of aggregates on inner side. By combining mesoscopic model including full-graded aggregate and macroscopic model, cases related to diffusivity and width of ITZ, volume fraction, and grade of aggregate were studied regarding the consideration of multiscale compensation. Result clearly showed that larger analysis model in multiscale model expanded the diffusion space of chloride ion and decreased chloride content in front of rebar. Finally, this paper addressed some noteworthy conclusions about the chloride distribution and rebar corrosion regarding the configuration of rebar diameter, concrete cover, and exposure period.
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    Topics: Computer Science , Technology
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    Fixed-Location Pulse Linear Prediction Coding Vocoder Model for Low Bit Rate Speech Coding (2018)
    Hindawi
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    Publication Date: 2018
    Description: An arbitrary-location pulse determination algorithm based on multipulse linear prediction coding (MP-LPC) is presented. This algorithm can determine all the amplitudes of the pulses at a time according to given pulse locations without the use of analysis-by-synthesis. This ensures that the pulses are optimal in a least-square sense, providing the theoretical foundation to improve the quality of synthesized speech. A fixed-location pulse linear prediction coding (FLP-LPC) method is proposed based on the arbitrary-location pulse determination algorithm. Simulation of the algorithm in MATLAB showed the superior quality of the speech synthesized using pulses in different locations and processed using the arbitrary-location pulse determination algorithm. The algorithm improved speech quality without affecting coding time, which was approximately 1.5% of the coding time for MP-LPC. Pulse locations in FLP-LPC are fixed and do not need to be transmitted, with only LSF, gain, and 16 pulse amplitudes requiring coding and transmission. FLP-LPC allows the generation of synthesized speech similar to G.729 coded speech at a rate of 2.5 kbps.
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    Joint DOA and Polarization Estimation with Two Parallel Sparse Dipole Arrays (2018)
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    Publication Date: 2018
    Description: Electromagnetic vector sensors (EMVS) have attracted growing attention in recent years. However, the mutual coupling effects in practical EMVS arrays may seriously degrade the parameter estimation performance. In order to solve this problem, a novel array configuration consisting of two parallel sparse dipole arrays is proposed. Based on the spatially rotational invariance property between the two parallel arrays and the interdipole spacing inside each array, highly accurate but ambiguous direction-cosine estimates, coarse direction-of-arrival (DOA) estimates, and polarization parameter estimation can be obtained jointly. The coarse DOA estimates are then employed to disambiguate the phase ambiguities in the fine estimates. Compared with collocated EMVS, the proposed array overcomes the mutual coupling problem. Moreover, the DOA estimation accuracy is promoted due to the sparse array aperture extension. Simulation results demonstrate the effectiveness of the proposed algorithm.
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    Preliminary Assessment of Hydrogen Peroxide Gel as an Oxidizer in a Catalyst Ignited Hybrid Thruster (2018)
    Hindawi
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    Publication Date: 2018
    Description: In regard to propulsion system applications, the stability of liquid propellants in long-term storage is of increasing importance, and this had led to a greater interest in gelation technology. As part of a preliminary test to determine the feasibility of using a gel propellant in a rocket with a catalyst bed, a hybrid rocket with a catalyst reactor using a gel propellant as an oxidizer was tested for the first time in this study. Experiments were conducted with two different oxidizers: one with liquid phase hydrogen peroxide and the other with gel phase hydrogen peroxide, as well as high-density polyethylene as fuel for a 250 N class hybrid thruster performance test. The thruster was designed with the catalyst ignition system, and a catalyst was manufactured to be inserted into the catalyst reactor to facilitate oxidizer decomposition. While the test result with neat hydrogen peroxide indicated sufficient decomposition efficiency using a manganese dioxide/alumina catalyst and successful autoignition of the fuel via the decomposed product, gel hydrogen peroxide exhibited insufficient decomposition and there were difficulties in operating the thruster as a part of the catalyst was covered in the gelling agent. This preliminary study identifies the potential challenges of using a gel phase oxidizer in a catalyst ignited hybrid thruster and discusses the technical issues that should be addressed in regard to a gel propellant hybrid thruster design with a catalyst reactor.
    Print ISSN: 1687-5966
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    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
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    Simulation and Statistical Modeling of Acoustic Scattering of Bubble Wakes (2018)
    Hindawi
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    Publication Date: 2018
    Description: Ship wakes are large, exist for a long time, and are difficult to disguise or conceal. These characteristics can be used as an important basis for ship tracking and recognition. However, distinguishing between wakes, underwater targets, and sea surface is a difficult problem that currently limits acoustic wake homing technology. To solve this problem, in this study, from the viewpoint of feature recognition, the effects of bubble radius, air volume fraction, frequency, depth, and other parameters on the group bubble were first investigated. The volume scattering intensity of acoustic wakes at different frequencies and depths was also calculated and analyzed, and the results of our theoretical calculations were verified through an experiment using a multifrequency single wave sonar dock. Subsequently, through the single frequency and multibeam sonar sea trial test, a statistical model of target characteristics with a clear physical mechanism was developed. The developed model can be utilized for the guidance and recognition of acoustic wake targets. Thus, this study lays the foundation for the practical application of acoustic wake guidance.
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    A Displacement-Based Design Method for Seismic Retrofit of RC Buildings Using Dissipative Braces (2018)
    Hindawi
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    Publication Date: 2018
    Description: The paper proposes a displacement-based design method for seismic retrofit of RC buildings using hysteretic dissipative braces. At first, a fully multimodal procedure based on an adaptive version of the capacity spectrum method is applied to the 3D model of the damped braced structure. Then, the properties of an idealized bilinear model are defined using the seismic characteristics of the compound system thus accounting for the frame-damped brace interaction. Finally, an iterative procedure is developed to provide an optimal distribution of dampers. The proposed method overcomes the limitations of the design procedures in the literature that generally neglect the frame-damped braces interactions. Moreover, it addresses the main issues of seismic design of damped braces: effect of force demands applied to the frame due to the damper yielding and strain hardening, higher modes contribution, effect of soft-storey irregularities, and torsion effect in asymmetric buildings. The proposed design procedure is first validated using nonlinear static and dynamic analyses of a numerical example. Then, it is implemented to a real case study of a RC school building to assess its applicability in current practice.
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    A Dual-Observer Design for Nonlinear Suspension System Based on Feedback Linearization (2018)
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    Publication Date: 2018
    Description: A novel approach to estimate suspension state information and payload condition was developed in this article. A nonlinear quarter car model with air spring and damper was built. After verification of system observability and solvability, a certain coordinate transform was built to transform the nonlinear system into a linear one. Then a Kalman filter observer was applied. A sprung mass observer, which works cooperatively with suspension state information observer, was also designed. Designed dual-observer was verified under typical road profile and sprung mass disturbance. Compared with extended Kalman filter, the dual-observer showed better accuracy and robustness.
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    Parametric Underwater Transmission Based on Pattern Time Delay Shift Coding System (2018)
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    Publication Date: 2018
    Description: The technique of pattern time delay shift coding (PDS) underwater acoustic (UWA) communication based on parametric array is presented in this paper, which is easy to be implemented and robust in the spatiotemporal variable ocean environment. The parametric array can generate low-frequency, broadband, and high-directivity beam with small-aperture. The high directivity reduces the impact of time variant characteristics of UWA channel especially multipath effects and improves the reuse rate of underwater acoustic channel at the same time. The wide bandwidth allows high rate communications. The sea trial results show that it can be employed to combat multipath propagation in shallow water and achieve very low bit error rate (BER). The theoretical research and sea trial verify the feasibility and effectiveness of the proposed UWA method.
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    Optimal Model for Complementary Operation of a Photovoltaic-Wind-Pumped Storage System (2018)
    Hindawi
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    Publication Date: 2018
    Description: An optimization model for the complementary operation of a photovoltaic-wind-pumped storage system is built to make full use of solar and wind energy. Apart from ensuring the maximum economic benefit which is normally used as the only objective, the stable objectives of minimizing the output fluctuation and variation of load and output difference are added to form the multiobjective problems because of lack of study on access capacity of photovoltaic and wind power. The model aims to increase the power benefit and reduce the output fluctuation and variation of load and output difference under the constraints of station, output balance, and transmission limitation. In a case study, four schemes including single-objective independent operation, single-objective complementary operation, and multiobjective complementary operation are compared to discuss the effect of pumped storage station on economic objective and stable objectives. Furthermore, the opposite trend of the two objectives is proved and a compromise optimal solution is given. The results indicate that the pumped storage station can effectively increase power benefit and access capacity of photovoltaic and wind power. The study can provide references to the complementary optimization of the pumped storage station and the intermittent renewable energy.
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    Rebate Decisions and Leadership Strategy in Competing Supply Chain with Heterogeneous Consumers (2018)
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    Publication Date: 2018
    Description: Rebate is a traditional type of promotion, and it can benefit manufacturers and retailers with expanded demands. However, the impact of leadership strategy in rebate competition on supply chain members and rebate decision is still somewhat unclear. Our paper focuses on a horizontal competition with respect to both rebate and leadership between two manufacturers selling substitutable products through a common retailer to consumers who are heterogeneous in their price sensitivity. Furthermore, we investigate the impacts of leadership strategy on profits and study rebate decision under different strategies. Our research indicates that Bertrand-Nash game benefits the retailer, but hurts manufacturers, while Stackelberg game benefits manufacturers but hurts the retailer, which shows no difference from previous studies. In addition, the sequential-move Stackelberg game could eliminate the classic prisoners’ dilemma in rebate decision, which is also influenced by fixed cost control.
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    Genetic-Based Optimization of the Manufacturing Process of a Robotic Arm under Fuzziness (2018)
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    Publication Date: 2018
    Description: Fuzziness is a key concern in modern industry and, thus, its implementation in manufacturing process modeling is of high practical importance for a wide industrial audience. The scientific contribution of the present attempt lies on the fact that the assembly line balancing problem of type 2 (SALBP-2) is approached for a real manufacturing process by introducing fuzzy processing times. The main scope of this work is the solution of the SALBP-2, which is an NP-hard problem, for a real manufacturing process considering fuzziness in the processing times. Since the data obtained from realistic situations are imprecise and uncertain, the consideration of fuzziness for the solution of SALBP-2 is of great interest. Thus, real data values for the processing times are gathered and estimated with uncertainty. Then, fuzzy processing times are used for finding the optimum cycle time. The optimization tool for the solution of the fuzzy SALBP-2 is a Genetic Algorithm (GA). The validity of the proposed approach is tested on the construction process of a metallic robotic arm. The experimental results demonstrate the effectiveness and efficiency of the proposed GA in determining the optimum sequence of the tasks assigned to workstations which provides the optimum fuzzy cycle time.
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    A Fast Object Tracker Based on Integrated Multiple Features and Dynamic Learning Rate (2018)
    Hindawi
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    Publication Date: 2018
    Description: Object tracking is a vital topic in computer vision. Although tracking algorithms have gained great development in recent years, its robustness and accuracy still need to be improved. In this paper, to overcome single feature with poor representation ability in a complex image sequence, we put forward a multifeature integration framework, including the gray features, Histogram of Gradient (HOG), color-naming (CN), and Illumination Invariant Features (IIF), which effectively improve the robustness of object tracking. In addition, we propose a model updating strategy and introduce a skewness to measure the confidence degree of tracking result. Unlike previous tracking algorithms, we judge the relationship of skewness values between two adjacent frames to decide the updating of target appearance model to use a dynamic learning rate. This way makes our tracker further improve the robustness of tracking and effectively prevents the target drifting caused by occlusion and deformation. Extensive experiments on large-scale benchmark containing 50 image sequences show that our tracker is better than most existing excellent trackers in tracking performance and can run at average speed over 43 fps.
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    Simple and Yet Efficient Estimators for Markovian Multiserver Queues (2018)
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    Publication Date: 2018
    Description: Estimators for the parameters of the Markovian multiserver queues are presented, from samples that are the number of clients in the system at arbitrary points and their sojourn times. As estimation in queues is a recognizably difficult inferential problem, this study focuses on the estimators for the arrival rate, the service rate, and the ratio of these two rates, which is known as the traffic intensity. Simulations are performed to verify the quality of the estimations for sample sizes up to 400. This research also relates notable new insights, for example, that the maximum likelihood estimator for the traffic intensity is equivalent to its moment estimator. Some limitations of the results are presented along with a detailed numerical example and topics for future developments in this research area.
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    Integrating Dynamic Pricing and Inventory Control for Fresh Agriproduct under Multinomial Logit Choice (2018)
    Hindawi
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    Publication Date: 2018
    Description: In this article, we investigate a joint pricing and inventory problem for a retailer selling fresh agriproducts (FAPs) with two-period shelf lifetime in a dynamic stochastic setting, where new and old FAPs are on sale simultaneously. At the beginning of each period the retailer makes ordering decision for new FAP and sets regular and discount price for new and old inventories, respectively. After demand realization, the expired leftover is disposed and unexpired inventory is carried to the next period, continuing selling. Unmet demand of all FAPs is backordered. The objective is to maximize the total expected discount profit over the whole planning horizon. We present a price-dependent, stochastic dynamic programming model taking into account zero lead time, linear ordering costs, inventory holding, and backlogging costs, as well as disposal cost. Considering the influence of the perishability, we integrate a Multinomial Logit (MNL) choice model to describe the consumer behavior on purchasing fresh or nonfresh product. By way of the inverse of the price vector, the original formulation can be transferred to be jointly concave and tractable. Finally we characterize the optimal policy and develop effective methods to solve the problem and conduct a simple numerical illustration.
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    A Point Cloud Registration Algorithm Based on Feature Extraction and Matching (2018)
    Hindawi
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    Publication Date: 2018
    Description: The existing registration algorithms suffer from low precision and slow speed when registering a large amount of point cloud data. In this paper, we propose a point cloud registration algorithm based on feature extraction and matching; the algorithm helps alleviate problems of precision and speed. In the rough registration stage, the algorithm extracts feature points based on the judgment of retention points and bumps, which improves the speed of feature point extraction. In the registration process, FPFH features and Hausdorff distance are used to search for corresponding point pairs, and the RANSAC algorithm is used to eliminate incorrect point pairs, thereby improving the accuracy of the corresponding relationship. In the precise registration phase, the algorithm uses an improved normal distribution transformation (INDT) algorithm. Experimental results show that given a large amount of point cloud data, this algorithm has advantages in both time and precision.
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    Two-Stage Assembly Scheduling with Batch Setup Times, Time-Dependent Deterioration, and Preventive Maintenance Activities Using Meta-Heuristic Algorithms (2018)
    Hindawi
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    Publication Date: 2018
    Description: This article considers a two-stage assembly scheduling problem (TSASP) with batch setup times, time-dependent deterioration, and preventive maintenance activities (PMAs). The objective of this problem is to simultaneously determine the optimal component-manufacturing sequence (CMS), product-assembly sequence (PAS), number of setups, and number and position of PMAs (PPMA). First, to determine the optimal solution, a novel mixed integer linear programming model (MILP) for the proposed problem is derived. Then, a standard genetic algorithm (SGA), hybrid genetic algorithm (HGA), standard harmony search (SHS), hybrid harmony search (HHS), and harmony-search-based evolutionary algorithm (HSEA) were proposed owing to the intractability of the optimal solution for large-scale problems. SGA and SHS provide a chromosome to represent a complete solution including three decisions (CMS, PAS, and PPMA). HGA, HHS, and HSEA provide a chromosome to represent a partial solution including PAS. CMS and PPMA are found by an effective local search heuristic based on the partial solution. A computational experiment is then conducted to evaluate the impacts of the factors on the performance of the proposed algorithms.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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    Adaptive Finite-Time Synchronization for Complex Dynamical Network with Different Dimensions of Nodes and Time-Varying Outer Coupling Structures (2018)
    Hindawi
    Details
    Publication Date: 2018
    Description: In this paper, we investigate finite-time synchronization problems of complex dynamical networks with different dimensions of nodes, which contain unknown periodically coupling structures and bounded time-varying delay. Based on finite-time stability theory, the inequality techniques, and the properties of Kronecker production of matrices, some useful finite-time synchronization criteria for complex dynamical network with unknown periodical couplings have been obtained. In addition, with proper adaptive periodical learning law designed, the unknown periodical couplings have been estimated successfully. Finally, some simulation examples are performed to verify the theoretical findings.
    Print ISSN: 1024-123X
    Electronic ISSN: 1563-5147
    Topics: Mathematics , Technology
    Published by Hindawi
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