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  • Articles  (32,782)
  • Hindawi  (23,210)
  • Institute of Electrical and Electronics Engineers (IEEE)
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  • Articles  (32,782)
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  • 1
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    Pareto-Ranking Based Quantum-Behaved Particle Swarm Optimization for Multiobjective Optimization (2015)
    Hindawi
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    Publication Date: 2015-08-11
    Description: A study on pareto-ranking based quantum-behaved particle swarm optimization (QPSO) for multiobjective optimization problems is presented in this paper. During the iteration, an external repository is maintained to remember the nondominated solutions, from which the global best position is chosen. The comparison between different elitist selection strategies (preference order, sigma value, and random selection) is performed on four benchmark functions and two metrics. The results demonstrate that QPSO with preference order has comparative performance with sigma value according to different number of objectives. Finally, QPSO with sigma value is applied to solve multiobjective flexible job-shop scheduling problems.
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  • 2
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    Pressure Prediction of Coal Slurry Transportation Pipeline Based on Particle Swarm Optimization Kernel Function Extreme Learning Machine (2015)
    Hindawi
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    Publication Date: 2015-08-11
    Description: For coal slurry pipeline blockage prediction problem, through the analysis of actual scene, it is determined that the pressure prediction from each measuring point is the premise of pipeline blockage prediction. Kernel function of support vector machine is introduced into extreme learning machine, the parameters are optimized by particle swarm algorithm, and blockage prediction method based on particle swarm optimization kernel function extreme learning machine (PSOKELM) is put forward. The actual test data from HuangLing coal gangue power plant are used for simulation experiments and compared with support vector machine prediction model optimized by particle swarm algorithm (PSOSVM) and kernel function extreme learning machine prediction model (KELM). The results prove that mean square error (MSE) for the prediction model based on PSOKELM is 0.0038 and the correlation coefficient is 0.9955, which is superior to prediction model based on PSOSVM in speed and accuracy and superior to KELM prediction model in accuracy.
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  • 3
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    Tyrosine Kinase Ligand-Receptor Pair Prediction by Using Support Vector Machine (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: Receptor tyrosine kinases are essential proteins involved in cellular differentiation and proliferation in vivo and are heavily involved in allergic diseases, diabetes, and onset/proliferation of cancerous cells. Identifying the interacting partner of this protein, a growth factor ligand, will provide a deeper understanding of cellular proliferation/differentiation and other cell processes. In this study, we developed a method for predicting tyrosine kinase ligand-receptor pairs from their amino acid sequences. We collected tyrosine kinase ligand-receptor pairs from the Database of Interacting Proteins (DIP) and UniProtKB, filtered them by removing sequence redundancy, and used them as a dataset for machine learning and assessment of predictive performance. Our prediction method is based on support vector machines (SVMs), and we evaluated several input features suitable for tyrosine kinase for machine learning and compared and analyzed the results. Using sequence pattern information and domain information extracted from sequences as input features, we obtained 0.996 of the area under the receiver operating characteristic curve. This accuracy is higher than that obtained from general protein-protein interaction pair predictions.
    Print ISSN: 1687-8027
    Electronic ISSN: 1687-8035
    Topics: Biology , Computer Science
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  • 4
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    Experimental and Theoretical Investigations on Frost Heave in Porous Media (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: For the construction in cold regions, frost heave and thaw settlement are the two factors which must be taken care of. Considered that a saturated soil column was subjected to an overburden pressure to model the ice lens growing process. A typical process, which coupled water, heat, and stress that happened in a saturated freezing soil column, was simulated by the finite element software. We did the numerical simulation under the same conditions as the experiment tests and then compared the results from temperature, frost heave, frozen structure, water content, and water intake. Result shows that the simulation results match well with the experimental results, and the correctness of the mathematical model is validated. On that basis, frost heave amount under different conditions by changing the temperature boundary and loading boundary is obtained. The frost heave has an optimum temperature gradient. Under the optimum value, the frost heave amount increases with increasing temperature gradient. Above the optimum value, frost heave decreases with increasing temperature gradient. Increasing the overburden pressure, frost heave amount always decreases. These results can provide references for the constrictions in cold regions.
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  • 5
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    An Unconditionally Stable Method for Solving the Acoustic Wave Equation (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: An unconditionally stable method for solving the time-domain acoustic wave equation using Associated Hermit orthogonal functions is proposed. The second-order time derivatives in acoustic wave equation are expanded by these orthogonal basis functions. By applying Galerkin temporal testing procedure, the time variable can be eliminated from the calculations. The restriction of Courant-Friedrichs-Levy (CFL) condition in selecting time step for analyzing thin layer can be avoided. Numerical results show the accuracy and the efficiency of the proposed method.
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  • 6
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    Complete Bilateral Teleoperation System for a Rotorcraft UAV with Time-Varying Delay (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: This paper proposes the use of simple proportional plus damping injection (P+d) controllers for delayed bilateral teleoperation of a rotorcraft UAV. The proposed control scheme involves P+d remote and local controllers, considers master and slave dynamics, and takes into account asymmetric time-varying delays. The stability of the proposed teleoperation system is analyzed using Lyapunov-Krasovskii functionals and delay-dependent stability criteria are obtained under linear-matrix-inequalities conditions. The performance of the teleoperation scheme is tested driving a virtual nonlinear 6DOF dynamic model of a minihelicopter in a human-in-the-loop simulation.
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  • 7
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    Application of the Periodic Average System Model in Dam Deformation Analysis (2015)
    Hindawi
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    Publication Date: 2015-08-12
    Description: Dams are among the most important hydraulic engineering facilities used for water supply, flood control, and hydroelectric power. Monitoring of dams is crucial since deformation might have occurred. How to obtain the deformation information and then judge the safe conditions is the key and difficult problem in dam deformation monitoring field. This paper proposes the periodic average system model and creates the concept of “settlement activity” based on the dam deformation issue. Long-term deformation monitoring data is carried out in a pumped-storage power station, this model combined with settlement activity is used to make the single point deformation analysis, and then the whole settlement activity profile is drawn by clustering analysis. Considering the cumulative settlement value of every point, the dam deformation trend is analyzed in an intuitive effect way. The analysis mode of combined single point with multipoints is realized. The results show that the key deformation information of the dam can be easily grasped by the application of the periodic average system model combined with the distribution diagram of settlement activity. And, above all, the ideas of this research provide an effective method for dam deformation analysis.
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  • 8
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    The Heat Transfer Coefficient of Recycled Concrete Bricks Combination with EPS Insulation Board Wall (2015)
    Hindawi
    Details
    Publication Date: 2015-08-12
    Description: Four tectonic forms samples were conducted to test their heat transfer coefficients. By analyzing and comparing the test values and theoretical values of the heat transfer coefficient, a corrected-value calculation method for determining the heat transfer coefficient was proposed; the proposed method was proved to be reasonably correct. The results indicated that the recycled concrete brick wall heat transfer coefficient is higher than that of the clay brick wall, the heat transfer coefficient of recycled concrete brick wall could be effectively reduced when combined with the EPS insulation board, and the sandwich insulation type was better than that of external thermal insulation type.
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  • 9
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    Four-Channel Teleoperation with Time-Varying Delays and Disturbance Observers (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: This paper addresses the robust stability of teleoperated systems under the four-channel architecture, affected by time-varying communication delays and using disturbance observers. It is based on our previous work which provides a framework for robust stability against delays with bounded variation and a bounded time-derivative, using structured singular values (SSV). The main new feature here is the inclusion of disturbance observers (DOBs). The DOB concept is well-documented and relevant to many applications, since only position (but not force) measurements are usually available. In this paper, we adapt two DOBs (master and slave) to our generic framework, by representing them as stable, fast filters affected by the uncertainty in the plant modelling. Our main result is an SSV test to verify robust stability. The simulation results confirm the usefulness of this approach.
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  • 10
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    Hom--Operators and Hom-Yang-Baxter Equations (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: In Hom-Lie set, we introduce the concept of Hom--operators and study its relation with classical Hom-Yang-Baxter equation, as well as left-symmetric Hom-algebras. We construct the corresponding relation between left-symmetric Hom-algebras and Hom-1-cocycles, which are both related to classical Hom-Yang-Baxter equation. Moreover, in Hom-algebra setting, we establish the equivalent relationship between AHYBE (associative Hom-Yang-Baxter equations) and -operators on Frobenius monoidal Hom-algebras.
    Print ISSN: 1687-9120
    Electronic ISSN: 1687-9139
    Topics: Mathematics , Physics
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  • 11
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    Heat and Mass Transfer for MHD Viscoelastic Fluid Flow over a Vertical Stretching Sheet with Considering Soret and Dufour Effects (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: The homotopy analysis method (HAM) with two auxiliary parameters is employed to examine heat and mass transfer in a steady two-dimensional magneto hydrodynamic viscoelastic fluid flow over a stretching vertical surface by considering Soret and Dufour effects. The two-dimensional boundary-layer governing partial differential equations are derived by considering the Boussinesq approximation. The highly nonlinear ordinary differential forms of momentum, energy, and concentration equations are obtained by similarity transformation. These equations are solved analytically in the presence of buoyancy force. The effects of different involved parameters such as magnetic field parameter, Prandtl number, buoyancy parameter, Soret number, Dufour number, and Lewis number on velocity, temperature, and concentration profiles are plotted and discussed. The effect of the second auxiliary parameter is also illustrated. Results show that the effect of increasing Soret number or decreasing Dufour number tends to decrease the velocity and temperature profiles (increase in Sr cools the fluid and reduces the temperature) while enhancing the concentration distribution.
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  • 12
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    Application of the Preview Control Method to the Optimal Tracking Control Problem for Continuous-Time Systems with Time-Delay (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: This paper considers the application of the preview control method to the optimal tracking control problem for a class of continuous-time systems with state and input delays. First, through a transformation, the system is transformed into a nondelayed one. Then, the tracking problem of the time-delay system is transformed into one of a nondelayed system via processing of the reference signal. We then apply preview control theory to derive an augmented system for the nondelayed system and design a controller with preview function assuming that the reference signal is previewable. Finally, we obtain the optimal control law of the augmented error system and thus obtain that of the original system by letting the preview length of the reference signal go to zero. Numerical simulations are provided to illustrate the effectiveness and validity of our conclusions.
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  • 13
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    Rotation and Magnetic Field Effect on Surface Waves Propagation in an Elastic Layer Lying over a Generalized Thermoelastic Diffusive Half-Space with Imperfect Boundary (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: The aim of the present investigation is to study the effects of magnetic field, relaxation times, and rotation on the propagation of surface waves with imperfect boundary. The propagation between an isotropic elastic layer of finite thickness and a homogenous isotropic thermodiffusive elastic half-space with rotation in the context of Green-Lindsay (GL) model is studied. The secular equation for surface waves in compact form is derived after developing the mathematical model. The phase velocity and attenuation coefficient are obtained for stiffness, and then deduced for normal stiffness, tangential stiffness and welded contact. The amplitudes of displacements, temperature, and concentration are computed analytically at the free plane boundary. Some special cases are illustrated and compared with previous results obtained by other authors. The effects of rotation, magnetic field, and relaxation times on the speed, attenuation coefficient, and the amplitudes of displacements, temperature, and concentration are displayed graphically.
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  • 14
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    Numerical Investigation of Non-Newtonian Flow and Heat Transfer Characteristics in Rectangular Tubes with Protrusions (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: Flow characteristics and heat transfer performances in rectangular tubes with protrusions are numerically investigated in this paper. The thermal heat transfer enhancement of composite structures and flow resistance reduction of non-Newtonian fluid are taken advantage of to obtain a better thermal performance. Protrusion channels coupled with different CMC concentration solutions are studied, and the results are compared with that of smooth channels with water flow. The comprehensive influence of turbulence effects, structural effects, and secondary flow effects on the CMC’s flow in protrusion tubes is extensively investigated. The results indicate that the variation of flow resistance parameters of shear-thinning power-law fluid often shows a nonmonotonic trend, which is different from that of water. It can be concluded that protrusion structure can effectively enhance the heat transfer of CMC solution with low pressure penalty in specific cases. Moreover, for a specific protrusion structure and a fixed flow velocity, there exists an optimal solution concentration showing the best thermal performance.
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  • 15
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    Research on Conflict Behavior of Top Management Team in Family Enterprises: A Complex Network Perspective (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: At present time, methods of research about top management team’s conflict become more and more prosperous with the help of complex system theory and evolutionary game. Taking family enterprise as an example, this paper makes an attempt on exploring complex network modeling to study data processing method and abstraction method of complex network of TMT conflict. And the paper will consider the attribute and relational mapping of top management team as nodes and edges in complex network to discuss the direct correspondence between complex network structure and management team characteristics. Besides that, according to the multiple attribute decision making, the method to dig into core members of the top management team will be created on the basis of the degree, closeness, cluster coefficient, and betweenness. And then the article will devote to studying the impact of attributes to the inner mechanism of TMT conflict and team cohesion through the network characteristic analysis.
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  • 16
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    Robust Observer-Based Feedback Control for Lipschitz Singularly Perturbed Systems (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: The observer-based feedback control for singularly perturbed systems (SPSs) with Lipschitz constraint is addressed. A sufficient condition, independent of the perturbation parameter, for a full-order observer is presented in terms of linear matrix inequality (LMI) such that observation error is exponentially stable for all sufficiently small perturbation parameters. Then, for observer-based feedback control, a proper controller is constructed to guarantee the input-to-state stability of the system with regard to the observation error. Considering the convergence of observation error, the stability of the system can be obtained based on the input-to-state stability property. It is shown that the proposed method is simple and easy to operate. Moreover, the upper bound of the small perturbation parameter for stability of systems can be explicitly estimated with a workable computation way. Finally, two numerical examples show the effectiveness of the proposed method.
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  • 17
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    Direction of Arrival Estimation Based on DDOA and Self-Organizing Map (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: An effective two-level self-organizing map (SOM) neural network for direction of arrival (DOA) of sound signals estimation is proposed. The approach is based on the distance difference of arrival (DDOA) and a uniform linear sensor array in a 2D plane; it performs a nonlinear mapping between the DDOA vectors and angles of arrival (AOA). We found that the topological order of DDOA vectors and AOAs of same signals is uniform; thus, the topological order preserving of SOM network makes it valid to estimate AOA through DDOA. From the results of simulations and lake experiments, it is shown that the network has the advantage of accuracy and robustness, can be trained in advance, and is easy to implement.
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  • 18
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    A Max-Term Counting Based Knowledge Inconsistency Checking Strategy and Inconsistency Measure Calculation of Fuzzy Knowledge Based Systems (2015)
    Hindawi
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    Publication Date: 2015-08-14
    Description: The task of finding all the minimal inconsistent subsets plays a vital role in many theoretical works especially in large knowledge bases and it has been proved to be a NP-complete problem. In this work, at first we propose a max-term counting based knowledge inconsistency checking strategy. And, then, we put forward an algorithm for finding all minimal inconsistent subsets, in which we establish a Boolean lattice to organize the subsets of the given knowledge base and use leaf pruning to optimize the algorithm efficiency. Comparative experiments and analysis also show the algorithm’s improvement over past approaches. Finally, we give an application for inconsistency measure calculation of fuzzy knowledge based systems.
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  • 19
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    On Galileo’s Tallest Column (2015)
    Hindawi
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    Publication Date: 2015-08-13
    Description: The height at which an unloaded column will fail under its own weight was calculated for first time by Galileo for cylindrical columns. Galileo questioned himself if there exists a shape function for the cross section of the column with which it can attain a greater height than the cylindrical column. The problem is not solved since then, although the definition of the so named “constant maximum strength” solids seems to give an affirmative answer to Galileo’s question, in the form of shapes which seem to attain infinite height, even when loaded with a useful load at the top. The main contribution of this work is to show that Galileo’s problem is (i) an important problem for structural design theory of buildings and other structures, (ii) not solved by the time being in any sense, and (iii) an interesting problem for mathematicians involved in related but very different problems (as Euler’s tallest column). A contemporary formulation of the problem is included as a result of a research on the subject.
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  • 20
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    Multivariate Network Exploration and Presentations (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-15
    Description: This installment of Computer's series highlighting the work published in IEEE Computer Society journals comes from IEEE Transactions on Visualization and Computer Graphics. The Web extra at http://youtu.be/E1PVTitj7h0 is a video demonstration of a novel solution to multivariate data visualization that helps users interactively explore data by combining standard presentations, from detailed views to high-level overviews.
    Print ISSN: 0018-9162
    Electronic ISSN: 1558-0814
    Topics: Computer Science
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  • 21
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    In-Memory Data Rearrangement for Irregular, Data-Intensive Computing (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-15
    Description: The data rearrangement engine (DRE) performs in-memory data restructuring to accelerate irregular, data-intensive applications. An emulation on a field-programmable gate array shows how the DRE could improve speedup, memory bandwidth, and energy consumption on three representative benchmarks.
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  • 22
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    Richard E. Merwin Scholarship House Advertisement (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-15
    Description: Advertisement, IEEE.
    Print ISSN: 0018-9162
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  • 23
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    Research on Solving Systems of Nonlinear Equations Based on Improved PSO (2015)
    Hindawi
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    Publication Date: 2015-08-17
    Description: Solving systems of nonlinear equations is perhaps one of the most difficult problems in all of numerical computations, especially in a diverse range of engineering applications. The convergence and performance characteristics can be highly sensitive to the initial guess of the solution for most numerical methods such as Newton’s method. However, it is very difficult to select reasonable initial guess of the solution for most systems of nonlinear equations. Besides, the computational efficiency is not high enough. Aiming at these problems, an improved particle swarm optimization algorithm (imPSO) is proposed, which can overcome the problem of selecting reasonable initial guess of the solution and improve the computational efficiency. The convergence and performance characteristics of this method are demonstrated through some standard systems. The results show that the improved PSO for solving systems of nonlinear equations has reliable convergence probability, high convergence rate, and solution precision and is a successful approach in solving systems of nonlinear equations.
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  • 24
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    Cross-Domain Matching with Squared-Loss Mutual Information (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-04
    Description: The goal of cross-domain matching (CDM) is to find correspondences between two sets of objects in different domains in an unsupervised way. CDM has various interesting applications, including photo album summarization where photos are automatically aligned into a designed frame expressed in the Cartesian coordinate system, and temporal alignment which aligns sequences such as videos that are potentially expressed using different features. In this paper, we propose an information-theoretic CDM framework based on squared-loss mutual information (SMI). The proposed approach can directly handle non-linearly related objects/sequences with different dimensions, with the ability that hyper-parameters can be objectively optimized by cross-validation. We apply the proposed method to several real-world problems including image matching, unpaired voice conversion, photo album summarization, cross-feature video and cross-domain video-to-mocap alignment, and Kinect -based action recognition, and experimentally demonstrate that the proposed method is a promising alternative to state-of-the-art CDM methods.
    Print ISSN: 0162-8828
    Electronic ISSN: 1939-3539
    Topics: Computer Science
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  • 25
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    Semi-Continuity of Skeletons in Two-Manifold and Discrete Voronoi Approximation (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-04
    Description: The skeleton of a 2D shape is an important geometric structure in pattern analysis and computer vision. In this paper we study the skeleton of a 2D shape in a two-manifold $mathcal {M}$ , based on a geodesic metric. We present a formal definition of the skeleton $S(Omega )$ for a shape $Omega$ in $mathcal {M}$ and show several properties that make $S(Omega )$ distinct from its Euclidean counterpart in $mathbb {R}^2$ . We further prove that for a shape sequence $lbrace Omega _irbrace$ that converge to a shape $Omega$ in $mathcal {M}$ , the mapping $Omega righta- row overline{S}(Omega )$ is lower semi-continuous. A direct application of this result is that we can use a set $P$ of sample points to approximate the boundary of a 2D shape $Omega$ in $mathcal {M}$ , and the Voronoi diagram of $P$ inside $Omega subset mathcal {M}$ gives a good approximation to the skeleton $S(Omega )$ . Examples of skeleton computation in topography and brain morphometry are illustrated.
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  • 26
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    Robust and Accurate Shape Model Matching Using Random Forest Regression-Voting (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-04
    Description: A widely used approach for locating points on deformable objects in images is to generate feature response images for each point, and then to fit a shape model to these response images. We demonstrate that Random Forest regression-voting can be used to generate high quality response images quickly. Rather than using a generative or a discriminative model to evaluate each pixel, a regressor is used to cast votes for the optimal position of each point. We show that this leads to fast and accurate shape model matching when applied in the Constrained Local Model framework. We evaluate the technique in detail, and compare it with a range of commonly used alternatives across application areas: the annotation of the joints of the hands in radiographs and the detection of feature points in facial images. We show that our approach outperforms alternative techniques, achieving what we believe to be the most accurate results yet published for hand joint annotation and state-of-the-art performance for facial feature point detection.
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  • 27
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    Recognising Planes in a Single Image (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2015-08-04
    Description: We present a novel method to recognise planar structures in a single image and estimate their 3D orientation. This is done by exploiting the relationship between image appearance and 3D structure, using machine learning methods with supervised training data. As such, the method does not require specific features or use geometric cues, such as vanishing points. We employ general feature representations based on spatiograms of gradients and colour, coupled with relevance vector machines for classification and regression. We first show that using hand-labelled training data, we are able to classify pre-segmented regions as being planar or not, and estimate their 3D orientation. We then incorporate the method into a segmentation algorithm to detect multiple planar structures from a previously unseen image.
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    IEEE Transactions on Pattern Analysis and Machine Intelligence Information for Authors (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-04
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    Sparse Multi-View Consistency for Object Segmentation (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-04
    Description: Multiple view segmentation consists in segmenting objects simultaneously in several views. A key issue in that respect and compared to monocular settings is to ensure propagation of segmentation information between views while minimizing complexity and computational cost. In this work, we first investigate the idea that examining measurements at the projections of a sparse set of 3D points is sufficient to achieve this goal. The proposed algorithm softly assigns each of these 3D samples to the scene background if it projects on the background region in at least one view, or to the foreground if it projects on foreground region in all views. Second, we show how other modalities such as depth may be seamlessly integrated in the model and benefit the segmentation. The paper exposes a detailed set of experiments used to validate the algorithm, showing results comparable with the state of art, with reduced computational complexity. We also discuss the use of different modalities for specific situations, such as dealing with a low number of viewpoints or a scene with color ambiguities between foreground and background.
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    Asymptotic Behavior of Weak Solutions to the Generalized Nonlinear Partial Differential Equation Model (2015)
    Hindawi
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    Publication Date: 2015-07-30
    Description: This paper investigates the asymptotic behavior of weak solutions to the generalized nonlinear partial differential equation model. It is proved that every perturbed weak solution of the perturbed generalized nonlinear partial differential equations asymptotically converges to the solution of the original system under the large perturbation.
    Print ISSN: 1024-123X
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    Normal Forms of Hopf Bifurcation for a Reaction-Diffusion System Subject to Neumann Boundary Condition (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: A reaction-diffusion system coupled by two equations subject to homogeneous Neumann boundary condition on one-dimensional spatial domain with is considered. According to the normal form method and the center manifold theorem for reaction-diffusion equations, the explicit formulas determining the properties of Hopf bifurcation of spatially homogeneous and nonhomogeneous periodic solutions of system near the constant steady state are obtained.
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    Determining Replenishment Lot Size and Shipment Policy for an EPQ Inventory Model with Delivery and Rework (2015)
    Hindawi
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    Publication Date: 2015-08-03
    Description: The determination of production-shipment policies for a vendor-buyer system is dealt within this paper. The main objective is to derive the optimal replenishment lot size and shipment policy for an EPQ inventory model with multiple deliveries and rework. This inventory model contains two decision variables: the replenishment lot size and the number of deliveries. Previous researches solve this inventory model considering both variables to be continuous. However, the number of deliveries must be considered as a discrete variable. In this direction, this paper solves the inventory model considering two cases: Case 1: the replenishment lot size as a continuous variable and the number of shipments as a discrete variable and Case 2: the replenishment lot size and the number of shipments as discrete variables. The final results are two simple and easy-to-apply solution procedures to find the optimal values for the replenishment lot size and the number of deliveries for each case.
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    A Study of SUOWA Operators in Two Dimensions (2015)
    Hindawi
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    Publication Date: 2015-08-03
    Description: SUOWA operators are a new class of aggregation functions that simultaneously generalize weighted means and OWA operators. They are Choquet integral-based operators with respect to normalized capacities; therefore, they possess some interesting properties such as continuity, monotonicity, idempotency, compensativeness, and homogeneity of degree 1. In this paper, we focus on two dimensions and show that any Choquet integral with respect to a normalized capacity can be expressed as a SUOWA operator.
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    A New Biobjective Model to Optimize Integrated Redundancy Allocation and Reliability-Centered Maintenance Problems in a System Using Metaheuristics (2015)
    Hindawi
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    Publication Date: 2015-08-03
    Description: A novel integrated model is proposed to optimize the redundancy allocation problem (RAP) and the reliability-centered maintenance (RCM) simultaneously. A system of both repairable and nonrepairable components has been considered. In this system, electronic components are nonrepairable while mechanical components are mostly repairable. For nonrepairable components, a redundancy allocation problem is dealt with to determine optimal redundancy strategy and number of redundant components to be implemented in each subsystem. In addition, a maintenance scheduling problem is considered for repairable components in order to identify the best maintenance policy and optimize system reliability. Both active and cold standby redundancy strategies have been taken into account for electronic components. Also, net present value of the secondary cost including operational and maintenance costs has been calculated. The problem is formulated as a biobjective mathematical programming model aiming to reach a tradeoff between system reliability and cost. Three metaheuristic algorithms are employed to solve the proposed model: Nondominated Sorting Genetic Algorithm (NSGA-II), Multiobjective Particle Swarm Optimization (MOPSO), and Multiobjective Firefly Algorithm (MOFA). Several test problems are solved using the mentioned algorithms to test efficiency and effectiveness of the solution approaches and obtained results are analyzed.
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    Deterministic and Probabilistic Investigation on Multiple Crack Interactions in a Semi-Infinite Domain (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: The investigation of multiple crack interactions in fracture mechanics is important to predict the safety and reliability of structures. This study aims to investigate the interactions of multiple parallel cracks in a semi-infinite domain in both deterministic and probabilistic ways by using an automated finite element modeling procedure and the Monte Carlo simulation. The stress intensity factor is considered as an indicator of failure and accurately evaluated by using the domain integral technique. The variation of the stress intensity factor according to the position, the length, and the number of cracks is demonstrated. In a probabilistic investigation, the effects of the number of cracks, the random distribution of the crack lengths, and the crack interactions to the failure probability are studied for a semi-infinite domain. The stress redistribution among multiple cracks, the effect of unevenly distributed crack lengths, and the combined effect of crack length uncertainties and a crack shielding effect have been examined.
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    Effects Comparison of Different Resilience Enhancing Strategies for Municipal Water Distribution Network: A Multidimensional Approach (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: Water distribution network (WDN) is critical to the city service, economic rehabilitation, public health, and safety. Reconstructing the WDN to improve its resilience in seismic disaster is an important and ongoing issue. Although a considerable body of research has examined the effects of different reconstruction strategies on seismic resistance, it is still hard for decision-makers to choose optimal resilience enhancing strategy. Taking the pipeline ductile retrofitting and network meshed expansion as demonstration, we proposed a feasible framework to contrast the resilience enhancing effects of two reconstruction strategies—units retrofitting strategy and network optimization strategy—in technical and organizational dimension. We also developed a new performance response function (PRF) which is based on network equilibrium theory to conduct the effects comparison in integrated technical and organizational dimension. Through the case study of municipal WDN in Lianyungang, China, the comparison results were thoroughly shown and the holistic decision-making support was provided.
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    Timetable Design for Urban Rail Line with Capacity Constraints (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: To design an efficient and economical timetable for a heavily congested urban rail corridor, a scheduling model is proposed in this paper. The objective of the proposed model is to find the departure time of trains at the start terminal to minimize the system cost, which includes passenger waiting cost and operating cost. To evaluate the performance of the timetable, a simulation model is developed to simulate the detailed movements of passengers and trains with strict constraints of station and train capacities. It assumes that passengers who arrive early will have more chances to access a station and board a train. The accessing and boarding processes of passengers are all based on a first-come-first-serve basis. When a station is full, passengers unable to access must wait outside until the number of waiting passengers at platform falls below a given value. When a train is full, passengers unable to board must wait at the platform for the next train to arrive. Then, based on the simulation results, a two-stage genetic algorithm is introduced to find the best timetable. Finally, a numerical example is given to demonstrate the effectiveness of the proposed model and solution method.
    Print ISSN: 1026-0226
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    Big Data-Driven Based Real-Time Traffic Flow State Identification and Prediction (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: With the rapid development of urban informatization, the era of big data is coming. To satisfy the demand of traffic congestion early warning, this paper studies the method of real-time traffic flow state identification and prediction based on big data-driven theory. Traffic big data holds several characteristics, such as temporal correlation, spatial correlation, historical correlation, and multistate. Traffic flow state quantification, the basis of traffic flow state identification, is achieved by a SAGA-FCM (simulated annealing genetic algorithm based fuzzy c-means) based traffic clustering model. Considering simple calculation and predictive accuracy, a bilevel optimization model for regional traffic flow correlation analysis is established to predict traffic flow parameters based on temporal-spatial-historical correlation. A two-stage model for correction coefficients optimization is put forward to simplify the bilevel optimization model. The first stage model is built to calculate the number of temporal-spatial-historical correlation variables. The second stage model is present to calculate basic model formulation of regional traffic flow correlation. A case study based on a real-world road network in Beijing, China, is implemented to test the efficiency and applicability of the proposed modeling and computing methods.
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    A Pest Management Model with Stage Structure and Impulsive State Feedback Control (2015)
    Hindawi
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    Publication Date: 2015-08-04
    Description: A pest management model with stage structure and impulsive state feedback control is investigated. We get the sufficient condition for the existence of the order-1 periodic solution by differential equation geometry theory and successor function. Further, we obtain a new judgement method for the stability of the order-1 periodic solution of the semicontinuous systems by referencing the stability analysis for limit cycles of continuous systems, which is different from the previous method of analog of Poincarè criterion. Finally, we analyze numerically the theoretical results obtained.
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    Multi-Orientation Scene Text Detection with Adaptive Clustering (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-04
    Description: Text detection in natural scene images is an important prerequisite for many content-based image analysis tasks, while most current research efforts only focus on horizontal or near horizontal scene text. In this paper, first we present a unified distance metric learning framework for adaptive hierarchical clustering, which can simultaneously learn similarity weights (to adaptively combine different feature similarities) and the clustering threshold (to automatically determine the number of clusters). Then, we propose an effective multi-orientation scene text detection system, which constructs text candidates by grouping characters based on this adaptive clustering. Our text candidates construction method consists of several sequential coarse-to-fine grouping steps: morphology-based grouping via single-link clustering, orientation-based grouping via divisive hierarchical clustering, and projection-based grouping also via divisive clustering. The effectiveness of our proposed system is evaluated on several public scene text databases, e.g., ICDAR Robust Reading Competition data sets (2011 and 2013), MSRA-TD500 and NEOCR. Specifically, on the multi-orientation text data set MSRA-TD500, the $f$ measure of our system is $71$ percent, much better than the state-of-the-art performance. We also construct and release a practical challenging multi-orientation scene text data set (USTB-SV1K), which is available at http://prir.ustb.edu.cn/TexStar/MOMV-text-detection/.
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    Using Metric Distance Ranking Method to Find Intuitionistic Fuzzy Critical Path (2015)
    Hindawi
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    Publication Date: 2015-08-06
    Description: Network analysis is a technique which determines the various sequences of activities concerning a project and the project completion time. The popular methods of this technique which is widely used are the critical path method and program evaluation and review techniques. The aim of this paper is to present an analytical method for measuring the criticality in an (Atanassov) intuitionistic fuzzy project network. Vague parameters in the project network are represented by (Atanassov) intuitionistic trapezoidal fuzzy numbers. A metric distance ranking method for (Atanassov) intuitionistic fuzzy numbers to a critical path method is proposed. (Atanassov) Intuitionistic fuzzy critical length of the project network is found without converting the (Atanassov) intuitionistic fuzzy activity times to classical numbers. The fuzzified conversion of the problem has been discussed with the numerical example. We also apply four different ranking procedures and we compare it with metric distance ranking method. Comparison reveals that the proposed ranking method is better than other raking procedures.
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    A Low-Cost Mechanism Exploiting Narrow-Width Values for Tolerating Hard Faults in ALU (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: Digital circuits are expected to increasingly suffer from more hard faults due to technology scaling. Especially, a single hard fault in ALU (Arithmetic Logic Unit) might lead to a total failure in processors or significantly reduce their performance. To address these increasingly important problems, we propose a novel cost-efficient fault-tolerant mechanism for the ALU, called LIZARD. LIZARD employs two half-word ALUs, instead of a single full-word ALU, to perform computations with concurrent fault detection. When a fault is detected, the two ALUs are partitioned into four quarter-word ALUs. After diagnosing and isolating a faulty quarter-word ALU, LIZARD continues its operation using the remaining ones, which can detect and isolate another fault. Even though LIZARD uses narrow ALUs for computations, it adds negligible performance overhead through exploiting predictability of the results in the arithmetic computations. We also present the architectural modifications when employing LIZARD for scalar as well as superscalar processors. Through comparative evaluation, we demonstrate that LIZARD outperforms other competitive fault-tolerant mechanisms in terms of area, energy consumption, performance and reliability.
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    Hybrid Search Scheme for Social Networks Supported by Dynamic Weighted Distributed Label Clustering (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: Information searches are the most common application within social networks. Normally, the social network is modeled as a network graph, consisting of nodes (In the rest of the paper, unless otherwise specified, we will use the terms “user” and “node” interchangeably.) representing users within the network and edges representing relationships between users. Choosing the appropriate nodes to form an auxiliary structure for supporting the effective query message spreading can reduce the troublesome repeated queries. To accomplish this, a hybrid search (HS) scheme is proposed. If the query message is received by a node belonging the auxiliary structure constructed by dynamic weighted distributed label clustering (DW-DLC), it would be flooded to all neighbors of the visited node; otherwise, it would be forwarded to one neighbor of the visited node. The DW-DLC based auxiliary structure can accelerate the process of obtaining required information within the network. The simulation results show that the HS+DW-DLC scheme can reduce the average searching delay time, even in a required-information-scarce social network. In addition, the proposed scheme can generate a relatively low amount of repeated messages to lower repeatedly asking social network users.
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    Radix-2 Division Algorithms with an Over-Redundant Digit Set (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: This paper presents a derivation of four radix-2 division algorithms by digit recurrence. Each division algorithm selects a quotient digit from the over-redundant digit set {−2, −1, 0, 1, 2}, and the selection of each quotient digit depends only on the two most-significant digits of the partial remainder in a redundant representation. Two algorithms use a two’s complement representation for the partial remainder and carry-save additions, and the other two algorithms use a binary signed-digit representation for the partial remainder and carry-free additions. Three algorithms are novel. The fourth algorithm has been presented before. Results from the synthesized netlists show that two of our fastest algorithms achieve an improvement of 10 percent in latency per iteration over a standard radix-2 SRT algorithm at the cost of 36 percent more power and 50 percent more area.
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    WaFS: A Workflow-Aware File System for Effective Storage Utilization in the Cloud (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: We present WaFS, a user-level file system, and a related scheduling algorithm for scientific workflow computation in the cloud. WaFS’s primary design goal is to automatically detect and gather the explicit and implicit data dependencies between workflow jobs, rather than high-performance file access. Using WaFS’s data, a workflow scheduler can either make effective cost-performance tradeoffs or improve storage utilization. Proper resource provisioning and storage utilization on pay-as-you-go clouds can be more cost effective than the uses of resources in traditional HPC systems. WaFS and the scheduler controls the number of concurrent workflow instances at runtime so that the storage is well used, while the total makespan (i.e., turnaround time for a workload) is not severely compromised. We describe the design and implementation of WaFS and the new workflow scheduling algorithm based on our previous work. We present empirical evidence of the acceptable overheads of our prototype WaFS and describe a simulation-based study, using representative workflows, to show the makespan benefits of our WaFS-enabled scheduling algorithm.
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    Maximizing a Record’s Standing in a Relation (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: Given a database table with records that can be ranked, an interesting problem is to identify selection conditions for the table, which are qualified by an input record and render its ranking as high as possible among the qualifying tuples. In this paper, we study this standing maximization problem, which finds application in object promotion and characterization. After showing the hardness of the problem, we propose greedy methods, which are experimentally shown to achieve high accuracy compared to exhaustive enumeration, while scaling very well to the problem input size. Our contributions include a linear-time algorithm for determining the optimal selection range for an ordinal attribute and techniques for choosing and prioritizing the most promising selection predicates to apply. Experiments on real datasets confirm the effectiveness and efficiency of our techniques.
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    XACML Policy Evaluation with Dynamic Context Handling (2015)
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    Publication Date: 2015-08-07
    Description: Some fairly recent research has focused on providing XACML-based solutions for dynamic privacy policy management. In this regard, a number of works have provided enhancements to the performance of XACML policy enforcement point (PEP) component, but very few have focused on enhancing the accuracy of that component. This paper improves the accuracy of an XACML PEP by filling some gaps in the existing works. In particular, dynamically incorporating user access context into the privacy policy decision, and its enforcement. We provide an XACML-based implementation of a dynamic privacy policy management framework and an evaluation of the applicability of our system in comparison to some of the existing approaches.
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    Pattern-Aided Regression Modeling and Prediction Model Analysis (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: This paper first introduces pattern aided regression (PXR) models, a new type of regression models designed to represent accurate and interpretable prediction models. This was motivated by two observations: (1) Regression modeling applications often involve complex diverse predictor-response relationships , which occur when the optimal regression models (of given regression model type) fitting two or more distinct logical groups of data are highly different. (2) State-of-the-art regression methods are often unable to adequately model such relationships. This paper defines PXR models using several patterns and local regression models, which respectively serve as logical and behavioral characterizations of distinct predictor-response relationships. The paper also introduces a contrast pattern aided regression (CPXR) method, to build accurate PXR models. In experiments, the PXR models built by CPXR are very accurate in general, often outperforming state-of-the-art regression methods by big margins. Usually using (a) around seven simple patterns and (b) linear local regression models, those PXR models are easy to interpret; in fact, their complexity is just a bit higher than that of (piecewise) linear regression models and is significantly lower than that of traditional ensemble based regression models. CPXR is especially effective for high-dimensional data. The paper also discusses how to use CPXR methodology for analyzing prediction models and correcting their prediction errors.
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    Granular Evaluation of Anomalies in Wireless Sensor Networks Using Dynamic Data Partitioning with an Entropy Criteria (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: This paper presents an anomaly detection model that is granular and distributed to accurately and efficiently identify sensed data anomalies within wireless sensor networks. A more decentralised mechanism is introduced with wider use of in-network processing on a hierarchical sensor node topology resulting in a robust framework for dynamic data domains. This efficiently addresses the big data issue that is encountered in large scale industrial sensor network applications. Data vectors on each node’s observation domain is first partitioned using an unsupervised approach that is adaptive regarding dynamic data streams using cumulative point-wise entropy and average relative density . Second order statistical analysis applied on average relative densities and mean entropy values is then used to differentiate anomalies through robust and adaptive thresholds that are responsive to a dynamic environment. Anomaly detection is then performed in a non-parametric and non-probabilistic manner over the different network tiers in the hierarchical topology in offering increased granularity for evaluation. Experiments were performed extensively using both real and artificial data distributions representative of different dynamic and multi-density observation domains. Results demonstrate higher accuracies in detection as more than 94 percent accompanied by a desirable reduction of more than 85 percent in communication costs when compared to existing centralized methods.
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    Modeling the Probability of a Strikeout for a Batter/Pitcher Matchup (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: We analyze models for predicting the probability of a strikeout for a batter/pitcher matchup in baseball using player descriptors that can be estimated accurately from small samples. We start with the log5 model which has been used extensively for describing matchups in sports. Log5 is a special case of a logit model and we use constrained logistic regression over nearly one million matchup observations to assess the use of the log5 explanatory variables for this application. We also show that a batter/pitcher ground ball rate interaction variable is significant for the prediction of strikeout probability and we provide physical justification for the inclusion of this variable in the model. We quantify the differences among the models and show that batters control the majority of the variance in predicted strikeout rate.
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    Quantitative Measurement of Split of the Second Heart Sound (S2) (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: This study proposes a quantitative measurement of split of the second heart sound (S2) based on nonstationary signal decomposition to deal with overlaps and energy modeling of the subcomponents of S2. The second heart sound includes aortic (A2) and pulmonic (P2) closure sounds. However, the split detection is obscured due to A2-P2 overlap and low energy of P2. To identify such split, HVD method is used to decompose the S2 into a number of components while preserving the phase information. Further, A2s and P2s are localized using smoothed pseudo Wigner-Ville distribution followed by reassignment method. Finally, the split iscalculated by taking the differences between the means of time indices of A2s and P2s. Experiments on total 33 clips of S2 signals are performed for evaluation of the method. The mean ± standard deviation of the split is 34.7 ± 4.6 ms. The method measures the splitefficiently, even when A2-P2 overlap is ≤ 20 ms and the normalized peak temporal ratio of P2 to A2 is low (≥ 0.22). This proposed method thus, demonstrates its robustness by defining split detectability (SDT), the split detection aptness through detecting P2s, by measuring upto 96 percent. Such findings reveal the effectiveness of the method as competent against the other baselines, especially for A2-P2 overlaps and low energy P2.
    Print ISSN: 1545-5963
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    Topics: Biology , Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computational Intelligence Society ; The IEEE Computer Society ; The IEEE Control Systems Society ; The IEEE Engineering in Medicine and Biology Society ; The Association for Computing Machinery.
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    An Optimized LMMSE Based Method for 3D MRI Denoising (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: Post-acquisition denoising of magnetic resonance (MR) images is an important step to improve any quantitative measurement of the acquired data. In this paper, assuming a Rician noise model, a new filtering method based on the linear minimum mean square error (LMMSE) estimation is introduced, which employs the self-similarity property of the MR data to restore the noise-less signal. This method takes into account the structural characteristics of images and the Bayesian mean square error (Bmse) of the estimator to address the denoising problem. In general, a twofold data processing approach is developed; first, the noisy MR data is processed using a patch-based L 2 -norm similarity measure to provide the primary set of samples required for the estimation process. Afterwards, the Bmse of the estimator is derived as the optimization function to analyze the pre-selected samples and minimize the error between the estimated and the underlying signal. Compared to the LMMSE method and also its recently proposed SNR-adapted realization (SNLMMSE), the optimized way of choosing the samples together with the automatic adjustment of the filtering parameters lead to a more robust estimation performance with our approach. Experimental results show the competitive performance of the proposed method in comparison with related state-of-the-art methods.
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    Topics: Biology , Computer Science
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    RBioCloud: A Light-Weight Framework for Bioconductor and R-based Jobs on the Cloud (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: Large-scale ad hoc analytics of genomic data is popular using the R-programming language supported by over 700 software packages provided by Bioconductor. More recently, analytical jobs are benefitting from on-demand computing and storage, their scalability and their low maintenance cost, all of which are offered by the cloud. While biologists and bioinformaticists can take an analytical job and execute it on their personal workstations, it remains challenging to seamlessly execute the job on the cloud infrastructure without extensive knowledge of the cloud dashboard. How analytical jobs can not only with minimum effort be executed on the cloud, but also how both the resources and data required by the job can be managed is explored in this paper. An open-source light-weight framework for executing R-scripts using Bioconductor packages, referred to as ‘RBioCloud’, is designed and developed. RBioCloud offers a set of simple command-line tools for managing the cloud resources, the data and the execution of the job. Three biological test cases validate the feasibility of RBioCloud. The framework is available from http://www.rbiocloud.com .
    Print ISSN: 1545-5963
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    Topics: Biology , Computer Science
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    Optimal Experimental Design for Gene Regulatory Networks in the Presence of Uncertainty (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: Of major interest to translational genomics is the intervention in gene regulatory networks (GRNs) to affect cell behavior; in particular, to alter pathological phenotypes. Owing to the complexity of GRNs, accurate network inference is practically challenging and GRN models often contain considerable amounts of uncertainty. Considering the cost and time required for conducting biological experiments, it is desirable to have a systematic method for prioritizing potential experiments so that an experiment can be chosen to optimally reduce network uncertainty. Moreover, from a translational perspective it is crucial that GRN uncertainty be quantified and reduced in a manner that pertains to the operational cost that it induces, such as the cost of network intervention. In this work, we utilize the concept of mean objective cost of uncertainty (MOCU) to propose a novel framework for optimal experimental design. In the proposed framework, potential experiments are prioritized based on the MOCU expected to remain after conducting the experiment. Based on this prioritization, one can select an optimal experiment with the largest potential to reduce the pertinent uncertainty present in the current network model. We demonstrate the effectiveness of the proposed method via extensive simulations based on synthetic and real gene regulatory networks.
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    Topics: Biology , Computer Science
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    Divide and Conquer Approach to Contact Map Overlap Problem Using 2D-Pattern Mining of Protein Contact Networks (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: A novel approach to Contact Map Overlap (CMO) problem is proposed using the two dimensional clusters present in the contact maps. Each protein is represented as a set of the non-trivial clusters of contacts extracted from its contact map. The approach involves finding matching regions between the two contact maps using approximate 2D-pattern matching algorithm and dynamic programming technique. These matched pairs of small contact maps are submitted in parallel to a fast heuristic CMO algorithm. The approach facilitates parallelization at this level since all the pairs of contact maps can be submitted to the algorithm in parallel. Then, a merge algorithm is used in order to obtain the overall alignment. As a proof of concept, MSVNS, a heuristic CMO algorithm is used for global as well as local alignment. The divide and conquer approach is evaluated for two benchmark data sets that of Skolnick and Ding et al. It is interesting to note that along with achieving saving of time, better overlap is also obtained for certain protein folds.
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    Statistical Detection of Intrinsically Multivariate Predictive Genes (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-07
    Description: Canalizing genes possess broad regulatory power over a wide swath of regulatory processes. On the other hand, it has been hypothesized that the phenomenon of intrinsically multivariate prediction (IMP) is associated with canalization. However, applications have relied on user-selectable thresholds on the IMP score to decide on the presence of IMP. A methodology is developed here that avoids arbitrary thresholds, by providing a statistical test for the IMP score. In addition, the proposed procedure allows the incorporation of prior knowledge if available, which can alleviate the problem of loss of power due to small sample sizes. The issue of multiplicity of tests is addressed by family-wise error rate (FWER) and false discovery rate (FDR) controlling approaches. The proposed methodology is demonstrated by experiments using synthetic and real gene-expression data from studies on melanoma and ionizing radiation (IR) responsive genes. The results with the real data identified DUSP1 and p53, two well-known canalizing genes associated with melanoma and IR response, respectively, as the genes with a clear majority of IMP predictor pairs. This validates the potential of the proposed methodology as a tool for discovery of canalizing genes from binary gene-expression data. The procedure is made available through an R package.
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    Topics: Biology , Computer Science
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    Stochastic Synchronization of Neutral-Type Neural Networks with Multidelays Based on -Matrix (2015)
    Hindawi
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    Publication Date: 2015-08-18
    Description: The problem of stochastic synchronization of neutral-type neural networks with multidelays based on -matrix is researched. Firstly, we designed a control law of stochastic synchronization of the neural-type and multiple time-delays neural network. Secondly, by making use of Lyapunov functional and -matrix method, we obtained a criterion under which the drive and response neutral-type multiple time-delays neural networks with stochastic disturbance and Markovian switching are stochastic synchronization. The synchronization condition is expressed as linear matrix inequality which can be easily solved by MATLAB. Finally, we introduced a numerical example to illustrate the effectiveness of the method and result obtained in this paper.
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    Level of Service Analysis Based on Maximum Number of Passengers in Waiting Room of Railway Passenger Station Using Arena Simulation (2015)
    Hindawi
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    Publication Date: 2015-08-18
    Description: The level of service is an important aspect of the operation and management at a railway passenger station. Particularly, the level of service in waiting room (LOSWR) is one of the most important influential factors in deciding passengers’ satisfaction. This paper proposes a model for finding the LOSWR based on the maximum number of passengers, and an Arena simulation model that simulates passengers’ aggregation behaviors in the waiting room is presented for analyzing the LOSWR. Through the simulation, we demonstrate how the passenger advanced arrival time and the accompany rate influence the maximum number of passengers and the LOSWR. In addition, the simulation also illustrates the effect utilities and the priority of different measures that can be used to improve the LOSWR. In detail, the simulation results demonstrate that the passenger advanced arrival time and advanced check-out time have much stronger effect utilities on the maximum number of passengers and the LOSWR than other discussed factors. The simulation suggests that the Arena is an effective simulation platform for analyzing complex passengers-related behaviors at railway passenger station.
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    Position and Thickness Optimization of Ribs for Ventilation Covering Using the Micro Genetic Algorithm with an Interpolated Smooth Objective Function (2015)
    Hindawi
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    Publication Date: 2015-08-19
    Description: Structures with supporting ribs are adopted in many fields of engineering. These ribs are attached to the main plate or shell to increase stiffness and reduce the stresses of a structure. Currently, much research in structural optimization has been devoted to size or thickness optimizations. In this study, the discrete positions of the ribs of a structure are optimized in addition to their thicknesses. The objective function, which is the total weight of a structure, is a continuous function with respect to the thickness of the ribs. However, it is a stepwise function of a dimensionless variable, which represents the set of positions of the ribs. Because of this stepwise objective function, the gradient method of optimization is not applicable. Therefore, we applied the micro genetic algorithm (MGA), which does not need derivatives of the objective function. To accelerate the rate of convergence, the stepwise objective function is interpolated to a smooth artificial objective function that does not alter the optimal solution.
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    Multiobjective Shape Optimization for Deployment and Adjustment Properties of Cable-Net of Deployable Antenna (2015)
    Hindawi
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    Publication Date: 2015-08-20
    Description: Based on structural features of cable-net of deployable antenna, a multiobjective shape optimization method is proposed to help to engineer antenna’s cable-net structure that has better deployment and adjustment properties. In this method, the multiobjective optimum mathematical model is built with lower nodes’ locations of cable-net as variables, the average stress ratio of cable elements and strain energy as objectives, and surface precision and natural frequency of cable-net as constraints. Sequential quadratic programming method is used to solve this nonlinear mathematical model in conditions with different weighting coefficients, and the results show the validity and effectiveness of the proposed method and model.
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    Electric Field Model of Transcranial Electric Stimulation in Nonhuman Primates: Correspondence to Individual Motor Threshold (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Objective: To develop a pipeline for realistic head models of nonhuman primates (NHPs) for simulations of noninvasive brain stimulation, and use these models together with empirical threshold measurements to demonstrate that the models capture individual anatomical variability. Methods: Based on structural MRI data, we created models of the electric field (E-field) induced by right unilateral (RUL) electroconvulsive therapy (ECT) in four rhesus macaques. Individual motor threshold (MT) was measured with transcranial electric stimulation (TES) administered through the RUL electrodes in the same subjects. Results: The interindividual anatomical differences resulted in 57% variation in median E-field strength in the brain at fixed stimulus current amplitude. Individualization of the stimulus current by MT reduced the E-field variation in the target motor area by 27%. There was significant correlation between the measured MT and the ratio of simulated electrode current and E-field strength ( $r^{2} = 0.95$ , $p = 0.026$ ). Exploratory analysis revealed significant correlations of this ratio with anatomical parameters including of the superior electrode-to-cortex distance, vertex-to-cortex distance, and brain volume ( $r^{2} > 0.96$ , $p 〈 0.02$ ). The neural activation threshold was estimated to be $0.45 pm 0.07$ V/cm for 0.2-ms stimulus pulse width. Conclusion: These results suggest that our individual-specific NHP E-field models appropriately capture individual anatomical variability relevant to the dosing of TES/ECT. These findings are exploratory due to the small number of subjects. Sign- ficance: This study can contribute insight in NHP studies of ECT and other brain stimulation interventions, help link the results to clinical studies, and ultimately lead to more rational brain stimulation dosing paradigms.
    Print ISSN: 0018-9294
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    Topics: Medicine , Technology
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    IEEE Transactions on Biomedical Engineering publication information (2015)
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    Publication Date: 2015-08-21
    Print ISSN: 0018-9294
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    Topics: Medicine , Technology
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    Local Gradients in Electrotonic Loading Modulate the Local Effective Refractory Period: Implications for Arrhythmogenesis in the Infarct Border Zone (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Ectopic electrical activity that originates in the peri-infarct region can give rise to potentially lethal re-entrant arrhythmias. The spatial variation in electrotonic loading that results from structural remodelling in the infarct border zone may increase the probability that focal activity will trigger electrical capture, but this has not previously been investigated systematically. This study uses in-silico experiments to examine the structural modulation of effective refractory period on ectopic beat capture. Informed by 3-D reconstructions of myocyte organization in the infarct border zone, a region of rapid tissue expansion is abstracted to an idealized representation. A novel metric is introduced that defines the local electrotonic loading as a function of passive tissue properties and boundary conditions. The effective refractory period correlates closely with local electrotonic loading, while the action potential duration, conduction, and upstroke velocity reduce in regions of increasing electrotonic load. In the presence of focal ectopic stimuli, spatial variation in effective refractory period can cause unidirectional conduction block providing a substrate for reentrant arrhythmias. Consequently, based on the observed results, a possible novel mechanism for arrhythmogenesis in the infarct border zone is proposed.
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    Topics: Medicine , Technology
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    Rock Stars of Cybersecurity House Advertisement (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-22
    Description: Prospective authors are requested to submit new, unpublished manuscripts for inclusion in the upcoming event described in this call for papers.
    Print ISSN: 1521-9615
    Electronic ISSN: 1558-366X
    Topics: Computer Science , Natural Sciences in General , Technology
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The American Institute of Physics (AIP) and the IEEE Computer Society.
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    An Impressive Anthology of Microbiology Modeling [Book review] (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-22
    Description: Kalyani Nair reviews "Multiscale Modeling in Biomechanics and Mechanobiology", edited by S. De, W. Hwang, and E. Kuhl, declaring it useful for anyone looking to get a quick overview of the field over a broad spectrum of areas.
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    Topics: Computer Science , Natural Sciences in General , Technology
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    Analysis of Traffic Conditions in Urban Region Based on Data from Fixed Detectors (2015)
    Hindawi
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    Publication Date: 2015-08-24
    Description: To evaluate traffic conditions in an urban region, the average travel speed in the street network and the average traffic flow per lane are selected as indexes. The results for identifying traffic conditions are obtained using macroscopic fundamental diagram. Because of the difficulty of collecting the traffic parameter of travel speed from widely distributed fixed detectors directly, in this paper, the relationship between average travel speed and queue lengths at signalized intersections within the urban area is established based on an equivalent assumption. Finally, the average travel speed estimation model proposed in this paper is tested with microscopic simulation platform, and the results showed that the average travel speed estimation model performed well with satisfactory accuracy. In addition, the best performance of the network efficiency can be identified based on the reflections of macroscopic fundamental diagram, and the evaluation system is simple enough for application in engineering. Therefore, the result is instructive both for generating traffic control strategies and for making route choices.
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    EPP Energy Efficiency Calculation and Influencing Factor Analysis: Cases in China (2015)
    Hindawi
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    Publication Date: 2015-08-24
    Description: Efficiency power plant (EPP) promotes the use of energy efficiency power plant technology and energy efficient equipment, coupled with its low-input, zero pollution, zero emissions, and other advantages, having an important role in the control of energy consumption and energy saving. In order to carry out scientific EPP investment decisions, the level of energy efficiency is an important basis for investment decisions. This paper introduces total factor energy efficiency (TFEE) in energy efficiency calculation of EPP, constructs energy efficiency calculation model considering environmental benefits, and takes the micro and macro cases in China for analysis; the results show that the TFEE of both single energy efficiency project and EPP are at a relatively high level (above 0.7), and there is a huge gap between calculation results considering and without considering the environmental benefit. In order to discuss energy efficiency influencing factors, the paper analyzes generalized technological advances variation feature of China typical provinces implementing EPP based on generalized technological advances decomposition model by Malmquist index, finding that the steady growth of index in these provinces is derived from the management level of implementation of EPP and the large-scale production capacity of formation and management. We hope the models and conclusions could provide some references on EPP energy efficiency calculation and decision.
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    Automorphism Properties and Classification of Adinkras (2015)
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    Publication Date: 2015-08-25
    Description: Adinkras are graphical tools for studying off-shell representations of supersymmetry. In this paper we efficiently classify the automorphism groups of Adinkras relative to a set of local parameters. Using this, we classify Adinkras according to their equivalence and isomorphism classes. We extend previous results dealing with characterization of Adinkra degeneracy via matrix products and present algorithms for calculating the automorphism groups of Adinkras and partitioning Adinkras into their isomorphism classes.
    Print ISSN: 1687-9120
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    Synchronization and Stability of Two Unbalanced Rotors with Fast Antirotation considering Energy Balance (2015)
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    Publication Date: 2015-08-18
    Description: We consider synchronization and stability of two unbalanced rotors reversely and fast excited by induction motors fixed on an oscillating body. We explore the energy balance of the system and show how the energy is transferred between the rotors via the oscillating body allowing the implementation of the synchronization of the two rotors. An approximate analytical analysis, energy balance method, allows deriving the synchronization condition, and the stability criterion of the synchronization is deduce by disturbance differential equations. Later, to prove the correctness of the theoretical analysis, many features of the vibrating system are computed and discussed by computer simulations. The proposed method may be useful for analyzing and understanding the mechanism of synchronization, stability, and energy balance of similar fast rotation rotors excited by induction motors in vibrating systems.
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    A New Lane Departure Warning Algorithm Considering the Driver’s Behavior Characteristics (2015)
    Hindawi
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    Publication Date: 2015-08-18
    Description: In order to meet the driving safety warning required for different driver types and situations, a new lane departure warning (LDW) algorithm was proposed. Its adaptability is much better through setting the different thresholds of time to lane crossing (TLC) using fuzzy control method for driver with different driving behaviors in different lanes and different vehicle movements. To ensure the accuracy of computation of TLC under the different actual driving scenarios, the algorithm was established based on vehicle kinematics and advanced mathematics compared to other ways of computation of TLC. On this basis, a LDW strategy determining driver's intentions was presented by introducing identifying vehicle movements. Finally, a vast quantity of the real vehicle experiments was given to demonstrate the effectiveness of the proposed LDW algorithm. The results of the tests show that the algorithm can decrease false alarm rate effectively because of distinguishing from unconscious by real-time vehicle movements, and promote the adaptability to the driver behavior characteristics, so it has favorable driver acceptance and strong intelligence.
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    Cooperative Search by Multiple Unmanned Aerial Vehicles in a Nonconvex Environment (2015)
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    Publication Date: 2015-08-18
    Description: This paper presents a distributed cooperative search algorithm for multiple unmanned aerial vehicles (UAVs) with limited sensing and communication capabilities in a nonconvex environment. The objective is to control multiple UAVs to find several unknown targets deployed in a given region, while minimizing the expected search time and avoiding obstacles. First, an asynchronous distributed cooperative search framework is proposed by integrating the information update into the coverage control scheme. And an adaptive density function is designed based on the real-time updated probability map and uncertainty map, which can balance target detection and environment exploration. Second, in order to handle nonconvex environment with arbitrary obstacles, a new transformation method is proposed to transform the cooperative search problem in the nonconvex region into an equivalent one in the convex region. Furthermore, a control strategy for cooperative search is proposed to plan feasible trajectories for UAVs under the kinematic constraints, and the convergence is proved by LaSalle’s invariance principle. Finally, by simulation results, it can be seen that our proposed algorithm is effective to handle the search problem in the nonconvex environment and efficient to find targets in shorter time compared with other algorithms.
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    Weighted Nuclear Norm Minimization Based Tongue Specular Reflection Removal (2015)
    Hindawi
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    Publication Date: 2015-08-18
    Description: In computational tongue diagnosis, specular reflection is generally inevitable in tongue image acquisition, which has adverse impact on the feature extraction and tends to degrade the diagnosis performance. In this paper, we proposed a two-stage (i.e., the detection and inpainting pipeline) approach to address this issue: (i) by considering both highlight reflection and subreflection areas, a superpixel-based segmentation method was adopted for the detection of the specular reflection areas; (ii) by extending the weighted nuclear norm minimization (WNNM) model, a nonlocal inpainting method is proposed for specular reflection removal. Experimental results on synthetic and real images show that the proposed method is accurate in detecting the specular reflection areas and is effective in restoring tongue image with more natural texture information of tongue body.
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    Numerical Investigation on Fluid Flow in a 90-Degree Curved Pipe with Large Curvature Ratio (2015)
    Hindawi
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    Publication Date: 2015-08-18
    Description: In order to understand the mechanism of fluid flows in curved pipes, a large number of theoretical and experimental researches have been performed. As a critical parameter of curved pipe, the curvature ratio has received much attention, but most of the values of are very small () or relatively small (). As a preliminary study and simulation this research studied the fluid flow in a 90-degree curved pipe of large curvature ratio. The Detached Eddy Simulation (DES) turbulence model was employed to investigate the fluid flows at the Reynolds number range from 5000 to 20000. After validation of the numerical strategy, the pressure and velocity distribution, pressure drop, fluid flow, and secondary flow along the curved pipe were illustrated. The results show that the fluid flow in a curved pipe with large curvature ratio seems to be unlike that in a curved pipe with small curvature ratio. Large curvature ratio makes the internal flow more complicated; thus, the flow patterns, the separation region, and the oscillatory flow are different.
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    Consensus for Discrete-Time Multiagent Systems (2015)
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    Publication Date: 2015-08-19
    Description: An consensus problem of multiagent systems is studied by introducing disturbances into the systems. Based on control theory and consensus theory, a condition is derived to guarantee the systems both reach consensus and have a certain property. Finally, an example is worked out to demonstrate the effectiveness of the theoretical results.
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    Data Stream Classification Based on the Gamma Classifier (2015)
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    Publication Date: 2015-08-19
    Description: The ever increasing data generation confronts us with the problem of handling online massive amounts of information. One of the biggest challenges is how to extract valuable information from these massive continuous data streams during single scanning. In a data stream context, data arrive continuously at high speed; therefore the algorithms developed to address this context must be efficient regarding memory and time management and capable of detecting changes over time in the underlying distribution that generated the data. This work describes a novel method for the task of pattern classification over a continuous data stream based on an associative model. The proposed method is based on the Gamma classifier, which is inspired by the Alpha-Beta associative memories, which are both supervised pattern recognition models. The proposed method is capable of handling the space and time constrain inherent to data stream scenarios. The Data Streaming Gamma classifier (DS-Gamma classifier) implements a sliding window approach to provide concept drift detection and a forgetting mechanism. In order to test the classifier, several experiments were performed using different data stream scenarios with real and synthetic data streams. The experimental results show that the method exhibits competitive performance when compared to other state-of-the-art algorithms.
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    Closed-Form Solutions of the Thomas-Fermi in Heavy Atoms and the Langmuir-Blodgett in Current Flow ODEs in Mathematical Physics (2015)
    Hindawi
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    Publication Date: 2015-08-19
    Description: Two kinds of second-order nonlinear, ordinary differential equations (ODEs) appearing in mathematical physics are analyzed in this paper. The first one concerns the Thomas-Fermi (TF) equation, while the second concerns the Langmuir-Blodgett (LB) equation in current flow. According to a mathematical methodology recently developed, the exact analytic solutions of both TF and LB ODEs are proposed. Both of these are nonlinear of the second order and by a series of admissible functional transformations are reduced to Abel’s equations of the second kind of the normal form. The closed form solutions of the TF and LB equations in the phase and physical plane are given. Finally a new interesting result has been obtained related to the derivative of the TF function at the limit.
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    Reversible Watermarking Using Prediction-Error Expansion and Extreme Learning Machine (2015)
    Hindawi
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    Publication Date: 2015-08-19
    Description: Currently, the research for reversible watermarking focuses on the decreasing of image distortion. Aiming at this issue, this paper presents an improvement method to lower the embedding distortion based on the prediction-error expansion (PE) technique. Firstly, the extreme learning machine (ELM) with good generalization ability is utilized to enhance the prediction accuracy for image pixel value during the watermarking embedding, and the lower prediction error results in the reduction of image distortion. Moreover, an optimization operation for strengthening the performance of ELM is taken to further lessen the embedding distortion. With two popular predictors, that is, median edge detector (MED) predictor and gradient-adjusted predictor (GAP), the experimental results for the classical images and Kodak image set indicate that the proposed scheme achieves improvement for the lowering of image distortion compared with the classical PE scheme proposed by Thodi et al. and outperforms the improvement method presented by Coltuc and other existing approaches.
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    Nonlinear Dynamics, Fixed Points and Coupled Fixed Points in Generalized Gauge Spaces with Applications to a System of Integral Equations (2015)
    Hindawi
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    Publication Date: 2015-08-20
    Description: We will discuss discrete dynamics generated by single-valued and multivalued operators in spaces endowed with a generalized metric structure. More precisely, the behavior of the sequence of successive approximations in complete generalized gauge spaces is discussed. In the same setting, the case of multivalued operators is also considered. The coupled fixed points for mappings and are discussed and an application to a system of nonlinear integral equations is given.
    Print ISSN: 1026-0226
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    A Time Discontinuous Galerkin Finite Element Method for Quasi-Linear Sobolev Equations (2015)
    Hindawi
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    Publication Date: 2015-08-21
    Description: We present a time discontinuous Galerkin finite element scheme for quasi-linear Sobolev equations. The approximate solution is sought as a piecewise polynomial of degree in time variable at most with coefficients in finite element space. This piecewise polynomial is not necessarily continuous at the nodes of the partition for the time interval. The existence and uniqueness of the approximate solution are proved by use of Brouwer’s fixed point theorem. An optimal -norm error estimate is derived. Just because of a damping term included in quasi-linear Sobolev equations, which is the distinct character different from parabolic equation, more attentions are paid to this term in the study. This is the significance of this paper.
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    G-Doob-Meyer Decomposition and Its Applications in Bid-Ask Pricing for Derivatives under Knightian Uncertainty (2015)
    Hindawi
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    Publication Date: 2015-08-21
    Description: The target of this paper is to establish the bid-ask pricing framework for the American contingent claims against risky assets with G-asset price systems on the financial market under Knightian uncertainty. First, we prove G-Dooby-Meyer decomposition for G-supermartingale. Furthermore, we consider bid-ask pricing American contingent claims under Knightian uncertainty, by using G-Dooby-Meyer decomposition; we construct dynamic superhedge strategies for the optimal stopping problem and prove that the value functions of the optimal stopping problems are the bid and ask prices of the American contingent claims under Knightian uncertainty. Finally, we consider a free boundary problem, prove the strong solution existence of the free boundary problem, and derive that the value function of the optimal stopping problem is equivalent to the strong solution to the free boundary problem.
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    Electronic ISSN: 1687-0042
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    Certain Properties of -Hypergeometric Functions (2015)
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    Publication Date: 2015-08-21
    Description: The quotients of certain -hypergeometric functions are presented as -fractions which converge uniformly in the unit disc. These results lead to the existence of certain -hypergeometric functions in the class of either -convex functions, , or -starlike functions .
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    Semisupervised ECG Ventricular Beat Classification With Novelty Detection Based on Switching Kalman Filters (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Automatic processing and accurate diagnosis of pathological electrocardiogram (ECG) signals remains a challenge. As long-term ECG recordings continue to increase in prevalence, driven partly by the ease of remote monitoring technology usage, the need to automate ECG analysis continues to grow. In previous studies, a model-based ECG filtering approach to ECG data from healthy subjects has been applied to facilitate accurate online filtering and analysis of physiological signals. We propose an extension of this approach, which models not only normal and ventricular heartbeats, but also morphologies not previously encountered. A switching Kalman filter approach is introduced to enable the automatic selection of the most likely mode (beat type), while simultaneously filtering the signal using appropriate prior knowledge. Novelty detection is also made possible by incorporating a third mode for the detection of unknown (not previously observed) morphologies, and denoted as X-factor. This new approach is compared to state-of-the-art techniques for the ventricular heartbeat classification in the MIT-BIH arrhythmia and Incart databases. $F_1$ scores of $mathbf {98.3%}$ and $mathbf {99.5%}$ were found on each database, respectively, which are superior to other published algorithms’ results reported on the same databases. Only $mathbf {3%}$ of all the beats were discarded as X-factor, and the majority of these beats contained high levels of noise. The proposed technique demonstrates accurate beat classification in the presence of previously unseen (and unlearned) morphologies and noise, and provides an automated method for morphological analysis of arbitrary (unknown) ECG leads.
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    Numerical Investigation of the Mechanisms of Ultrasound-Modulated Bioluminescence Tomography (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Objective : A hybrid imaging technique, ultrasound-modulated luminescence tomography, that uses ultrasound to modulate diffusely propagating light has been shown to improve the spatial resolution of optical images. This paper investigates the underlying modulation mechanisms and the feasibility of applying this technique to improve spatial resolution in bioluminescence tomography. Methods : Ultrasound-modulated bioluminescence tomography was studied numerically to identify the effects of four factors (reduced optical scattering coefficient, optical absorption coefficient, refractive index, and luciferase concentration) on the depth of light modulation. In practice, an open source finite-element method tool for simulation of diffusely propagating light, near infrared fluorescence and spectral tomography, was modified to incorporate the effects of ultrasound modulation. The signal-to-noise ratios of detected modulated bioluminescent emissions are calculated using the optical and physical properties of a mouse model. Results : The modulation depth of the bioluminescent emission affected by the US induced variation of local concentration of the light emitting enzyme luciferase was at least two orders of magnitude greater than that caused by variations in the other factors. For surface radiances above approximately $10^7$ $hbox{photons}$ / $hbox{s}$ / $hbox{cm}^{2}$ / $hbox{sr,}$ the corresponding SNRs are detectable with the currently available detector technologies. Conclusion : The dominant effect in generation of ultrasound-modulated bioluminescence is ultrasound induced variation in luciferase concentration. The SNR analysis confirms the- feasibility of applying ultrasound-modulated bioluminescence tomography in preclinical imaging of mice. Significance : The simulation model developed suggests ultrasound-modulated bioluminescence tomography is a potential technique to improve the spatial resolution of bioluminescence tomography.
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    Variable Ventilation as a Diagnostic Tool for the Injured Lung (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Mechanical ventilation of patients with acute respiratory distress syndrome (ARDS) is a necessary life support measure which may lead to ventilator-induced lung injury, a complication that can be reduced or ameliorated by using appropriate tidal volumes and positive end-expiratory pressures. However, the optimal mechanical ventilation parameters are almost certainly different for each patient, and will vary with time as the injury status of the lung changes. In order to optimize mechanical ventilation in an individual ARDS patient, therefore, it is necessary to track the manner in which injury status is reflected in the mechanical properties of the lungs. Accordingly, we developed an algorithm for assessing the time-dependent manner in which different lung regions open (recruit) and close (derecruit) as a function of the pressure waveform that is applied to the airways during mechanical ventilation. We used this algorithm to test the notion that variable ventilation provides the dynamic perturbations in lung volume necessary to accurately identify recruitment/derecruitment dynamics in the injured lung. We performed this test on synthetic pressure and flow data generated with established numerical models of lung function corresponding to both healthy mice and mice with lung injury. The data were generated by subjecting the models to a variety of mechanical ventilation regimens including variable ventilation. Our results support the hypothesis that variable ventilation can be used as a diagnostic tool to identify the injury status of the lung in ARDS.
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    Optimization of Single-Trial Detection of Event-Related Potentials Through Artificial Trials (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Goal: Many brain–computer interface (BCI) classification techniques rely on a large number of labeled brain responses to create efficient classifiers. A large database representing all of the possible variability in the signal is impossible to obtain in a short period of time, and prolonged calibration times prevent efficient BCI use. We propose to improve BCIs based on the detection of event-related potentials (ERPs) in two ways. Methods: First, we increase the size of the training database by considering additional deformed trials. The creation of the additional deformed trials is based on the addition of Gaussian noise, and on the variability of the ERP latencies. Second, we exploit the variability of the ERP latencies by combining decisions across multiple deformed trials. These new methods are evaluated on data from 16 healthy subjects participating in a rapid serial visual presentation task. Results: The results show a significant increase in the performance of single-trial detection with the addition of artificial trials, and the combination of decisions obtained from altered trials. When the number of trials to train a classifier is low, the proposed approach allows us improve performance from an AUC of $0.533pm 0.080$ to $0.905pm 0.053$ . This improvement represents approximately an 80% reduction in classification error. Conclusion: These results demonstrate that artificially increasing the training dataset leads to improved single-trial detection. Significance: Calibration sessions can be shortened for BCIs based on ERP detection.
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    A Dual-Mode Large-Arrayed CMOS ISFET Sensor for Accurate and High-Throughput pH Sensing in Biomedical Diagnosis (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Goal: The existing ISFET-based DNA sequencing detects hydrogen ions released during the polymerization of DNA strands on microbeads, which are scattered into microwell array above the ISFET sensor with unknown distribution. However, false pH detection happens at empty microwells due to crosstalk from neighboring microbeads. In this paper, a dual-mode CMOS ISFET sensor is proposed to have accurate pH detection toward DNA sequencing. Methods: Dual-mode sensing, optical and chemical modes, is realized by integrating a CMOS image sensor (CIS) with ISFET pH sensor, and is fabricated in a standard 0.18-μm CIS process. With accurate determination of microbead physical locations with CIS pixel by contact imaging, the dual-mode sensor can correlate local pH for one DNA slice at one location-determined microbead, which can result in improved pH detection accuracy. Moreover, toward a high-throughput DNA sequencing, a correlated-double-sampling readout that supports large array for both modes is deployed to reduce pixel-to-pixel nonuniformity such as threshold voltage mismatch. Results: The proposed CMOS dual-mode sensor is experimentally examined to show a well correlated pH map and optical image for microbeads with a pH sensitivity of 26.2 mV/pH, a fixed pattern noise (FPN) reduction from 4% to 0.3%, and a readout speed of 1200 frames/s. Conclusion: A dual-mode CMOS ISFET sensor with suppressed FPN for accurate large-arrayed pH sensing is proposed and demonstrated with state-of-the-art measured results toward accurate and high-throughput DNA sequencing. Significance: The developed dual-mode CMOS ISFET sensor has great potential for future personal genome diagnostics with high accuracy and low cost.
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    Effects of Visual Feedback Distortion on Gait Adaptation: Comparison of Implicit Visual Distortion Versus Conscious Modulation on Retention of Motor Learning (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Goal : Visual feedback can be used during gait rehabilitation to improve the efficacy of training. We presented a paradigm called visual feedback distortion; the visual representation of step length was manipulated during treadmill walking. Our prior work demonstrated that an implicit distortion of visual feedback of step length entails an unintentional adaptive process in the subjects’ spatial gait pattern. Here, we investigated whether the implicit visual feedback distortion, versus conscious correction, promotes efficient locomotor adaptation that relates to greater retention of a task. Methods: Thirteen healthy subjects were studied under two conditions: (1) we implicitly distorted the visual representation of their gait symmetry over 14 min, and (2) with help of visual feedback, subjects were told to walk on the treadmill with the intent of attaining the gait asymmetry observed during the first implicit trial. After adaptation, the visual feedback was removed while subjects continued walking normally. Over this 6-min period, retention of preserved asymmetric pattern was assessed. Results: We found that there was a greater retention rate during the implicit distortion trial than that of the visually guided conscious modulation trial. Conclusion: This study highlights the important role of implicit learning in the context of gait rehabilitation by demonstrating that training with implicit visual feedback distortion may produce longer lasting effects. Significance: This suggests that using visual feedback distortion could improve the effectiveness of treadmill rehabilitation processes by influencing the retention of motor skills.
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    Modeling Implantable Passive Mechanisms for Modifying the Transmission of Forces and Movements Between Muscle and Tendons (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: This paper explores the development of biomechanical models for evaluating a new class of passive mechanical implants for orthopedic surgery. The proposed implants take the form of passive engineered mechanisms, and will be used to improve the functional attachment of muscles to tendons and bone by modifying the transmission of forces and movement inside the body. Specifically, we present how two types of implantable mechanisms may be modeled in the open-source biomechanical software OpenSim. The first implant, which is proposed for hand tendon-transfer surgery, differentially distributes the forces and movement from one muscle across multiple tendons. The second implant, which is proposed for knee-replacement surgery, scales up the forces applied to the knee joint by the quadriceps muscle. This paper's key innovation is that such mechanisms have never been considered before in biomechanical simulation modeling and in surgery. When compared with joint function enabled by the current surgical practice of using sutures to make the attachment, biomechanical simulations show that the surgery with 1) the differential mechanism (tendon network) implant improves the fingers’ ability to passively adapt to an object's shape significantly during grasping tasks (2.74× as measured by the extent of finger flexion) for the same muscle force, and 2) the force-scaling implant increases knee-joint torque by 84% for the same muscle force. The critical significance of this study is to provide a methodology for the design and inclusion of the implants into biomechanical models and validating the improvement in joint function they enable when compared with current surgical practice.
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    The Role of Pulse Repetition Rate in nsPEF-Induced Electroporation: A Biological and Numerical Investigation (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: The impact of pulse repetition rate (PRR) in modulating electroporation (EP) induced by nanosecond pulsed electric fields (nsPEFs) in mammalian cells was approached here by performing both biological and numerical analysis. Plasma membrane permeabilization and viability of Jurkat cells were analyzed after exposure to 500, 1.3 MV/m, 40 ns PEFs with variable PRR (2–30 Hz). A finite-element model was used to investigate EP dynamics in a single cell under the same pulsing conditions, by looking at the time course of transmembrane voltage and pore density on the ns time scale. The biological observations showed an increased EP and reduced viability of the exposed cells at lower PRR in the considered range. The numerical analysis resulted in different dynamics of plasma membrane response when ns pulses were delivered with different PRR, consistently with a phenomenon of electrodesensitization recently hypothesized by another research group.
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    Global and Local Panoramic Views for Gastroscopy: An Assisted Method of Gastroscopic Lesion Surveillance (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Gastroscopy plays an important role in the diagnosis of gastric disease. In this paper, we develop an image panoramic system to assist endoscopists in improving lesion surveillance and reducing many of the tedious operations associated with gastroscopy. The constructed panoramic view has two categories: 1) the local view broadens the endoscopist's field of view in real time. Combining with the original gastroscopic video, this mosaicking view enables the endoscopist to diagnose the lesion comprehensively; 2) the global view constructs a large-area panoramic scene of the internal gastric surface, which can be used for intraoperative surgical navigation and postoperative scene review. Due to the irregular texture and inconsistent reflection of the gastric internal surface, common registration methods cannot accurately stitch this surface. Thereby, a six degree of freedom position tracking endoscope is devised to accommodate for the accumulated mosaicking error and provide efficient mosaicking results. For the global view, a dual-cube constraint model and a Bundle Adjustment algorithm are incorporated to deal with the mosaicking error caused by the irregular inflation and nonrigid deformation of the stomach. Moreover, texture blending and frame selection schemes are developed to make the mosaicking results feasible in real-clinical applications. The experimental results demonstrate that our system performs with a speed of 7.12 frames/s in a standard computer environment, and the mosaicking mean error is 0.43 mm for local panoramic view and 3.71 mm for global panoramic view.
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    A Smart Capsule With GI-Tract-Location-Specific Payload Release (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: In this paper, we present a smart capsule for location-specific drug release in the gastrointestinal tract. Once activated through a magnetic proximity fuse, the capsule opens up and releases its powdered payload in a location specified by an implanted miniature magnetic marker or an externally worn larger magnet. The capsule (9 mm × 26 mm) comprises of two compartments: one contains a charged capacitor and a reed switch, while the second one houses the drug reservoir capped by a taut nylon thread intertwined with a nichrome wire. The nichrome wire is connected to the capacitor through the reed switch. The capacitor is charged to 2.7 V before ingestion and once within the proximity of the permanent magnet; the reed switch closes, discharging the capacitor through the nichrome wire, melting the nylon thread, detaching the cap, and emptying the drug reservoir.
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    Design and Evaluation of a Novel Fixation Mechanism for a Transcatheter Pacemaker (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-21
    Description: Goal: The purpose of this paper was to evaluate a nitinol tine fixation design for a transcatheter pacemaker in order to determine if the tines could be easily deployed and safely removed from the myocardium, enable low, stable pacing thresholds, and minimize the potential for dislodgment. Methods: The penetration properties of 13 human hearts were compared to the deployment and fixation energy of the tines to determine if the tines could be easily deployed and removed from the myocardium. The safety factor for dislodgement was calculated by comparing the kinetic energy of the device to the fixation energy of the tines. The fixation stability was tested in 113 chronic implants across 89 animals via pacing threshold measurements or evidence of dislodgement at necropsy. Results: Based on the tine fixation and tissue energy analysis, the tines can easily penetrate the heart. The tines can be safely removed from the myocardium based on the increased tine surface area during retraction. There were no dislodgements observed in the animals and the mean pacing threshold at implant was 0.59 +/− 0.21 V and at termination was 0.65 +/− 0.36 V. The safety factor for dislodgement was determined to be 15X during simulated exercise conditions. Conclusion: The nitinol tine fixation design enabled the implant of a self-contained pacemaker within the right ventricle and was effective in meeting the design requirements. Significance: This fixation technology provides a novel solution to enable the attachment of a transcatheter pacemaker directly within the heart.
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    Global Production Planning Process considering the Supply Risk of Overseas Manufacturing Sites (2015)
    Hindawi
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    Publication Date: 2015-08-21
    Description: Although global manufacturers can produce most of their final products in local plants, they need to source components or parts from desirable overseas manufacturing partners at low cost in order to fulfill customer orders. In this global manufacturing environment, capacity information for planning is usually imprecise owing to the various risks of overseas plants (e.g., foreign governments’ policies and labor stability). It is therefore not easy for decision-makers to generate a global production plan showing the production amounts at local plants and overseas manufacturing facilities operated by manufacturing partners. In this paper, we present a new global production planning process considering the supply risk of overseas manufacturing sites. First, local experts estimate the supply capacity of an overseas plant using their judgment to determine when the risk could occur and how large the risk impact would be. Next, we run a global production planning model with the estimated supply capacities. The proposed process systematically adopts the qualitative judgments of local experts in the global production planning process and thus can provide companies with a realistic global production plan. We demonstrate the applicability of the proposed process with a real world case.
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    Observer-Based Adaptive Iterative Learning Control for a Class of Nonlinear Time Delay Systems with Input Saturation (2015)
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    Publication Date: 2015-08-21
    Description: This paper presents an adaptive iterative learning control scheme for the output tracking of a class of nonlinear systems with unknown time-varying delays and input saturation nonlinearity. An observer is presented to estimate the states and linear matrix inequality (LMI) method is employed for observer design. The assumption of identical initial condition for ILC is relaxed by introducing boundary layer function. The possible singularity problem is avoided by introducing hyperbolic tangent function. The uncertainties with time-varying delays are compensated for by the combination of appropriate Lyapunov-Krasovskii functional and Young’s inequality. Both time-varying and time-invariant radial basis function neural networks are employed to deal with system uncertainties. On the basis of a property of hyperbolic tangent function, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function in two cases, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.
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    Multimode Process Monitoring Based on Sparse Principal Component Selection and Bayesian Inference-Based Probability (2015)
    Hindawi
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    Publication Date: 2015-08-21
    Description: According to the demand for diversified products, modern industrial processes typically have multiple operating modes. At the same time, variables within the same mode often follow a mixture of Gaussian distributions. In this paper, a novel algorithm based on sparse principal component selection (SPCS) and Bayesian inference-based probability (BIP) is proposed for multimode process monitoring. SPCS can be formulated as a just-in-time regression between all PCs and each sample. SPCS selects PCs according to the nonzero regression coefficients which indicate the compact expression of the sample. This expression is necessarily discriminative: amongst all subset of PCs, SPCS selects the PCs which most compactly express the sample and rejects all other possible but less compact expressions. BIP is utilized to compute the posterior probabilities of each monitored sample belonging to the multiple components and derive an integrated global probabilistic index for fault detection of multimode processes. Finally, to verify its superiority, the SPCS-BIP algorithm is applied to the Tennessee Eastman (TE) benchmark process and a continuous stirred-tank reactor (CSTR) process.
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    2016 Richard E. Merwin Distinguished Service Award House Advertisement (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
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    Publication Date: 2015-08-25
    Description: Presents the information on the 2016 Richard E. Merwin Distinguished Service Award.
    Print ISSN: 0740-7459
    Electronic ISSN: 1937-4194
    Topics: Computer Science
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    Naming the Pain in Requirements Engineering: Comparing Practices in Brazil and Germany (2015)
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    Publication Date: 2015-08-25
    Description: As part of the Naming the Pain in Requirements Engineering (NaPiRE) initiative, researchers compared problems that companies in Brazil and Germany encountered during requirements engineering (RE). The key takeaway was that in RE, human interaction is necessary for eliciting and specifying high-quality requirements, regardless of country, project type, or company size.
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    What are Hackathons for? (2015)
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    Publication Date: 2015-08-25
    Description: A swift execution from idea to market has become a key competitive advantage for software companies to enable them to survive and grow in turbulent business environments. To combat this challenge, companies are using hackathons. A hackathon is a highly engaging, continuous event in which people in small groups produce working software prototypes in a limited amount of time. F-Secure, a software product company, views hackathons as a possible solution to the fundamental business problem of how to make revenue from an idea, spanning the phases from creating the idea to producing a software prototype. However, hackathons pose the challenge of how to transform those promising prototypes into finalized products that create revenue and real business value.
    Print ISSN: 0740-7459
    Electronic ISSN: 1937-4194
    Topics: Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computer Society.
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    Sustainability and Requirements: A Manifesto (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2015-08-25
    Description: "The Karlskrona Manifesto on Sustainability Design" is a call for discussion and action on the challenge of sustainability and its relation to software engineering. The manifesto aims to create common ground and develop a reference point for the global community of research and practice in software and sustainability. The Web extra at http://youtu.be/PXhFgswJPco is an audio podcast in which author Birgit Penzenstadler provides an audio recording of this column.
    Print ISSN: 0740-7459
    Electronic ISSN: 1937-4194
    Topics: Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computer Society.
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    Software Adaptation: Classification and a Case Study with State Chart XML (2015)
    Institute of Electrical and Electronics Engineers (IEEE)
    Details
    Publication Date: 2015-08-25
    Description: Software adaptation has become prominent owing to the proliferation of software in everyday devices. In particular, computing with the Internet of Things requires adaptability. Traditional software maintenance, which involves long, energy-consuming cycles, is no longer satisfactory. Adaptation is a lightweight software evolution that provides more transparent maintenance for users. This article classifies types of adaptation and describes an implementation of it.
    Print ISSN: 0740-7459
    Electronic ISSN: 1937-4194
    Topics: Computer Science
    Published by Institute of Electrical and Electronics Engineers (IEEE) on behalf of The IEEE Computer Society.
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