E?cient Video Cutout by Paint Selection

Video cutout refers to extracting moving objects from videos, which is an important step in many video editing tasks. Recent algorithms have limitations in terms of e?ciency, interaction style, and rob...     

Sperm metabolism is altered during storage by female insects: evidence from two-photon autofluorescence lifetime measurements in bedbugs

We explore the possibility of characterizing sperm cells without the need to stain them using spectral and fluorescence lifetime analyses after multi-photon excitation in an insect model. The autofluorescence emission spectrum of sperm of the common bedbug, Cimex lectularius, was consistent with the presence of flavins and NAD(P)H. The mean fluorescence lifetimes showed smaller variation in sperm extracted from the male (tau m, τ_m = 1.54–1.84 ns) than in that extracted from the female sperm storage organ (tau m, τ_m = 1.26–2.00 ns). The fluorescence lifetime histograms revealed four peaks. These peaks (0.18, 0.92, 2.50 and 3.80 ns) suggest the presence of NAD(P)H and flavins and show that sperm metabolism can be characterized using fluorescence lifetime imaging. The difference in fluorescence lifetime variation between the sexes is consistent with the notion that female animals alter the metabolism of sperm cells during storage. It is not consistent, however, with the idea that sperm metabolism represents a sexually selected character that provides females with information about the male genotype.     

PMU based voltage security assessment of power systems exploiting principal component analysis and decision trees

The need for feature selection and dimension reduction is felt as a fundamental step in security assessment of large power systems in which the number of features representing the state of power grids dramatically increases. These large amounts of attributes are not proper to be used for computational intelligence (CI) techniques as inputs, because it may lead to a time consuming procedure with insufficient results and they are not suitable for on-line purposes and updates.This paper proposes a combined method for an online voltage security assessment in which the dimension of the token data from phasor measurement units (PMUs) is reduced by principal component analysis (PCA). Then, the features with different stability indices are put into several categories and feature selection is done by correlation analysis in each category. These selected features are then given to decision trees (DTs) for classification and security assessment of power systems.The method is applied to 39-bus test system and a part of Iran power grid. It is seen from the results that the DTs with reduced data have simpler splitting rules, better performance in saving time, reasonable DT error and they are more suitable for constant updates.     

An iterative method for suboptimal control of linear time-delayed systems

This article presents a new approach for solving the Optimal Control Problem (OCP) of linear time-delay systems with a quadratic cost functional. The proposed method can also be used for designing optimal control time-delay systems with disturbance. In this study, the Variational Iteration Method (VIM) is employed to convert the original Time-Delay Optimal Control Problem (TDOCP) into a sequence of nonhomogeneous linear two-point boundary value problems (TPBVPs). The optimal control law obtained consists of an accurate linear feedback term and a nonlinear compensation term which is the limit of an adjoint vector sequence. The feedback term is determined by solving Riccati matrix differential equation. By using the finite-step iteration of a nonlinear compensation sequence, we can obtain a suboptimal control law. Finally, Illustrative examples are included to demonstrate the validity and applicability of the technique.     

Nash equilibrium cooperative transmission strategy considering competition

In cooperative communications, employing the idle relay node for forwarding data can effectively improve the transmission rate and performance of the wireless networks. Therefore, various relay node selection algorithms are proposed. However, most of the existing algorithms just focus on the benefit caused by relay nodes, while ignoring the negative effect of the backoff duration time which does not exist in direct transmission, when more than one flow compete for the same relay node. To this end, considering both advantage and adverse impact caused by the relay node, we adopt the game-theoretic approach and propose a cooperative transmission strategy based on the Nash equilibrium, named the Nash Equilibrium Cooperative Transmission Strategy (NECTS). The NECTS can not only guarantee the gain of each flow, but also maximize the system performance, and improve the system throughput effectively. Simulation results show that the NECTS can take the advantage of cooperative communications. Meanwhile, it can avoid the unnecessary competition, and its performance outperforms that of the existing methods.     

An experimental study of adaptive control for evolutionary algorithms

In this paper, we investigate how adaptive operator selection techniques are able to efficiently manage the balance between exploration and exploitation in an evolutionary algorithm, when solving combinatorial optimization problems. We introduce new high level reactive search strategies based on a generic algorithm's controller that is able to schedule the basic variation operators of the evolutionary algorithm, according to the observed state of the search. Our experiments on SAT instances show that reactive search strategies improve the performance of the solving algorithm.     

Optimal configuration of cluster supply chains with augmented Lagrange coordination

Enterprises in an industrial cluster could dynamically alliance in the form of cluster supply chains to share inner-cluster resources and services, and respond to the ever-fluctuating customer demands in a cost-effective way. However, an effective and feasible method enabling such dynamic cluster supply chain configuration (CSCC) lags behind practice due to the conflict of interests. Researchers are designing All-in-One theoretic models to optimize CSCC with the assumed decision details of all enterprises, while in fact clustered enterprises are seeking effective decentralized decision mechanisms which protect their decision autonomy in the frequently re-configured CSC. A newly emerged multi-disciplinary optimization method, Augmented Lagrangian Coordination (ALC), which supports the open-structure collaboration with strict optimization convergence, is thoroughly investigated in this paper and applied to solve the conflict. Through a complete analysis of CSC’s configuration policies in typical stages, a generic CSCC model is proposed and then partitioned into an ALC-based decentralized decision model by the typical decision autonomy distribution in clusters. Clustered enterprises collaborate vertically and laterally along the ALC model through multi-dimensional couplings to achieve the overall consistency and optimality. Results have proved the effectiveness of ALC for CSCC problem. A set of sensitivity analysis is also conducted to find out the condition in which an order has to be fulfilled in a CSC and the most appropriate configuration.     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.