Lévy flight artificial bee colony algorithm

Artificial bee colony (ABC) optimisation algorithm is a relatively simple and recent population-based probabilistic approach for global optimisation. The solution search equation of ABC is significantly influenced by a random quantity which helps in exploration at the cost of exploitation of the search space. In the ABC, there is a high chance to skip the true solution due to its large step sizes. In order to balance between diversity and convergence in the ABC, a Lévy flight inspired search strategy is proposed and integrated with ABC. The proposed strategy is named as Lévy Flight ABC (LFABC) has both the local and global search capability simultaneously and can be achieved by tuning the Lévy flight parameters and thus automatically tuning the step sizes. In the LFABC, new solutions are generated around the best solution and it helps to enhance the exploitation capability of ABC. Furthermore, to improve the exploration capability, the numbers of scout bees are increased. The experiments on 20 test problems of different complexities and five real-world engineering optimisation problems show that the proposed strategy outperforms the basic ABC and recent variants of ABC, namely, Gbest-guided ABC, best-so-far ABC and modified ABC in most of the experiments.     

A new water-resistant snow index for the detection and mapping of snow cover on a global scale

An up-to-date spatio-temporal change analysis of global snow cover is essential for better understanding of climate–hydrological interactions. The normalized difference snow index (NDSI) is a widely used algorithm for the detection and estimation of snow cover. However, NDSI cannot discriminate between snow cover and water bodies without use of an external water mask. A stand-alone methodology for robust detection and mapping of global snow cover is presented by avoiding external dependency on the water mask. A new spectral index called water-resistant snow index (WSI) with the capability of exhibiting significant contrast between snow cover and other cover types, including water bodies, was developed. WSI uses the normalized difference between the value and hue obtained by transforming red, green, and blue, (RGB) colour composite images comprising red, green, and near-infrared bands into a hue, saturation, and value (HSV) colour model. The superiority of WSI over NDSI is confirmed by case studies conducted in major snow regions globally. Snow cover was mapped by considering monthly variation in snow cover and availability of satellite data at the global scale. A snow cover map for the year 2013 was produced at the global scale by applying the random walker algorithm in the WSI image supported by the reference data collected from permanent snow-covered and non-snow-covered areas. The resultant snow-cover map was compared to snow cover estimated by existing maps: MODIS Land Cover Type Product (MCD12Q1 v5.1, 2012), Global Land Cover by National Mapping Organizations (GLCNMO v2.0, 2008), and European Space Agency’s GlobCover 2009. A significant variation in snow cover as estimated by different maps was noted, and was was attributed to methodological differences rather than annual variation in snow cover. The resultant map was also validated with reference data, with 89.46% overall accuracy obtained. The WSI proposed in the research is expected to be suitable for seasonal and annual change analysis of global snow cover.     

Tri‐band composite cylindrical dielectric resonator antenna with hybrid mode excitation and cross‐polarization suppression

This communication investigates composite cylindrical dielectric resonator antenna (CDRA) for various wireless applications. Three important features of proposed antenna design are (i) realization of two different hybrid modes, that is, HEM_11δ and HEM_12δ mode in CDRA with the help of modified annular ring printed line (work as both magnetic dipole and electric dipole), both the hybrid modes support broadside radiation characteristics (ii) suppression of HEM_21δ mode, in order to reduce the cross‐polarization level in H‐plane of other hybrid modes (HEM_11δ and HEM_12δ mode) by an amount of 8‐10 dB (iii) creation of triple‐band attribute using the concept of composite antenna. The proposed antenna design has been fabricated and practically tested. Simulated outcomes show good agreement with measured outcomes. It works in three frequency bands, that is, 2.25‐2.79 GHz, 3.1‐4.0 GHz, and 5.05‐5.6 GHz. The designed antenna structure is appropriate for WLAN and WiMAX applications.     

Reliability evaluation and optimal design in heterogeneous multi-state series-parallel systems

This paper addresses the heterogeneous redundancy allocation problem in multi-state series-parallel reliability structures with the objective to minimize the total cost of system design satisfying the given reliability constraint and the consumer load demand. The demand distribution is presented as a piecewise cumulative load curve and each subsystem is allowed to consist of parallel redundant components of not more than three types. The system uses binary capacitated components chosen from a list of available products to provide redundancy so as to increase system performance and reliability. The components are characterized by their feeding capacity, reliability and cost. A system that consists of elements with different reliability and productivity parameters has the capacity strongly dependent upon the selection of constituent components. A binomial probability based method to compute exact system reliability index is suggested. To analyze the problem and suggest an optimal/near-optimal system structure, an ant colony optimization algorithm has been presented. The solution approach consists of a series of simple steps as used in early ant colony optimization algorithms dealing with other optimization problems and offers straightforward analysis. Four multi-state system design problems have been solved for illustration. Two problems are taken from the literature and solved to compare the algorithm with the other existing methods. The other two problems are based upon randomly generated data. The results show that the method can be appealing to many researchers with regard to the time efficiency and yet without compromising over the solution quality.     

Homotopy-based surface reconstruction with application to?acoustic signals

This work introduces a new algorithm for surface reconstruction in ℝ³ from spatially arranged one-dimensional cross sections embedded in ℝ³. This is generally the case with acoustic signals that pierce an object non-destructively. Continuous deformations (homotopies) that smoothly reconstruct information between any pair of successive cross sections are derived. The zero level set of the resulting homotopy field generates the desired surface. Four types of homotopies are suggested that are well suited to generate a smooth surface. We also provide derivation of necessary higher order homotopies that can generate a C ² surface. An algorithm to generate surface from acoustic sonar signals is presented with results. Reconstruction accuracies of the homotopies are compared by means of simulations performed on basic geometric primitives.     

Hybrid Game Strategy in Fuzzy Markov-Game-Based Control

This paper proposes a novel control approach that incorporates a hybrid game strategy in Markov-game-based fuzzy control. Specifically, we aim at designing a “safe and universally consistent” controller that exhibits an ability to maintain performance against large disturbance and environment variations. The proposed hybrid control is a convex combination (based on experiential information) of “a variation of cautious fictitious play” approach and the “minimax” control approach implemented on a fuzzy Markov game platform. We show analytical convergence of Markov-game-based control in the presence of bounded external disturbances, and extend the analysis to show convergence of the proposed Markov-game-based hybrid control approach. Controller simulation and comparison against baseline Markov game fuzzy control and fuzzy $Q$ -learning control on a highly nonlinear two-link robot brings out the superiority of the approach in handling severe environment and disturbance variations over different desired trajectories. This paper illustrates the possibility of obtaining “universal consistency,” i.e., reasonable performance against severe environment and disturbance variations, by hybridizing “cautious fictitious play” with “minimax” approaches in Markov-game-based control.      

A Markov Game-Adaptive Fuzzy Controller for Robot Manipulators

This paper develops an adaptive fuzzy controller for robot manipulators using a Markov game formulation. The Markov game framework offers a promising platform for robust control of robot manipulators in the presence of bounded external disturbances and unknown parameter variations. We propose fuzzy Markov games as an adaptation of fuzzy Q-learning (FQL) to a continuous-action variation of Markov games, wherein the reinforcement signal is used to tune online the conclusion part of a fuzzy Markov game controller. The proposed Markov game-adaptive fuzzy controller uses a simple fuzzy inference system (FIS), is computationally efficient, generates a swift control, and requires no exact dynamics of the robot system. To illustrate the superiority of Markov game-adaptive fuzzy control, we compare the performance of the controller against a) the Markov game-based robust neural controller, b) the reinforcement learning (RL)-adaptive fuzzy controller, c) the FQL controller, d) the H_infin theory-based robust neural game controller, and e) a standard RL-based robust neural controller, on two highly nonlinear robot arm control problems of i) a standard two-link rigid robot arm and ii) a 2-DOF SCARA robot manipulator. The proposed Markov game-adaptive fuzzy controller outperformed other controllers in terms of tracking errors and control torque requirements, over different desired trajectories. The results also demonstrate the viability of FISs for accelerating learning in Markov games and extending Markov game-based control to continuous state-action space problems.     

Surface modes of a sessile water drop: an optical tweezer based study

A high-precision method to study the dynamics of two-fluid interfaces using an optical tweezer and a phase-sensitive detection technique are described. The disturbances set up at the interface are studied by analyzing the motion of an optically trapped particle in the bulk of the fluid, i.e., away from the interface. The usefulness of the technique is demonstrated for the well-known problem of a horizontally vibrated sessile liquid drop. The vibrational modes of the liquid drop excited by sinusoidally vibrating the support in a horizontal plane appear as resonances in the motion of the trapped particle. The nature of the resonance is studied in detail by measuring the real part, the imaginary part, and the phase response of the motion of the particle as a function of the "effective" size of the liquid drop. Excellent quantitative agreement with the theoretically predicted values of the eigenfrequencies and damping of the surface modes is obtained.     

Tactical approaches for alleviating distance in global softwaredevelopment

To overcome the problem of distance in global software development, various managers are experimenting and quickly adjusting their tactical approaches. We discuss some emerging approaches and explain their motivations from conceptual and practical perspectives. The most intuitive approach for alleviating distance is to apply communication technologies, but this is not our focus. Rather, we examine tactics that go beyond communication technologies, tactics aimed at reducing intensive collaboration, national and organizational cultural differences, and temporal distance     

Identification of statistical patterns in complex systems via symbolic time series analysis

Identification of statistical patterns from observed time series of spatially distributed sensor data is critical for performance monitoring and decision making in human-engineered complex systems, such as electric power generation, petrochemical, and networked transportation. This paper presents an information-theoretic approach to identification of statistical patterns in such systems, where the main objective is to enhance structural integrity and operation reliability. The core concept of pattern identification is built upon the principles of Symbolic Dynamics, Automata Theory, and Information Theory. To this end, a symbolic time series analysis method has been formulated and experimentally validated on a special-purpose test apparatus that is designed for data acquisition and real-time analysis of fatigue damage in polycrystalline alloys.