Iterative equalization combining algorithm in intersymbol interference channel

To realize joint optimization of spatial diversity and equalization combining in the intersymbol interference (ISI) channel, an iterative equalization combining algorithm is proposed. The proposed algorithm uses the coefficients of Turbo equalization to calculate the combination weights without estimating the signal to noise ratio in each diversity branch. The equalized symbols from different diversity branches are combined, and the extrinsic information output from the decoder is fed back to the equalizers, so as to exchange soft information between the equalizers and the decoder. The performance of the proposed algorithm is analyzed using the extrinsic information transfer (EXIT) chart and verified by simulations. Results show that our approach fully exploits time domain information from the multipath channel and spatial domain information from multi receiving antennas, which efficiently improve the performance of the receiver in the severe ISI channel.     

A new decomposition based evolutionary algorithm with uniform designs for many-objective optimization

For many-objective optimization problems, how to get a set of solutions with good convergence and diversity is a difficult and challenging work. In this paper, a new decomposition based evolutionary algorithm with uniform designs is proposed to achieve the goal. The proposed algorithm adopts the uniform design method to set the weight vectors which are uniformly distributed over the design space, and the size of the weight vectors neither increases nonlinearly with the number of objectives nor considers a formulaic setting. A crossover operator based on the uniform design method is constructed to enhance the search capacity of the proposed algorithm. Moreover, in order to improve the convergence performance of the algorithm, a sub-population strategy is used to optimize each sub-problem. Comparing with some efficient state-of-the-art algorithms, e.g., NSGAII-CE, MOEA/D and HypE, on six benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence.     

Genetic algorithm and self organizing map based fuzzy hybrid intelligent method for color image segmentation

The grouping of pixels based on some similarity criteria is called image segmentation. In this paper the problem of color image segmentation is considered as a clustering problem and a fixed length genetic algorithm (GA) is used to handle it. The effectiveness of GA depends on the objective function (fitness function) and the initialization of the population. A new objective function is proposed to evaluate the quality of the segmentation and the fitness of a chromosome. In fixed length genetic algorithm the chromosomes have same length, which is normally set by the user. Here, a self organizing map (SOM) is used to determine the number of segments in order to set the length of a chromosome automatically. An opposition based strategy is adopted for the initialization of the population in order to diversify the search process. In some cases the proposed method makes the small regions of an image as separate segments, which leads to noisy segmentation. A simple ad hoc mechanism is devised to refine the noisy segmentation. The qualitative and quantitative results show that the proposed method performs better than the state-of-the-art methods.     

The Interplay of Modulus,Strength, and Ductility in Adhesive Design Using Biomimetic Polymer Chemistry

High‐performance adhesives require mechanical properties tuned to demands of the surroundings. A mismatch in stiffness between substrate and adhesive leads to stress concentrations and fracture when the bonding is subjected to mechanical load. Balancing material strength versus ductility, as well as considering the relationship between adhesive modulus and substrate modulus, creates stronger joints. However, a detailed understanding of how these properties interplay is lacking. Here, a biomimetic terpolymer is altered systematically to identify regions of optimal bonding. Mechanical properties of these terpolymers are tailored by controlling the amount of a methyl methacrylate stiff monomer versus a similar monomer containing flexible poly(ethylene glycol) chains. Dopamine methacrylamide, the cross‐linking monomer, is a catechol moiety analogous to 3,4‐dihydroxyphenylalanine, a key component in the adhesive proteins of marine mussels. Bulk adhesion of this family of terpolymers is tested on metal and plastic substrates. Incorporating higher amounts of poly(ethylene glycol) into the terpolymer introduces flexibility and ductility. By taking a systematic approach to polymer design, the region in which material strength and ductility are balanced in relation to the substrate modulus is found, thereby yielding the most robust joints.     

Design criterion for fatigue strengthening of riveted beams in a 120-year-old railway metallic bridge using pre-stressed CFRP plates

This study presents a design criterion developed for fatigue strengthening of a 120-year-old metallic railway bridge in Switzerland and presents a pre-stressed un-bonded reinforcement (PUR) system developed to apply the strengthening. The PUR system uses carbon fiber reinforced polymer (CFRP) plates; however, unlike conventional pre-stressed CFRP reinforcement methods, preparation of the existing metallic bridge surface is not required. This decreases the time required for on-site strengthening procedures. The principle of the constant life diagram (CLD) and two fatigue failure criteria (Johnson and Goodman) are described. Analytical formulations are developed based on the CLD method to determine the minimum CFRP pre-stress level required to prevent fatigue crack initiation. The PUR system uses an applied pre-stress force to reduce the mean stress level (and stress ratio) to shift an existing fatigue-susceptible metallic detail from the ‘at risk’ finite life regime to the ‘safe’ infinite life regime. The applied CLD method is particularly valuable when the stress history of the detail is not known and it is difficult to assess the remaining fatigue life. Moreover, it is shown that the currently adopted approach in many structural codes which emphasizes stress range as the dominant parameter influencing fatigue life are non-conservative for tension–tension stress patterns (i.e., stress ratios of 0 < R < 1). Analyses show that the modified Johnson formula accurately reflects the combined effect of stress range, mean stress level, and material properties, and offers a relatively easy design procedure. Details of a retrofit field application on members of a riveted wrought iron railway bridge are given. A wireless sensor network (WSN) system is used for long-term monitoring of the on-site CFRP stress levels and temperature of the retrofitted details. WSN measurements indicate that increases in ambient temperature result in increased CFRP pre-stress levels.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

A new metaheuristic for optimization: Optics inspired optimization (OIO)

Due to the law of reflection, a concave reflecting surface/mirror causes the incident light rays to converge and a convex surface/mirror causes the light rays to reflect away so that they all appear to be diverging. These converging and diverging behaviors cause that the curved mirrors show different image types depending on the distance between the object and the mirror. We model such optical phenomena metaphorically into the searching process of numerical optimization by a new algorithm called optics inspired optimization (OIO). OIO treats the surface of the numerical function to be optimized as a reflecting surface in which each peak is assumed to reflect as a convex mirror and each valley to reflect as a concave one. Each individual is assumed to be an artificial object (or light point) that its artificially glittered ray is reflected back by the function surface, given that the surface is convex or concave, and the artificial image is formed (a candidate solution is generated within the search domain) based on the mirror equations adopted from physics of optics. Besides OIO, we introduce different variants of it, called ROIO (Rotation based OIO), and COIO (Convex combination based OIO) algorithms and conduct an extensive computational effort to find out the merit of the new algorithms. Our comparisons on benchmark test functions and a real world engineering design application (i.e., optimization of a centrifuge pump) demonstrate that the new algorithms are efficient and compete better than or similar to most of state of the art optimization algorithms with the advantage of accepting few input parameters.     

Nonlinear response in glass fibre non-crimp fabric reinforced vinylester composites

This paper addresses the nonlinear stress-strain response in glass fibre non-crimp fabric reinforced vinylester composite laminates subjected to in-plane tensile loading. The nonlinearity is shown to be a combination of brittle and plastic failure. It is argued that the shift from plastic to brittle behaviour in the vinylester is caused by the state of stress triaxiality caused by the interaction between fibre and vinylester. A model combining damage and plasticity is calibrated and evaluated using data from extensive experimental testing. The onset of damage is predicted using the Puck failure criterion, and the evolution of damage is calibrated from the observed softening in plies loaded in transverse tension. Shear loading beyond linear elastic response is observed to result in irreversible strains. A yield criterion is implemented for shear deformation. A strain hardening law is fitted to the stress-strain response observed in shear loaded plies. Experimental results from a selection of laminates with different layups are used to verify the numerical models. A complete set of model parameters for predicting elastic behaviour, strength and post failure softening is presented for glass fibre non-crimped fabric reinforced vinylester. The predicted behaviour from using these model parameters are shown to be in good agreement with experimental results.     

Remote Steering of Self‐Propelling Microcircuits by Modulated Electric Field

The principles and design of “active” self‐propelling particles that can convert energy, move directionally on their own, and perform a certain function is an emerging multidisciplinary research field, with high potential for future technologies. A simple and effective technique is presented for on‐demand steering of self‐propelling microdiodes that move electroosmotically on water surface, while supplied with energy by an external alternating (AC) field. It is demonstrated how one can control remotely the direction of diode locomotion by electronically modifying the applied AC signal. The swimming diodes change their direction of motion when a wave asymmetry (equivalent to a DC offset) is introduced into the signal. The data analysis shows that the ability to control and reverse the direction of motion is a result of the electrostatic torque between the asymmetrically polarized diodes and the ionic charges redistributed in the vessel. This novel principle of electrical signal‐coded steering of active functional devices, such as diodes and microcircuits, can find applications in motile sensors, MEMs, and microrobotics.