Electron backscatter diffraction (EBSD) map of AZ31 compressed to 1% strain at room temperature in a direction parallel to the extrusion direction

The collection contains an EBSD map of AZ31 compressed to 1% strain at room temperature in a direction parallel to the extrusion direction. The map was collected as part of an investigation into the role of twinning in the occurrence of a yield point elongation during deformation.

A coarse-grained parallel genetic algorithm employing cluster analysis for multi-modal numerical optimisation

This paper describes a technique for improving the performance of parallel genetic algorithms on multi-modal numerical optimisation problems. It employs a cluster analysis algorithm to identify regions of the search space in which more than one sub-population is sampling. Overlapping clusters are merged in one sub-population whilst a simple derating function is applied to samples in all other sub-populations to discourage them from further sampling in that region. This approach leads to a better distribution of the search effort across multiple subpopulations and helps to prevent premature convergence. On the test problems used, significant performance improvements over the traditional island model implementation are realised.

Channel estimation of dual-hop MIMO relay system via parallel factor analysis

The optimal source precoding matrix and relay amplifying matrix have been developed in recent works on multiple-input multiple-output (MIMO) relay communication systems assuming that the instantaneous channel state information (CSI) is available. However, in practical relay communication systems, the instantaneous CSI is unknown, and therefore, has to be estimated at the destination node. In this paper, we develop a novel channel estimation algorithm for two-hop MIMO relay systems using the parallel factor (PARAFAC) analysis. The proposed algorithm provides the destination node with full knowledge of all channel matrices involved in the communication. Compared with existing approaches, the proposed algorithm requires less number of training data blocks, yields smaller channel estimation error, and is applicable for both one-way and two-way MIMO relay systems with single or multiple relay nodes. Numerical examples demonstrate the effectiveness of the PARAFAC-based channel estimation algorithm.

The Octahedral Hexarot - a novel 6-DOF parallel manipulator

A novel 6-DOF parallel kinematic manipulator named the Octahedral Hexarot is presented and analyzed. It is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations. These features are obtained by combining a rotation-symmetric actuating arm system with links in an octahedral-like configuration. Thus the manipulator consists of a central cylindrical column with six actuated rotating upper arms that can rotate indefinitely around the central column. Each upper arm is connected to a manipulated platform by one 5-DOF lower arm link. The link arrangement of the Octahedral Hexarot is inspired by the original Gough platform. The manipulated platform is an equilateral triangle and the joint positions on the upper arms approximately form an equilateral triangle. A task dependent optimization procedure for the structural parameters is proposed and the workspace of the resulting manipulator is analyzed in depth.

Underdetermined blind source separation by parallel factor analysis in time-frequency domain

This paper presents a new time-frequency approach to the underdetermined blind source separation using the parallel factor decomposition of third-order tensors. Without any constraint on the number of active sources at an auto-term time-frequency point, this approach can directly separate the sources as long as the uniqueness condition of parallel factor decomposition is satisfied. Compared with the existing two-stage methods where the mixing matrix should be estimated at first and then used to recover the sources, our approach yields better source separation performance in the presence of noise. Moreover, the mixing matrix can be estimated at the same time of the source separation process. Numerical simulations are presented to show the superior performance of the proposed approach to some of the existing two-stage blind source separation methods that use the time-frequency representation as well.

Dimensionality reduction of protein mass spectrometry data using random projection

Protein mass spectrometry (MS) pattern recognition has recently emerged as a new method for cancer diagnosis. Unfortunately, classification performance may degrade owing to the enormously high dimensionality of the data. This paper investigates the use of Random Projection in protein MS data dimensionality reduction. The effectiveness of Random Projection (RP) is analyzed and compared against Principal Component Analysis (PCA) by using three classification algorithms, namely Support Vector Machine, Feed-forward Neural Networks and K-Nearest Neighbour. Three real-world cancer data sets are employed to evaluate the performances of RP and PCA. Through the investigations, RP method demonstrated better or at least comparable classification performance as PCA if the dimensionality of the projection matrix is sufficiently large. This paper also explores the use of RP as a pre-processing step prior to PCA. The results show that without sacrificing classification accuracy, performing RP prior to PCA significantly improves the computational time.

Parallel manipulators with a rotation-symmetric arm system

Parallel manipulators with a rotation-symmetric arm system possess all the typical advantages of parallel robots, such as high acceleration and high-accuracy positioning. Contrary to the majority of proposed parallel manipulators, the rotation-symmetric arm system leads to a large workspace in relation to the footprint of the manipulator. This paper focuses on a subclass of these manipulators with additional favorable qualities, including low inertia and high eigenfrequencies. These qualities are achieved using only 5-DOF lower arm links and by mounting all actuators on the nonmoving base column of the manipulator. The common feature of all previously proposed manipulators in this subclass is identified and several novel 3-DOF and 4-DOF members are introduced.

Projection-pursuit-based method for blind separation of nonnegative sources

This paper presents a projection pursuit (PP) based method for blind separation of nonnegative sources. First, the available observation matrix is mapped to construct a new mixing model, in which the inaccessible source matrix is normalized to be column-sum-to-1. Then, the PP method is proposed to solve this new model, where the mixing matrix is estimated column by column through tracing the projections to the mapped observations in specified directions, which leads to the recovery of the sources. The proposed method is much faster than Chan's method, which has similar assumptions to ours, due to the usage of optimal projection. It is also more advantageous in separating cross-correlated sources than the independence- and uncorrelation-based methods, as it does not employ any statistical information of the sources. Furthermore, the new method does not require the mixing matrix to be nonnegative. Simulation results demonstrate the superior performance of our method.

Remote centre-of-motion control algorithms of 6-RRCRR parallel robot assisted surgery system (PRAMiSS)

In this paper a 6-RRCRR parallel robot assisted minimally invasive surgery/microsurgery system (PRAMiSS) is introduced. Remote centre-of-motion (RCM) control algorithms of PRAMiSS suitable for minimally invasive surgery and microsurgery are also presented. The programmable RCM approach is implemented in order to achieve manipulation under the constraint of moving through the fixed penetration point. Having minimised the displacements of the mobile platform of the parallel micropositioning robot, the algorithms also apply orientation constraint to the instrument and prevent the tool tip to orient due to the robot movements during the manipulation. Experimental results are provided to verify accuracy and effectiveness of the proposed RCM control algorithms for minimally invasive surgery.

Kinematics analysis of 6-DOF parallel micro-manipulators with offset U-Joints : a case study

This paper analyses the kinematics of a special 6-DOF parallel micro-manipulator with offset RR-joint configuration. Kinematics equations are derived and numerical methodologies to solve the inverse and forward kinematics are presented. The inverse and forward kinematics of such robots compared with those of 6-UCU parallel robots are more complicated due to the existence of offsets between joints of RR-pairs. The characteristics of RR-pairs used in this manipulator are investigated and kinematics constraints of these offset U-joints are mathematically explained in order to find the best initial guesses for the numerical solution. Both inverse and forward kinematics of the case study 6-DOF parallel micro-manipulator are modelled and computational analyses are performed to numerically verify accuracy and effectiveness of the proposed methodologies.