The Modified Condensed Nearest Neighbour (MCNN) algorithm for prototype selection is order-independent, unlike the Condensed Nearest Neighbour (CNN) algorithm. Though MCNN gives better performance, the time requirement is much higher than for CNN. To mitigate this, we propose a distributed approach called Parallel MCNN (pMCNN) which cuts down the time drastically while maintaining good performance. We have proposed two incremental algorithms using MCNN to carry out prototype selection on large and streaming data. The results of these algorithms using MCNN and pMCNN have been compared with an existing algorithm for streaming data.
An adaptive fuzzy controller is designed for spark-ignited (SI) engines, under the constraint that the system's model is unknown. The control algorithm aims at satisfying the H∞ tracking performance criterion, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. After transforming the SI-engine model into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system's parameters. The nonlinear terms which appear in the control inputs are approximated with the use of neuro-fuzzy networks. It is shown that a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis it is proven that the proposed adaptive fuzzy control scheme results in H∞ tracking performance. The efficiency of the proposed adaptive fuzzy control scheme is checked through simulation experiments.
Eva Kurekova, Martin Halaj, Milada Omachelová and Ilja Martišovitš
Modern production machines employ complex kinematic structures that shall enhance their performance. As those machines are very sophisticated electro-mechanical structures, their design is time consuming and financially demanding. Therefore, designers search for new possibilities how to estimate future properties of the machine as early as in the design phase. The paper gives a brief introduction to the adoption of methodology of measurement uncertainties into the design of production machines. The adapted methodology enables to estimate the theoretical positioning accuracy of the machine end effector that is one of the important indicators of machine performance. Both serial and parallel kinematic structures are considered in the paper. Methodology and sample calculations of theoretical positioning accuracy are presented for serial kinematic structure (represented by advanced plasma cutting head) and parallel kinematic structure, represented by one specific design named Tricept.
The present article describes a novel phrasing model which can be used for segmenting sentences of unconstrained text into syntactically-defined phrases. This model is based on the notion of attraction and repulsion forces between adjacent words. Each of these forces is weighed appropriately by system parameters, the values of which are optimised via particle swarm optimisation. This approach is designed to be language-independent and is tested here for different languages.
The phrasing model’s performance is assessed per se, by calculating the segmentation accuracy against a golden segmentation. Operational testing also involves integrating the model to a phrase-based Machine Translation (MT) system and measuring the translation quality when the phrasing model is used to segment input text into phrases. Experiments show that the performance of this approach is comparable to other leading segmentation methods and that it exceeds that of baseline systems.
E. Sysoev, R. Kulikov, I. Vykhristyuk and Yu. Chugui
In scanning interferometry of longitudinal shift, an uncertainty of required phase shift performance leads to a measurement error. Such uncertainty can be caused by external factors (vibrations, air turbulence in measuring area etc.) as well as inaccuracy of the scanning system. The method for calculating the phase shift between interferograms, which allows reducing the measurement error, is proposed. The results of numerical and full scale experiments are presented.
Iterative Method and Dithering with Averaging used for Correction of ADC Error
Additive iterative method in combination with averaging of dithered samples is designed for self-correction of ADC linearity error in the paper. Iterative method is one of the automated error correction techniques. Dithering is a special tool for quantizer performance enhancement. Dither theory for Gaussian noise and averaging has been used for exhibition of method abilities in ADC characteristic improvement.
High Speed Optical Wavefront Sensing with Low Cost FPGAs
This paper outlines a study into deployment of a parallel processing scheme on an FPGA to meet the needs of high bandwidth processing in adaptive optics wavefront sensing. By exploiting a multi-stage pipeline approach we have significantly reduced the processing time needed to perform the wavefront sensing operation. The paper details the design, implementation, and performance testing results of the proposed FPGA-based wavefront sensing system.
Comparison of Minimum Detectable Concentration with the IUPAC Detection Limit
Detection capability is an important performance characteristic of a measurement process. It is characterized by ISO as minimum detectable value. Another characteristic, used in chemical measurements, was defined by IUPAC as the limit of detection. These and further closely related characteristics are compared and theoretically analysed. Directions for their use are given and exemplified using chemical trace analysis of lead.
S. Solis-Najera, F. Vazquez, R. Hernandez, O. Marrufo and A.O. Rodriguez
A surface radio frequency coil was developed for small animal image acquisition in a pre-clinical magnetic resonance imaging system at 7 T. A flexible coil composed of two circular loops was developed to closely cover the object to be imaged. Electromagnetic numerical simulations were performed to evaluate its performance before the coil construction. An analytical expression of the mutual inductance for the two circular loops as a function of the separation between them was derived and used to validate the simulations. The RF coil is composed of two circular loops with a 5 cm external diameter and was tuned to 300 MHz and 50 Ohms matched. The angle between the loops was varied and the Q factor was obtained from the S11 simulations for each angle. B1 homogeneity was also evaluated using the electromagnetic simulations. The coil prototype was designed and built considering the numerical simulation results. To show the feasibility of the coil and its performance, saline-solution phantom images were acquired. A correlation of the simulations and imaging experimental results was conducted showing a concordance of 0.88 for the B1 field. The best coil performance was obtained at the 90° aperture angle. A more realistic phantom was also built using a formaldehyde-fixed rat phantom for ex vivo imaging experiments. All images showed a good image quality revealing clearly defined anatomical details of an ex vivo rat.
Q. Liang, W. Wu, D. Zhang, B. Wei, W. Sun, Y. Wang and Y. Ge
Roughness, which can represent the trade-off between manufacturing cost and performance of mechanical components, is a critical predictor of cracks, corrosion and fatigue damage. In order to measure polished or super-finished surfaces, a novel touch probe based on three-component force sensor for characterizing and quantifying surface roughness is proposed by using silicon micromachining technology. The sensor design is based on a cross-beam structure, which ensures that the system possesses high sensitivity and low coupling. The results show that the proposed sensor possesses high sensitivity, low coupling error, and temperature compensation function. The proposed system can be used to investigate micromechanical structures with nanometer accuracy.