BPP has subexponential time simulations unlessEXPTIME has publishable proofs

We show thatBPP can be simulated in subexponential time for infinitely many input lengths unless exponential time

Simulations of ionization in a hot cavity surface ion source

A new numerical Monte Carlo method based model of a hot cavity surface ionization ion source is presented in this paper. The model, intended to support the studies on ionization phenomena in a widely used class of ion sources, takes into account geometry of the ion source and extraction system, ionizer temperature and other features. The results of ion source efficiency calculations for various configurations of the extraction field are reviewed. The dominant role of the ionizer region near the extraction opening is described. Simulated dependences of ionization efficiency on the working parameters like ionizer length and temperature, ionization potential of the substance, and extraction voltage are discussed. A good agreement of the experimental data (e.g., influence of ionizer temperature, current-voltage curve) and the predictions of the model is found. It is also shown that the contribution to the ionization yield from impact of thermionic electrons accelerated by the extraction field may be significant, especially for the substances of small surface ionization coefficient. The simulation results are compared to the predictions of different theoretical models of the ion source--the obtained simulation data are in accordance both with a well-known Kirchner formula and the so called spherical ionizer model.     

Preferences in multi-objective evolutionary optimisation of electric motor speed control with hardware in the loop

This paper presents the design of a robust Pareto-optimal controller with the designer preference articulation for a Permanent Magnet Synchronous Motor (PMSM). An evolutionary multi-objective optimisation (EMOO) algorithm is used to tune the proportional integral (PI) speed regulator in the Direct Torque Control drive system.Approximation of the Pareto front with hardware in the loop (HiL) is chosen as an alternative to the time-consuming software simulation studies. Thanks to this approach problems of un-modelled plant dynamics are alleviated and additional manual tuning on-line is not required. The weak point of the HiL approach is caused by disruptive presence of noise which affects the performance of EMOO. This influence is strongly problem-dependent; therefore no generalized results have yet been presented in the literature. In this paper the robustness features of the proposed design approach are verified using the state-of-the-art multi-objective evolutionary Non-dominated Sorting Genetic Algorithm (NSGA-II; Deb, 2001 [1]).The on-line optimised motor drive speed controller is shown to be effective, possessing good dynamic characteristics, demonstrating applicability of the a priori preference articulation technique to the controller design. The final Pareto-optimal solution is selected according to the designer's preference articulation before the Pareto front is approximated by EMOO.     

Characterisation of the microstructure and thermal properties of Nd2Zr2O7 and Nd2Zr2O7/YSZ thermal barrier coatings

The microstructure of following thermal barrier coatings (TBC) was characterised in this paper: monolayer coatings Nd₂Zr₂O₇ and 8YSZ; a double ceramic layered (DCL) coating. Coatings were characterised by thicknesses that did not exceed 300 μm and porosities of approx. 5%. The chemical and phase composition analysis of the DCL layers revealed an external Nd₂Zr₂O₇ ceramic layer approx. 80 μm thick, a transitional zone approx. 120 μm thick and an internal 8YSZ layer 100 μm thick. For the case of the monolayer coating, the Nd₂Zr₂O₇ pyrochlore phase was the only one-phase component. The surface topography of both TBC systems was typical for plasma sprayed coatings, and compressive stress state had a value of approx. 5–10 MPa. Measurements of the thermal parameters, i.e., thermal diffusivity, point to considerably better insulative properties for both new types of layers when compared to the standard 8YSZ layers.     

Interactive Gene Clustering—A Case Study of Breast Cancer Microarray Data

We present a new approach to clustering and visualization of the DNA microarray gene expression data. We utilize the self-organizing map (SOM) framework for handling (dis)similarities between genes in terms of their expression characteristics. We rely on appropriately defined distances between ranked genes-attributes, also capable of handling missing values. As a case study, we consider breast cancer data and the gene ESR1, whose expression alterations, appearing for many of the tumor subtypes, have been already observed to be correlated with some other significant genes. Preliminary results positively verify applicability of our approach, although further development is definitely needed. They suggest that it may be very effective when used by the domain experts. The algorithmic toolkit is enriched with GUI enabling the users to interactively support the SOM optimization process. Its effectiveness is achieved by drag&drop techniques allowing for the cluster modification according to the expert knowledge or intuition.