Discrete cosine transform generator for VLSI synthesis

A generator for the automated design of Discrete Cosine Transform (DCT) cores is presented. This can be used to rapidly create silicon circuits from a high level specification. These compare very favourably with existing designs. The DCT cores produced are scaleable in terms of point size as well as input/output and coefficient wordlengths. This provides a high degree of flexibility. An example, 8-point 1D DCT design, produced occupies less than 0.92 mm when implemented in a 0.35µ double level metal CMOS technology. This can be clocked at a rate of 100MHz.

Blown Jet Vortex Generator Control of a Separated Diffuser Flow

The application of blown jet vortex generators to control flow separation in a diffuser with an opening angle of 10° has been studied using the computational fluid dynamics (CFD) code Fluent 6™. Experimental data is available for the uncontrolled flow in the diffuser. The section of the duct upstream of the diffuser has a height H equal to 15 mm; its length and breadth are 101H and 41H respectively; the diffuser has an expansion ratio of 4.7:1. Fully developed flow is achieved upstream of the diffuser. Pipes of diameters equal to 1.5%, 2.5% and 5% of H were considered; pitch angle was constant at 45° and yaw angle was fixed at 60°; velocity ratio was varied from 1.7 to 8.0; both co-rotating and counter-rotating arrays were studied. The best results were obtained with a counter-rotating array of generators with a hole diameter of 5% of H and a velocity ratio of 3.7.

On the Condition Number Distribution of Complex Wishart Matrices

This paper investigates the distribution of the condition number of complex Wishart matrices. Two closely related measures are considered: the standard condition number (SCN) and the Demmel condition number (DCN), both of which have important applications in the context of multiple-input multipleoutput (MIMO) communication systems, as well as in various branches of mathematics. We first present a novel generic framework for the SCN distribution which accounts for both central and non-central Wishart matrices of arbitrary dimension. This result is a simple unified expression which involves only a single scalar integral, and therefore allows for fast and efficient computation. For the case of dual Wishart matrices, we derive new exact polynomial expressions for both the SCN and DCN distributions. We also formulate a new closed-form expression for the tail SCN distribution which applies for correlated central Wishart matrices of arbitrary dimension and demonstrates an interesting connection to the maximum eigenvalue moments of Wishart matrices of smaller dimension. Based on our analytical results, we gain valuable insights into the statistical behavior of the channel conditioning for various MIMO fading scenarios, such as uncorrelated/semi-correlated Rayleigh fading and Ricean fading. © 2010 IEEE.

Large-Scale Wind Generator Cascaded Tripping

Large scale wind farms are subject to tripping, as a consequence of turbine failure, over-sensitive protection, turbines not equipped with low-voltage ride through (LVRT), and reactive power compensation device defects which can lead to voltage rises. This paper considers pertinent issues which render tripping based on a study of LVRT and wind farm protection, with methods to avoid large scale wind generator tripping proposed. The results of LVRT field tests in Jiuquan, China in December 2012 show that the proposed approaches are effective. The paper also presents work which proposes an early warning system to forecast the risk of wind power tripping.

Modelling and Control of a Variable-Speed Switched Reluctance Generator based Wind Turbine

This paper studies the system modelling and control aspects of switched reluctance generator (SRG) based variable speed wind turbines. A control system is implemented to provide proper operation of the SRG as well as power tracking capabilities for varying wind speeds. The control system for the grid side inverter that will allow the SRG to properly generate power to the system is also presented. Studies are presented of both the SRG and inverter control systems capabilities during a balanced three-phase fault. The paper will demonstrate that the SRG based wind turbine presents a feasible variable wind speed solution with good fault response capabilities.

Inter-Area Power Oscillation Frequency Mode with Wind Turbine Generator in Irish Power System using PMU Data

Two case studies are presented in this paper to demonstrate the impact of different power system operation conditions on the power oscillation frequency modes in the Irish power system. A simplified 2 area equivalent of the Irish power system has been used in this paper, where area 1 represents the Republic of Ireland power system and area 2 represents the Northern Ireland power system.

The potential power oscillation frequency modes on the interconnector during different operation conditions have been analysed in this paper. The main objective of this paper is to analyse the influence of different operation conditions involving wind turbine generator (WTG) penetration on power oscillation frequency modes using phasor measurement unit (PMU) data.

Fast Fourier transform (FFT) analysis was performed to identify the frequency oscillation mode while correlation coefficient analysis was used to determine the source of the frequency oscillation. The results show that WTG, particularly fixed speed induction generation (FSIG), gives significant contribution to inter-area power oscillation frequency modes during high WTG operation.

A unique and robust single slice FPGA identification generator

In this paper, a new field-programmable gate array (FPGA) identification generator circuit is introduced based on physically unclonable function (PUF) technology. The new identification generator is able to convert flip-flop delay path variations to unique n-bit digital identifiers (IDs), while requiring only a single slice per ID bit by using 1-bit ID cells formed as hard-macros. An exemplary 128-bit identification generator is implemented on ten Xilinx Spartan-6 FPGA devices. Experimental results show an uniqueness of 48.52%, and reliability of 92.41% over a 25°C to 70°C temperature range and 10% fluctuation in supply voltage

In Vitro Release from Reverse Poloxamine/alpha-Cyclodextrin Matrices: Modelling and Comparison of Dissolution Profiles

Gels obtained by complexation of octablock star polyethylene oxide/polypropylene oxide copolymers (Tetronic 90R4) with -cyclodextrin (-CD) were evaluated as matrices for drug release. Both molecules are biocompatible so they can be potentially applied to drug delivery systems. Two different types of matrices of Tetronic 90R4 and -CD were evaluated: gels and tablets. These gels are capable to gelifying in situ and show sustained erosion kinetics in aqueous media. Tablets were prepared by freeze-drying and comprising the gels. Using these two different matrices, the release of two model molecules, L-tryptophan (Trp), and a protein, bovine serum albumin (BSA), was evaluated. The release profiles of these molecules from gels and tablets prove that they are suitable for sustained delivery. Mathematical models were applied to the release curves from tablets to elucidate the drug delivery mechanism. Good correlations were found for the fittings of the release curves to different equations. The results point that the release of Trp from different tablets is always governed by Fickian diffusion, whereas the release of BSA is governed by a combination of diffusion and tablet erosion. 

Discovering subgroups of patients from DNA copy number data using NMF on compacted matrices

In the study of complex genetic diseases, the identification of subgroups of patients sharing similar genetic characteristics represents a challenging task, for example, to improve treatment decision. One type of genetic lesion, frequently investigated in such disorders, is the change of the DNA copy number (CN) at specific genomic traits. Non-negative Matrix Factorization (NMF) is a standard technique to reduce the dimensionality of a data set and to cluster data samples, while keeping its most relevant information in meaningful components. Thus, it can be used to discover subgroups of patients from CN profiles. It is however computationally impractical for very high dimensional data, such as CN microarray data. Deciding the most suitable number of subgroups is also a challenging problem. The aim of this work is to derive a procedure to compact high dimensional data, in order to improve NMF applicability without compromising the quality of the clustering. This is particularly important for analyzing high-resolution microarray data. Many commonly used quality measures, as well as our own measures, are employed to decide the number of subgroups and to assess the quality of the results. Our measures are based on the idea of identifying robust subgroups, inspired by biologically/clinically relevance instead of simply aiming at well-separated clusters. We evaluate our procedure using four real independent data sets. In these data sets, our method was able to find accurate subgroups with individual molecular and clinical features and outperformed the standard NMF in terms of accuracy in the factorization fitness function. Hence, it can be useful for the discovery of subgroups of patients with similar CN profiles in the study of heterogeneous diseases.

Constructing random matrices to represent real ecosystems

Models of complex systems with n components typically have order n² parameters because each component can potentially interact with every other. When it is impractical to measure these parameters, one may choose random parameter values and study the emergent statistical properties at the system level. Many influential results in theoretical ecology have been derived from two key assumptions: that species interact with random partners at random intensities and that intraspecific competition is comparable between species. Under these assumptions, community dynamics can be described by a community matrix that is often amenable to mathematical analysis. We combine empirical data with mathematical theory to show that both of these assumptions lead to results that must be interpreted with caution. We examine 21 empirically derived community matrices constructed using three established, independent methods. The empirically derived systems are more stable by orders of magnitude than results from random matrices. This consistent disparity is not explained by existing results on predator-prey interactions. We investigate the key properties of empirical community matrices that distinguish them from random matrices. We show that network topology is less important than the relationship between a species’ trophic position within the food web and its interaction strengths. We identify key features of empirical networks that must be preserved if random matrix models are to capture the features of real ecosystems.

Ionic liquid reconstituted cellulose composites as solid support matrices with good transparency for biocatalytic reaction.

Disclosed are composites comprising regenerated cellulose, a first active substance, a second active substance, and a linker. Thus, microcryst. cellulose was dissolved in 1-butyl-3-methylimidazolium chloride using microwave pulse heating at 120-150°, cooled to 60° to form a super-cooled liq., 20% (based on cellulose) poly(L-lysine hydrobromide) was added therein, homogenized, cast onto a glass plate, the resulting film soaked in water for at least 24 h to leach residual from the film to give a reconstituted cellulose film, showing good transparency. [on SciFinder(R)]