Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Two-Stage Transmitter Precoding Based on Data-Driven Code Hopping and Partial Zero Forcing Beamforming for MC-DCMA Communications

This paper proposes a hybrid transmission technique based on adaptive code-to-user allocation and linear precoding for the downlink of phase shift keying (PSK) based multi-carrier code division multiple access (MC-CDMA) systems. The proposed scheme is based on the separation of the instantaneous multiple access interference (MAI) into constructive and destructive components taking into account the dependency on both the channel variation and the instantaneous symbol values of the active users. The first stage of the proposed technique is to adaptively distribute the available spreading sequences to the users on a symbol-by-symbol basis in the form of codehopping with the objective to steer the users' instantaneous crosscorrelations to yield a favourable constructive to destructive MAI ratio. The second stage is to employ a partial transmitter based zero forcing (ZF) scheme specifically designed for the exploitation of constructive MAI. The partial ZF processing decorrelates destructive interferers, while users that interfere constructively remain correlated. This results in a signal to interference-plus-noise ratio (SINR) enhancement without the need for additional power-per-user investment. It will be shown in the results section that significant bit error rate (BER) performance benefits can be achieved with this technique.

Archiving Qualitative Data in the Context of a Society Coming out of Conflict: Some Lessons from Northern Ireland.

ARK (‘Access Research Knowledge’) was set up with a single goal: to make social science information on Northern Ireland available to the widest possible audience. The most well-known and widely used part of the ARK resource is CAIN (Conflict Archive on the INternet), which is one of the largest on-line collections of source material and information and about the Northern Ireland conflict. The compilation of CAIN's new Remembering: Victims, Survivors and Commemoration section raised issues related to the sensitivity of the material, as it feeds into the fundamental debate on the legacy of the Northern Ireland conflict. It also fundamentally raises the question to what extent archiving is a neutral or political activity and necessitates a discourse on responsibility and ethics among social researchers. Experiences from the establishment of the Northern Ireland Qualitative Archive (NIQA) shed light on future possibilities with regard to qualitative archives on the Northern Ireland conflict.

Extracting a more realistic pseudopotential for aluminum, lead, niobium and tantalum from superconductor electron tunnelling spectroscopy data

Electron tunnelling spectroscopy, developed to extract superconductive metals the electron-phonon spectral density, $\alpha^2F(\nu)$, is found to be a powerful tool also for extracting a more realistic pseudopotential from such metals. The pseudopotential so extracted has a range of surprising but physically reasonable properties and regenerates $\alpha^2F(\nu)$ accurately. Free from most of its long-standing uncertainties, thie pseudopotential may be useful in a number of active fields.

Networks for systems biology: conceptual connection of data and function

The purpose of this study is to survey the use of networks and network-based methods in systems biology. This study starts with an introduction to graph theory and basic measures allowing to quantify structural properties of networks. Then, the authors present important network classes and gene networks as well as methods for their analysis. In the last part of this study, the authors review approaches that aim at analysing the functional organisation of gene networks and the use of networks in medicine. In addition to this, the authors advocate networks as a systematic approach to general problems in systems biology, because networks are capable of assuming multiple roles that are very beneficial connecting experimental data with a functional interpretation in biological terms.

Protection Assessment using Reduced Power System Fault Data

Wavelet transforms provide basis functions for time-frequency analysis and have properties that are particularly useful for the compression of analogue point on wave transient and disturbance power system signals. This paper evaluates the compression properties of the discrete wavelet transform using actual power system data. The results presented in the paper indicate that reduction ratios up to 10:1 with acceptable distortion are achievable. The paper discusses the application of the reduction method for expedient fault analysis and protection assessment.