New approach to improved detection and tracking performance in track-while-scan radars. Part 3: Performance prediction, optimisation and testing

The paper presents, in three parts, a new approach to improve the detection and tracking performance of a track-while-scan radar. Part 1 presents a review of the current status of the subject. Part 2 details the new approach. It shows how a priori information provided by the tracker can be used to improve detection. It also presents a new multitarget tracking algorithm. In the present Part, analytical derivations are presented for assessing, a priori, the performance of the TWS radar system. True track initiation, false track initiation, true track continuation and false track deletion characteristics have been studied. It indicates how the various thresholds can be chosen by the designer to optimise performance. Simulation results are also presented.

Electrode kinetics of a nickel/cadmium cell and failure-mode prediction. Estimation of equivalent resistance of an internal short

A quantitative expression has been obtained for the equivalent resistance of an internal short in rechargeable cells under constant voltage charging.

Analysis of proteins with the `hot dog' fold: Prediction of function and identification of catalytic residues of hypothetical proteins

Background: The hot dog fold has been found in more than sixty proteins since the first report of its existence about a decade ago. The fold appears to have a strong association with fatty acid biosynthesis, its regulation and metabolism, as the proteins with this fold are predominantly coenzyme A-binding enzymes with a variety of substrates located at their active sites. Results: We have analyzed the structural features and sequences of proteins having the hot dog fold. This study reveals that though the basic architecture of the fold is well conserved in these proteins, significant differences exist in their sequence, nature of substrate and oligomerization. Segments with certain conserved sequence motifs seem to play crucial structural and functional roles in various classes of these proteins. Conclusion: The analysis led to predictions regarding the functional classification and identification of possible catalytic residues of a number of hot dog fold-containing hypothetical proteins whose structures were determined in high throughput structural genomics projects.

Prediction of Compressibility of Overconsolidated Uncemented Soils

Overconsolidated soils exhibit a bilinear e-log p relationship. During virgin compression, microstructural units form larger stable groups, thereby reducing the operating specific surface and, in turn, net osmotic repulsive forces in the soil. The rebound portion of the e-log p curve is consequently flatter. The generalized relationship for compressibility of uncemented soils in the overconsolidated state has been developed in the form of e/eL = 1.122 = 0.188 log pc - 0.0463 log p in which e/eL is the generalized soil state parameter, pc is the preconsolidation pressure in kPa, p is the effective overburden pressure in kPa, e is the in situ void ratio, and eL is the void ratio corresponding to the liquid limit water content (wLG). This relationship can be usefully employed to predict both the preconsolidation pressure and compressibility responses of overconsolidated uncemented soils.

Prediction of Breakdown Voltages of Binary Gas Mixtures in Uniform Electric Fields

A simple equation to predict the breakdown voltages for binary mixtures (Vmix) of electronegative gases (SF6, CCl2F2) and buffer gases (N2, N2O, CO2, air) under uniform electric field has been proposed. Values of Vmix evaluated using this equation for mixtures of SF6-N2, SF6-air, SF6-N2O, SF6-CO2 and CCl2F2-N2 over a wide range of pd show an excellent agreement with the experimentally measured data available in the literature.

Prediction of bubble growth rates and departure volumes in nucleate boiling at isolated sites

A model has been developed to predict heat transfer rates and sizes of bubbles generated during nucleate pool boiling. This model assumes conduction and a natural convective heat transfer mechanism through the liquid layer under the bubble and transient conduction from the bulk liquid. The temperature of the bulk liquid in the vicinity of the bubble is obtained by assuming a turbulent natural convection process from the hot plate to the liquid bulk. The shape of the bubble is obtained by equilibrium analysis. The bubble departure condition is predicted by a force balance equation. Good agreement has been found between the bubble radii predicted by the present theory and the ones obtained experimentally.

R-parameter: A local truncation error based adaptive framework for finite volume compressible flow solvers

A residual-based strategy to estimate the local truncation error in a finite volume framework for steady compressible flows is proposed. This estimator, referred to as the -parameter, is derived from the imbalance arising from the use of an exact operator on the numerical solution for conservation laws. The behaviour of the residual estimator for linear and non-linear hyperbolic problems is systematically analysed. The relationship of the residual to the global error is also studied. The -parameter is used to derive a target length scale and consequently devise a suitable criterion for refinement/derefinement. This strategy, devoid of any user-defined parameters, is validated using two standard test cases involving smooth flows. A hybrid adaptive strategy based on both the error indicators and the -parameter, for flows involving shocks is also developed. Numerical studies on several compressible flow cases show that the adaptive algorithm performs excellently well in both two and three dimensions.

Prediction of frequency and amplitude of foundations at resonance

This note presents the statistical analysis carried out on some of the available experimental results to predict the resonant frequency and maximum displacement amplitude of a machine foundation – soil system under vertical vibration as a function of the size and weight of the foundation and of the excitation level. A total of 442 experimental results of Fry, Novak, and Raman have been analysed using nonlinear regression analysis. The results obtained compared well with predictions obtained from the popular theoretical models, and the coefficient of correlation obtained from the analysis was satisfactory in most of the cases.

Error correction in nonbinary words

A simple error detecting and correcting procedure is described for nonbinary symbol words; here, the error position is located using the Hamming method and the correct symbol is substituted using a modulo-check procedure.

Prediction of Intrinsic kinetics in diffusion disguised immobilized enzyme systems

When immobilized enzyme kinetics are disguised by inter- and intraparticle diffusion effects, an approximate mathematical procedure is indicated whereby experimental data obtained in the limiting ranges of first- and zeroth-order Michaelis-Menten kinetics could be used for the prediction of the kinetic constants.

Prediction of protein-protein interactions between Helicobacter pylori and a human host

A lack of information on protein-protein interactions at the host-pathogen interface is impeding the understanding of the pathogenesis process. A recently developed, homology search-based method to predict protein-protein interactions is applied to the gastric pathogen, Helicobacter pylori to predict the interactions between proteins of H. pylori and human proteins in vitro. Many of the predicted interactions could potentially occur between the pathogen and its human host during pathogenesis as we focused mainly on the H. pylori proteins that have a transmembrane region or are encoded in the pathogenic island and those which are known to be secreted into the human host. By applying the homology search approach to protein-protein interaction databases DIP and iPfam, we could predict in vitro interactions for a total of 623 H. pylori proteins with 6559 human proteins. The predicted interactions include 549 hypothetical proteins of as yet unknown function encoded in the H. pylori genome and 13 experimentally verified secreted proteins. We have recognized 833 interactions involving the extracellular domains of transmembrane proteins of H. pylori. Structural analysis of some of the examples reveals that the interaction predicted by us is consistent with the structural compatibility of binding partners. Examples of interactions with discernible biological relevance are discussed.

Relative stability of DNA as a generic criterion for promoter prediction: whole genome annotation of microbial genomes with varying nucleotide base composition

The rapid increase in genome sequence information has necessitated the annotation of their functional elements, particularly those occurring in the non-coding regions, in the genomic context. Promoter region is the key regulatory region, which enables the gene to be transcribed or repressed, but it is difficult to determine experimentally. Hence an in silico identification of promoters is crucial in order to guide experimental work and to pin point the key region that controls the transcription initiation of a gene. In this analysis, we demonstrate that while the promoter regions are in general less stable than the flanking regions, their average free energy varies depending on the GC composition of the flanking genomic sequence. We have therefore obtained a set of free energy threshold values, for genomic DNA with varying GC content and used them as generic criteria for predicting promoter regions in several microbial genomes, using an in-house developed tool `PromPredict'. On applying it to predict promoter regions corresponding to the 1144 and 612 experimentally validated TSSs in E. coli (50.8% GC) and B. subtilis (43.5% GC) sensitivity of 99% and 95% and precision values of 58% and 60%, respectively, were achieved. For the limited data set of 81 TSSs available for M. tuberculosis (65.6% GC) a sensitivity of 100% and precision of 49% was obtained.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.