An adaptive power-system stabiliser which cancels the negative damping torque of a synchronous generator

The paper presents a new criterion for designing a power-system stabiliser, which is that it should cancel the negative damping torque inherent in a synchronous generator and automatic voltage regulator. The method arises from analysis based on the properties of tensor invariance, but it is easily implemented, and leads to the design of an adaptive controller. Extensive computations and simulation have been performed, and laboratory tests have been conducted on a computer-controlled micromachine system. Results are presented illustrating the effectiveness of the adaptive stabiliser.

Invited paper Application of the least mean fourth (LMF) adaptive algorithm to signals associated with gaussian noise

This paper considers the applicability of the least mean fourth (LM F) power gradient adaptation criteria with 'advantage' for signals associated with gaussian noise, the associated noise power estimate not being known. The proposed method, as an adaptive spectral estimator, is found to provide superior performance than the least mean square (LMS) adaptation for the same (or even lower) speed of convergence for signals having sufficiently high signal-to-gaussian noise ratio. The results include comparison of the performance of the LMS-tapped delay line, LMF-tapped delay line, LMS-lattice and LMF-lattice algorithms, with the Burg's block data method as reference. The signals, like sinusoids with noise and stochastic signals like EEG, are considered in this study.

An Adaptive Scheme for Learning the Probability Threshold in Pattern Recognition

The statistical minimum risk pattern recognition problem, when the classification costs are random variables of unknown statistics, is considered. Using medical diagnosis as a possible application, the problem of learning the optimal decision scheme is studied for a two-class twoaction case, as a first step. This reduces to the problem of learning the optimum threshold (for taking appropriate action) on the a posteriori probability of one class. A recursive procedure for updating an estimate of the threshold is proposed. The estimation procedure does not require the knowledge of actual class labels of the sample patterns in the design set. The adaptive scheme of using the present threshold estimate for taking action on the next sample is shown to converge, in probability, to the optimum. The results of a computer simulation study of three learning schemes demonstrate the theoretically predictable salient features of the adaptive scheme.

Crystallographic and modelling studies on Mycobacterium tuberculosis RuvA: Additional role of RuvB-binding domain and inter species variability

RuvA, along with RuvB, is involved in branch migration of heteroduplex DNA in homologous recombination. The structures of three new crystal forms of RuvA from Mycobacterium tuberculosis (MtRuvA) have been determined. The RuvB-binding domain is cleaved off in one of them. Detailed models of the complexes of octameric RuvA from different species with the Holliday junction have also been constructed. A thorough examination of the structures presented here and those reported earlier brings to light the hitherto unappreciated role of the RuvB-binding domain in determining inter-domain orientation and oligomerization. These structures also permit an exploration of the interspecies variability of structural features such as oligomerization and the conformation of the loop that carries the acidic pin, in terms of amino acid substitutions. These models emphasize the additional role of the RuvB-binding domain in Holliday junction binding. This role along with its role in oligomerization could have important biological implications.

Spectral Sensing for Cognitive Radio: Estimation of Adaptive Frequency Hopping Signal

The issue of dynamic spectrum scene analysis in any cognitive radio network becomes extremely complex when low probability of intercept, spread spectrum systems are present in environment. The detection and estimation become more complex if frequency hopping spread spectrum is adaptive in nature. In this paper, we propose two phase approach for detection and estimation of frequency hoping signals. Polyphase filter bank has been proposed as the architecture of choice for detection phase to efficiently detect the presence of frequency hopping signal. Based on the modeling of frequency hopping signal it can be shown that parametric methods of line spectral analysis are well suited for estimation of frequency hopping signals if the issues of order estimation and time localization are resolved. An algorithm using line spectra parameter estimation and wavelet based transient detection has been proposed which resolves above issues in computationally efficient manner suitable for implementation in cognitive radio. The simulations show promising results proving that adaptive frequency hopping signals can be detected and demodulated in a non cooperative context, even at a very low signal to noise ratio in real time.

DNA structural variability as a factor in gene expression and evolution

Redundant DNA can buffer sequence dependent structural deviations from an ideal double helix. Buffering serves a mechanistic function by reducing extraneous conformational effects which could interfere with readout or which would impose energetic constraints on evolution. It also serves an evolutionary function by allowing for gradual variations in conformation-dependent regulation of gene expression. Such gradualism is critical for the rate of evolution. The buffer structure concept provides a new interpretation for repetitive DNA and for exons and introns.

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.

Single network adaptive critic design for power system stabilisers

The recently developed single network adaptive critic (SNAC) design has been used in this study to design a power system stabiliser (PSS) for enhancing the small-signal stability of power systems over a wide range of operating conditions. PSS design is formulated as a discrete non-linear quadratic regulator problem. SNAC is then used to solve the resulting discrete-time optimal control problem. SNAC uses only a single critic neural network instead of the action-critic dual network architecture of typical adaptive critic designs. SNAC eliminates the iterative training loops between the action and critic networks and greatly simplifies the training procedure. The performance of the proposed PSS has been tested on a single machine infinite bus test system for various system and loading conditions. The proposed stabiliser, which is relatively easier to synthesise, consistently outperformed stabilisers based on conventional lead-lag and linear quadratic regulator designs.

Variability of Indian summer monsoon rainfall in daily data from gauge and satellite

It has long been thought that tropical rainfall retrievals from satellites have large errors. Here we show, using a new daily 1 degree gridded rainfall data set based on about 1800 gauges from the India Meteorology Department (IMD), that modern satellite estimates are reasonably close to observed rainfall over the Indian monsoon region. Daily satellite rainfalls from the Global Precipitation Climatology Project (GPCP 1DD) and the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) are available since 1998. The high summer monsoon (June-September) rain over the Western Ghats and Himalayan foothills is captured in TMPA data. Away from hilly regions, the seasonal mean and intraseasonal variability of rainfall (averaged over regions of a few hundred kilometers linear dimension) from both satellite products are about 15% of observations. Satellite data generally underestimate both the mean and variability of rain, but the phase of intraseasonal variations is accurate. On synoptic timescales, TMPA gives reasonable depiction of the pattern and intensity of torrential rain from individual monsoon low-pressure systems and depressions. A pronounced biennial oscillation of seasonal total central India rain is seen in all three data sets, with GPCP 1DD being closest to IMD observations. The new satellite data are a promising resource for the study of tropical rainfall variability.

trans gene regulation in adaptive evolution: A genetic algorithm model

This is a continuation of earlier studies on the evolution of infinite populations of haploid genotypes within a genetic algorithm framework. We had previously explored the evolutionary consequences of the existence of indeterminate—“plastic”—loci, where a plastic locus had a finite probability in each generation of functioning (being switched “on”) or not functioning (being switched “off”). The relative probabilities of the two outcomes were assigned on a stochastic basis. The present paper examines what happens when the transition probabilities are biased by the presence of regulatory genes. We find that under certain conditions regulatory genes can improve the adaptation of the population and speed up the rate of evolution (on occasion at the cost of lowering the degree of adaptation). Also, the existence of regulatory loci potentiates selection in favour of plasticity. There is a synergistic effect of regulatory genes on plastic alleles: the frequency of such alleles increases when regulatory loci are present. Thus, phenotypic selection alone can be a potentiating factor in a favour of better adaptation.

X-ray studies on crystalline complexes involving amino acids and peptides. XXIII. Variability in ionization state, conformation and molecular aggregation in the complexes of succinic acid with DL- and L-lysine

Crystalline complexes of succinic acid with DL- and L-lysine have been prepared and analysed by X-ray diffraction. DL-Lysine complex: C6HIsN202 + 1 2- 1 ~C4H404 .~C4H604, Mr -- 264"2, PI, a = 5"506 (4), =8.070(2), c=14.089(2) A,, a=92.02(1), /3= 100"69 (3), y = 95"85 (3) ~>, Z = 2, Dx = 1"44 g cm -3, R = 0.059 for 2546 observed reflections. Form I of the e-lysine complex: C6HIsN20-, ~ .C4H504, Mr = 264.2, P1, a = 5" 125 (2), b = 8"087 (1), c = 8"689 (1) A,, a = 112.06 (1), /3 = 99.08 (2), y = 93"77(2) °, Z--l, D,,,=1"34(3), Dx=l"34gcm 3 R = 0.033 for 1475 observed reflections. Form II of + I 2- the e-lysine complex: C6H15N202 .,iC4H404 .- 1 I ") 4C4H604.4(C4HsO4""H'"CaH404)" , Mr = 264"2, P1, a = 10.143 (4), b = 10.256 (2), c = 12"916 (3) A,, a = 105.00 (2),/3 = 99-09 (3), y = 92"78 (3)::, Z = 4, Dm= 1"37(4), D,.= 1.38gcm 3, R=0.067 for 2809 observed reflections. The succinic acid molecules in the structures exhibit a variety of ionization states. Two of the lysine conformations found in the complexes have been observed for the first time in crystals containing lysine. Form II of the L-lysine complex is highly pseudosymmetric. In all the complexes, unlike molecules aggregate into separate alternating layers. The basic element of aggregation in the lysine layer in the complexes is an S2-type head-to-tail sequence. This element combines in different ways in the three structures. The basic element of aggre gation in the succinic acid layer in the complexes is a hydrogen-bonded ribbon. The ribbons are interconnected indirectly through amino groups in the lysine layer.

Effect of soil variability on the bearing capacity of clay and in slope stability problems

Site-specific geotechnical data are always random and variable in space. In the present study, a procedure for quantifying the variability in geotechnical characterization and design parameters is discussed using the site-specific cone tip resistance data (qc) obtained from static cone penetration test (SCPT). The parameters for the spatial variability modeling of geotechnical parameters i.e. (i) existing trend function in the in situ qc data; (ii) second moment statistics i.e. analysis of mean, variance, and auto-correlation structure of the soil strength and stiffness parameters; and (iii) inputs from the spatial correlation analysis, are utilized in the numerical modeling procedures using the finite difference numerical code FLAC 5.0. The influence of consideration of spatially variable soil parameters on the reliability-based geotechnical deign is studied for the two cases i.e. (a) bearing capacity analysis of a shallow foundation resting on a clayey soil, and (b) analysis of stability and deformation pattern of a cohesive-frictional soil slope. The study highlights the procedure for conducting a site-specific study using field test data such as SCPT in geotechnical analysis and demonstrates that a few additional computations involving soil variability provide a better insight into the role of variability in designs.

A Control Strategy for Reference Wave Adaptive Current Generation

Speed control of ac motors requires variable frequency, variable current, or variable voltage supply. Variable frequency supply can be obtained directly from a fixed frequency supply by using a frequency converter or from a dc source using inverters. In this paper a control technique for reference wave adaptive-current generation by modulating the inverter voltage is explained. Extension of this technique for three-phase induction-motor speed control is briefly explained. The oscillograms of the current waveforms obtained from the experimental setup are also shown.

Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling

The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.