On generating optimal signal probabilities for random tests: A genetic approach

Genetic Algorithms are robust search and optimization techniques. A Genetic Algorithm based approach for determining the optimal input distributions for generating random test vectors is proposed in the paper. A cost function based on the COP testability measure for determining the efficacy of the input distributions is discussed, A brief overview of Genetic Algorithms (GAs) and the specific details of our implementation are described. Experimental results based on ISCAS-85 benchmark circuits are presented. The performance pf our GA-based approach is compared with previous results. While the GA generates more efficient input distributions than the previous methods which are based on gradient descent search, the overheads of the GA in computing the input distributions are larger. To account for the relatively quick convergence of the gradient descent methods, we analyze the landscape of the COP-based cost function. We prove that the cost function is unimodal in the search space. This feature makes the cost function amenable to optimization by gradient-descent techniques as compared to random search methods such as Genetic Algorithms.

Spatial distribution of oil in groundnut and sunflower seeds by nuclear magnetic resonance imaging

The nuclear magnetic resonance imaging technique has been used to obtain images of different transverse and vertical sections in groundnut and sunflower seeds. Separate images have been obtained for oil and water components in the seeds. The spatial distribution of oil and water inside the seed has been obtained from the detailed analysis of the images. In the immature groundnut seeds obtained commercially, complementary oil and water distributions have been observed. Attempts have been made to explain these results.

Seyfert Galaxies: Nuclear Radio Structure And Unification

A radio study of a carefully selected sample of 20 Seyfert galaxies that are matched in orientation-independent parameters, which are measures of intrinsic active galactic nucleus power and host galaxy properties, is presented to test the predictions of the unified scheme hypothesis. Our sample sources have core flux densities greater than 8 mJy at 5 GHz on arcsec scales due to the feasibility requirements. These simultaneous parsec-scale and kiloparsec-scale radio observations reveal (1) that Seyfert 1 and Seyfert 2 galaxies have an equal tendency to show compact radio structures on milliarcsecond scales, (2) the distributions of parsec-scale and kiloparsec-scale radio luminosities are similar for both Seyfert 1 and Seyfert 2 galaxies, (3) there is no evidence for relativistic beaming in Seyfert galaxies, (4) similar distributions of source spectral indices in spite of the fact that Seyferts show nuclear radio flux density variations, and (5) the distributions of the projected linear size for Seyfert 1 and Seyfert 2 galaxies are not significantly different as would be expected in the unified scheme. The latter could be mainly due to a relatively large spread in the intrinsic sizes. We also find that a starburst alone cannot power these radio sources. Finally, an analysis of the kiloparsec-scale radio properties of the CfA Seyfert galaxy sample shows results consistent with the predictions of the unified scheme.

Dynamic Behavior of Poly(2-vinylpyridine) in Solution Studied by 13C Nuclear Magnetic Relaxation

Abstract: The dynamics of poly(2-vinylpyridine) in chloroform solution has been examined by C-13 spin-lattice relaxation time and NOE measurements as a function of temperature. The experiments were performed at 50.3 and 100.6 MHz. The backbone carbon relaxation data have been analyzed in terms of six motional models. Among these models, the models which consider conformational transitions and bond librations for the backbone were found to be more successful. Pyridyl ring motion has been modeled as a restricted rotation with the rotational amplitude varying with temperature. The activation energy parameters obtained from the relaxation data of the pyridyl ring carbon have been compared with the energy barrier for ring rotation estimated from conformational energy calculations using the AM1 semiempirical quantum chemical method. The results of the conformational energy calculations support the description of pyridyl ring motion as a restricted rotation.

Reinforcement Learning With Function Approximation for Traffic Signal Control

We propose, for the first time, a reinforcement learning (RL) algorithm with function approximation for traffic signal control. Our algorithm incorporates state-action features and is easily implementable in high-dimensional settings. Prior work, e. g., the work of Abdulhai et al., on the application of RL to traffic signal control requires full-state representations and cannot be implemented, even in moderate-sized road networks, because the computational complexity exponentially grows in the numbers of lanes and junctions. We tackle this problem of the curse of dimensionality by effectively using feature-based state representations that use a broad characterization of the level of congestion as low, medium, or high. One advantage of our algorithm is that, unlike prior work based on RL, it does not require precise information on queue lengths and elapsed times at each lane but instead works with the aforementioned described features. The number of features that our algorithm requires is linear to the number of signaled lanes, thereby leading to several orders of magnitude reduction in the computational complexity. We perform implementations of our algorithm on various settings and show performance comparisons with other algorithms in the literature, including the works of Abdulhai et al. and Cools et al., as well as the fixed-timing and the longest queue algorithms. For comparison, we also develop an RL algorithm that uses full-state representation and incorporates prioritization of traffic, unlike the work of Abdulhai et al. We observe that our algorithm outperforms all the other algorithms on all the road network settings that we consider.

Signal compression through spatial frequency-based motion estimation

The interest in low bit rate video coding has increased considerably. Despite rapid progress in storage density and digital communication system performance, demand for data-transmission bandwidth and storage capacity continue to exceed the capabilities of available technologies. The growth of data-intensive digital audio, video applications and the increased use of bandwidth-limited media such as video conferencing and full motion video have not only sustained the need for efficient ways to encode analog signals, but made signal compression central to digital communication and data-storage technology. In this paper we explore techniques for compression of image sequences in a manner that optimizes the results for the human receiver. We propose a new motion estimator using two novel block match algorithms which are based on human perception. Simulations with image sequences have shown an improved bit rate while maintaining ''image quality'' when compared to conventional motion estimation techniques using the MAD block match criteria.

Distributed intrusion detection in the presence of correlated sensor readings: Signal-space and communication-complexity view-point

The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space view-point is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces f(s) and f(g) and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating f(s) and f(g) is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication-complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. Extensions to the multi-party case is straightforward and is briefly discussed. The average case CC of the relevant greaterthan (CT) function is characterized within two bits. Under the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm. 2010 Elsevier B.V. All rights reserved.

The steady state nuclear Overhauser effect revisited

The steady state of a two spin system coupled to an isotropic environment and to each other through a dipolar interaction and under irradiation by a monochromatic, circularly polarized radio frequency field is determined ab initio using thermodynamic arguments. This steady state is used to describe the well known nuclear Overhauser effect in liquids. The steady state is also derived from the Solomon-Bloch set of equations used to describe the driven spin. It is shown that in the limit of weak driving, the two solutions coincide. (C) 1999 American Institute of Physics. [S0021-9606(99)71210-9].

GNSS Signal Detection Under Noise Uncertainty

High sensitivity detection techniques are required for indoor navigation using Global Navigation Satellite System (GNSS) receivers, and typically, a combination of coherent and non- coherent integration is used as the test statistic for detection. The coherent integration exploits the deterministic part of the signal and is limited due to the residual frequency error, navigation data bits and user dynamics, which are not known apriori. So, non- coherent integration, which involves squaring of the coherent integration output, is used to improve the detection sensitivity. Due to this squaring, it is robust against the artifacts introduced due to data bits and/or frequency error. However, it is susceptible to uncertainty in the noise variance, and this can lead to fundamental sensitivity limits in detecting weak signals. In this work, the performance of the conventional non-coherent integration-based GNSS signal detection is studied in the presence of noise uncertainty. It is shown that the performance of the current state of the art GNSS receivers is close to the theoretical SNR limit for reliable detection at moderate levels of noise uncertainty. Alternate robust post-coherent detectors are also analyzed, and are shown to alleviate the noise uncertainty problem. Monte-Carlo simulations are used to confirm the theoretical predictions.

Developments in quantum information processing by nuclear magnetic resonance: Use of quadrupolar and dipolar couplings

Use of dipolar and quadrupolar couplings for quantum information processing (QIP) by nuclear magnetic resonance (NMR) is described. In these cases, instead of the individual spins being qubits, the 2(n) energy levels of the spin-system can be treated as an n-qubit system. It is demonstrated that QIP in such systems can be carried out using transition-selective pulses, in (CHCN)-C-3, (CH3CN)-C-13, Li-7 (I = 3/2) and Cs-133 (I = 7/2), oriented in liquid crystals yielding 2 and 3 qubit systems. Creation of pseudopure states, implementation of logic gates and arithmetic operations (half-adder and subtractor) have been carried out in these systems using transition-selective pulses.

Transformation in heterokaryons of Neurospora crassa is nuclear rather than cellular phenomenon

In Neurospora crassa, multinucleate macroconidia are used for genetic transformation. The barrier for such a transformation can be either at the cell membrane level or at the nuclear membrane level. For assessment of these possibilities, a forced heterokaryon (containing two genetically marked nuclei and auxotrophic for histidine) of Neurospora crassa was transformed with a plasmid containing his-3(+) gene. The transformants, which could grow without histidine supplementation, were then resolved into component homokaryons to determine into which nucleus or nuclei the plasmid had entered. Our results suggest that the barrier for transformation in Neurospora crassa is at the nuclear level, not at the cell membrane level. In a heterokaryon containing two genetically distinct nuclei, plasmid DNA integrated into only one of the nuclear types at any instance, but never into both nuclear types. Thus, in Neurospora crassa, the competent nucleus is essential for the transformation event to take place, and at a given time only one type of nucleus is competent to take up the exogenous DNA. Genomic Southern analysis showed that the transformants harbor both ectopic and homologous integrations of the plasmid DNA. The type and number of integrations were reflected at the post-translational level, since the specific activity of histidinol dehydrogenase (the translation product of his-3+ gene) was variable among several transformants and always less than the level of the wild type.