First break refraction event picking using fuzzy logic systems

First break picking is a pattern recognition problem in seismic signal processing, one that requires much human effort and is difficult to automate. The authors' goal is to reduce the manual effort in the picking process and accurately perform the picking. Feedforward neural network first break pickers have been developed using backpropagation training algorithms applied either to an encoded version of the raw data or to derived seismic attributes which are extracted from the raw data. The authors summarize a study in which they applied a backpropagation fuzzy logic system (BPFLS) to first break picking. The authors use derived seismic attributes as features, and take lateral variations into account by using the distance to a piecewise linear guiding function as a new feature. Experimental results indicate that the BPFLS achieves about the same picking accuracy as a feedforward neural network that is also trained using a backpropagation algorithm; however, the BPFLS is trained in a much shorter time, because there is a systematic way in which the initial parameters of the BPFLS can be chosen, versus the random way in which the weights of the neural network are chosen     

Biochemical basis for increased susceptibility to Cidofovir of herpes simplex viruses with altered or deficient thymidine kinase activity

It has been observed that herpes simplex virus mutants with deficient or altered thymidine kinase activity are more susceptible to Cidofovir (CDV; 1-[(S)-3-hydroxy-2-(phosphonomethoxy)propyl]cytosine dihydrate) in tissue culture than are the parental strains. During infection of cells, the elevation of the dCTP pool by thymidine kinase mutant viruses is less than that induced by the wild-type virus. The competition between CDV diphosphate and dCTP at the viral polymerase is therefore changed in favor of CDV diphosphate, enhancing its activity.     

The constrained total least squares technique and its applicationsto harmonic superresolution

The constrained total least squares (CTLS) method is a natural extension of TLS to the case when the noise components of the coefficients are algebraically related. The CTLS technique is developed, and some of its applications to superresolution harmonic analysis are presented. The CTLS problem is reduced to an unconstrained minimization problem over a small set of variables. A perturbation analysis of the CTLS solution is derived, and from it the root mean-square error (RMSE) of the CTLS solution, which is valid for small noise levels, is obtained in closed form. The complex version of the Newton method is derived and applied to determine the CTLS solution. It is also shown that the CTLS problem is equivalent to a constrained parameter maximum-likelihood problem. The CTLS technique is applied to estimate the frequencies of sinusoids in white noise and the angle of arrival of narrowband wavefronts at a linear uniform array. In both cases the CTLS method shows superior or similar accuracy to other advanced techniques     

Outdoor attractancy of males ofMatsucoccus josephi (Homoptera: Matsucoccidae) andElatophilus hebraicus (Hemiptera: Anthocoridae) to synthetic female sex pheromone ofMatsucoccus josephi

The active component of the sex pheromone ofMatsucoccus josephi is (2E,6E,8E)-5,7-dimethyl-2,6,8-decatrien-4-one; the chemical is also a powerful kairomone of adult males and females of the bugElatophilus hebraicus the principal predator ofM. josephi. The presence of theZ isomer (2E,6Z,8E)-5,7-dimethyl-2,6,8-decatrien-4-one does not interfere with the attractancy of the activeE component forM. josephi males or the bug. Our results show a clear dose-response between trap catch ofM. josephi males andE. hebraicus. Conversely, increasing amounts of theZ isomer in the mixture did not affect the attraction of the scale insect males or the bug. The catch ofM. josephi males did not differ significantly among traps of different color, and was significantly higher with traps attached to the tree trunk than those suspended between trees. Comparison of the catch ofM. josephi among the three forests and between pine species suggests that the level of infestation ofPinus halepepsis andPinus brutia ssp.brutia is similar, despite the fact that the latter pine is resistant to the scale insect. Both sexes ofE. hebraicus were trapped in much lower numbers at the more infested sites. This may be related to interference with the activity ofE. hebraicus due to deterioration and drying of parts of the tree crowns and heavy colonization by generalist predators in injured trees.     

Using artificial neural networks to detect unknown computer worms

Detecting computer worms is a highly challenging task. We present a new approach that uses artificial neural networks (ANN) to detect the presence of computer worms based on measurements of computer behavior. We compare ANN to three other classification methods and show the advantages of ANN for detection of known worms. We then proceed to evaluate ANN’s ability to detect the presence of an unknown worm. As the measurement of a large number of system features may require significant computational resources, we evaluate three feature selection techniques. We show that, using only five features, one can detect an unknown worm with an average accuracy of 90%. We use a causal index analysis of our trained ANN to identify rules that explain the relationships between the selected features and the identity of each worm. Finally, we discuss the possible application of our approach to host-based intrusion detection systems.     

The hysteretic Hopfield neural network

A new neuron activation function based on a property found in physical systems-hysteresis-is proposed. We incorporate this neuron activation in a fully connected dynamical system to form the hysteretic Hopfield neural network (HHNN). We then present an analog implementation of this architecture and its associated dynamical equation and energy function. We proceed to prove Lyapunov stability for this new model, and then solve a combinatorial optimization problem (i.e., the N-queen problem) using this network. We demonstrate the advantages of hysteresis by showing increased frequency of convergence to a solution, when the parameters associated with the activation function are varied.     

The effects of VIP on intestinal motility: study on ex vivo perfused isolated canine jejunal loops

The effects of VIP on intestinal motility were studied on isolated canine jejunal loops ex vivo perfused at normothermia, under pulsatile flow with heparinized, oxygenated and nonrecirculated canine whole blood, by means of an intraluminal balloon. VIP was administered intraarterially either by 1 min injections or by long-time infusions. The results showed that for arterial concentrations of the polypeptide ranging between 25 pg/ml and 300-500 pg/ml a fast but short-lasting relaxant effect was observed. For higher concentrations VIP usually produced a biphasic response: The relaxant effect is followed by an increase of the basal muscular tone often accompanied, for concentrations higher than about 25 ng/ml, by a marked and transient increase in amplitude of the intestinal rhythmic contractions. During long-time infusions a biphasic response was also observed but both effects were of short duration. A cholingeric origin of the secondary contracting phase was expected but could not be demonstrated because, at blood concentrations at which atropine affected the biphasic response, not only was the contractile effect abolished but also the initial relaxing phase. It is suggested that the secondary contraction may be a "rebound excitation" of myogenic nature or a result of noncholingeric excitatory fiber stimulations. The short-lasting relaxant effect observed under the present experimental conditions, even during long-time infusion of the polypeptide, fails to argue for an important physiological role of VIP as an hormonal inhibitor of intestinal motility. The biphasic response, however, might have a physiological significance in so far as the aboral propulsion of the intestinal content requires a muscular inhibition which rapidly changes to contraction.     

Effect of near-critical swirl on the Burke-Schumann reaction sheet

The influence of swirl on the shape of the Burke-Schumann reaction sheet in a straight cylindrical pipe is investigated by asymptotic and numerical means. Attention is confined to swirl levels that are near the critical value at which vortex breakdown occurs. A high-Reynolds-number, laminar, isothermal, low-Mach-number reacting flow is considered. An asymptotic analysis is developed to study the nonlinear interaction between near-critical swirl and mixture fraction distribution within the flow. It is first shown that leading-order perturbation of the velocity field from the columnar state, generated by the interaction of near-critical swirl and low viscosity, can be described by a nonlinear reduced-order model. This flow perturbation is computed, and then employed to determine the correction to the classical Burke-Schumann solution. Under lean conditions of reaction the reaction sheet becomes shorter and more compact as swirl is increased. For rich conditions of reaction, increasing swirl first causes the reaction-sheet length to decrease, and then increase after vortex breakdown has appeared. Numerical simulations of the flow and reaction-zone shape are substantiated by, and supplement, the asymptotic results.     

Fuzzy basis functions, universal approximation, and orthogonalleast-squares learning

Fuzzy systems are represented as series expansions of fuzzy basis functions which are algebraic superpositions of fuzzy membership functions. Using the Stone-Weierstrass theorem, it is proved that linear combinations of the fuzzy basis functions are capable of uniformly approximating any real continuous function on a compact set to arbitrary accuracy. Based on the fuzzy basis function representations, an orthogonal least-squares (OLS) learning algorithm is developed for designing fuzzy systems based on given input-output pairs; then, the OLS algorithm is used to select significant fuzzy basis functions which are used to construct the final fuzzy system. The fuzzy basis function expansion is used to approximate a controller for the nonlinear ball and beam system, and the simulation results show that the control performance is improved by incorporating some common-sense fuzzy control rules.     

On high-speed computing with a programmable linear array

It has been observed by many researchers that systolic arrays are very suitable for certain high-speed computations. Using a formal methodology, we present a design for a single simple programmable linear systolic array capable of solving large numbers of problems drawn from a variety of applications. The methodology is applicable to problems solvable by sequential algorithms that can be specified as nested for-loops of arbitrary depth. The algorithms of this form that can be computed on the array presented in this paper include 25 algorithms dealing with signal and image processing, algebraic computations, matrix arithmetic, pattern matching, database operations, sorting, and transitive closure. Assuming bounded I/O, for 18 of those algorithms the time and storage complexities are optimal, and therefore no improvement can be expected by using dedicated special-purpose linear systolic arrays designed for individual algorithms. We also describe another design which, using a sufficient large local memory and allowing data to be preloaded and unloaded, has an optimal processor/time product.An earlier version of this paper was presented at Supercomputing '88.This work was partially supported by ONR under the contract N00014-85-K-0046 and by NSF under Grant Number CCR-8906949.