An Experimental Investigation of the Effect of Flange Angle on Radiation Patterns of V-Slot Waveguide Antenna

Results of exhaustive study of the effect of metallic flanges on H-plane radiation characteristics of V-slot waveguide antenna are presented . It has been established that the beam can be sharpened or broadened by varying the flange angle . The adjustment of the flange angle and flange width would further improve the radiation pattern , yielding optimum efficiency from the flanged system

AN ARTIFICIAL NEURAL NETWORK FOR SONAR TARGET DETECTION

Neural Network has emerged as the topic of the day. The spectrum of its application is as wide as from ECG noise filtering to seismic data analysis and from elementary particle detection to electronic music composition. The focal point of the proposed work is an application of a massively parallel connectionist model network for detection of a sonar target. This task is segmented into: (i) generation of training patterns from sea noise that contains radiated noise of a target, for teaching the network;(ii) selection of suitable network topology and learning algorithm and (iii) training of the network and its subsequent testing where the network detects, in unknown patterns applied to it, the presence of the features it has already learned in. A three-layer perceptron using backpropagation learning is initially subjected to a recursive training with example patterns (derived from sea ambient noise with and without the radiated noise of a target). On every presentation, the error in the output of the network is propagated back and the weights and the bias associated with each neuron in the network are modified in proportion to this error measure. During this iterative process, the network converges and extracts the target features which get encoded into its generalized weights and biases.In every unknown pattern that the converged network subsequently confronts with, it searches for the features already learned and outputs an indication for their presence or absence. This capability for target detection is exhibited by the response of the network to various test patterns presented to it.Three network topologies are tried with two variants of backpropagation learning and a grading of the performance of each combination is subsequently made.

Modifications of secondary reflector antenna patterns due to shaped beams from flanged primary horn feeds

With the advent of satellite communication and radio astronomy, the need for large and efficient reflector antennas had triggered a widespread investigation in reflector feed design techniques. Major improvements sought are reduction in spill-over, cross polarization losses and the enhancement of aperture efficiency. The search for such a feed culminated in the corrugated horn. The main idea behind the present work is to use the H-plane sectoral horns fitted with,corrugated flanges as feeds of a paraboloid and see how the secondary pattern of the reflector antenna varies with different parameters of the feed. An offset paraboloid is used as the secondary reflector in order to avoid the adverse effect of aperture ‘blocking by the feed horn structure on the secondary radiation pattern. The measurements were repeated for three different H-plane sectoral horns with the same set of corrugated flanges at various X-band frequencies. The following parameters of the whole system are studied: (a) Beam shaping. (b) Gain. (c) Variation of VSWR and (d) Cross polarization

Coherent patterns and self-induced diffraction of electrons on a thin nonlinear layer

Electron scattering on a thin layer where the potential depends self-consistently on the wave function has been studied. When the amplitude of the incident wave exceeds a certain threshold, a soliton-shaped brightening (darkening) appears on the layer causing diffraction of the wave. Thus the spontaneously formed transverse pattern can be viewed as a self-induced nonlinear quantum screen. Attractive or repulsive nonlinearities result in different phase shifts of the wave function on the screen, which give rise to quite different diffraction patterns. Among others, the nonlinearity can cause self-focusing of the incident wave into a beam, splitting in two "beams," single or double traces with suppressed reflection or transmission, etc.

Heavy metal tolerance patterns of total heterotrophic bacteria isolated from the soils of Mahatma Gandhi University campus, Kottayam, Kerala

Industrialization of our society has led to an increased production and discharge of both xenobiotic and natural chemical substances. Many of these chemicals will end up in the soil. Pollution of soils with heavy metals is becoming one of the most severe ecological and human health hazards. Elevated levels of heavy metals decrease soil microbial activity and bacteria need to develop different mechanisms to confer resistances to these heavy metals. Bacteria develop heavy-metal resistance mostly for their survivals, especially a significant portion of the resistant phenomena was found in the environmental strains. Therefore, in the present work, we check the multiple metal tolerance patterns of bacterial strains isolated from the soils of MG University campus, Kottayam. A total of 46 bacterial strains were isolated from different locations of the campus and tested for their resistant to 5 common metals in use (lead, zinc, copper, cadmium and nickel) by agar dilution method. The results of the present work revealed that there was a spatial variation of bacterial metal resistance in the soils of MG University campus, this may be due to the difference in metal contamination in different sampling location. All of the isolates showed resistance to one or more heavy metals selected. Tolerance to lead was relatively high followed by zinc, nickel, copper and cadmium. About 33% of the isolates showed very high tolerance (>4000μg/ml) to lead. Tolerance to cadmium (65%) was rather low (<100 μg/ml). Resistance to zinc was in between 100μg/ml - 1000μg/ml and the majority of them shows resistance in between 200μg/ml - 500μg/ml. Nickel resistance was in between 100μg/ml - 1000μg/ml and a good number of them shows resistance in between 300μg/ml - 400μg/ml. Resistance to copper was in between <100μg/ml - 500μg/ml and most of them showed resistance in between 300μg/ml - 400μg/ml. From the results of this study, it was concluded that heavy metal-resistant bacteria are widely distributed in the soils of MG university campus and the tolerance of heavy metals varied among bacteria and between locations

Single Frame Image Super Resolution Using Learned Directionlets

In this paper, a new directionally adaptive, learning based, single image super resolution method using multiple direction wavelet transform, called Directionlets is presented. This method uses directionlets to effectively capture directional features and to extract edge information along different directions of a set of available high resolution images .This information is used as the training set for super resolving a low resolution input image and the Directionlet coefficients at finer scales of its high-resolution image are learned locally from this training set and the inverse Directionlet transform recovers the super-resolved high resolution image. The simulation results showed that the proposed approach outperforms standard interpolation techniques like Cubic spline interpolation as well as standard Wavelet-based learning, both visually and in terms of the mean squared error (mse) values. This method gives good result with aliased images also.

Study of individual lactation patterns of Iranian dairy buffaloes

The aims of the current study were 1) to investigate the effects of some environmental factors on lactation curve traits (LCTs) including initial milk yield (A), peak yield (PY), days to attain peak yield (PD), inclining- and declining slope of lactation (B and C, respectively), persistency (Per), and 240-d milk yield, and 2) to estimate pairwise phenotypic correlations between these traits in two Iranian buffalo ecotypes (Khuzestani and Azeri buffaloes). The dataset consisted of 15396 and 9283 lactations from 6632 Khuzestani and 3558 Azeri buffaloes, respectively (collected during 1992–2009). The results revealed that almost all of the factors had significant effects on the majority of the LCTs, whereby age group, parity and season of calving had greater influence on 240-d milk yield and PY than the other LCTs in both of the ecotypes. These effects were more apparent in Khuzestani buffaloes than in Azeri buffaloes. In the Khuzestani ecotype, the LCTs were significantly correlated with each other. However, in the Azeri ecotype the 240-d milk yield showed no significant relationship with parameters B, PD and Per. In conclusion, the studied factors play an important role in determining both the shape of the lactation curve and the overal performance of Iranian dairy buffaloes.

Biologically Plausible Neural Model for the Recognition of Biological Motion and Actions

The visual recognition of complex movements and actions is crucial for communication and survival in many species. Remarkable sensitivity and robustness of biological motion perception have been demonstrated in psychophysical experiments. In recent years, neurons and cortical areas involved in action recognition have been identified in neurophysiological and imaging studies. However, the detailed neural mechanisms that underlie the recognition of such complex movement patterns remain largely unknown. This paper reviews the experimental results and summarizes them in terms of a biologically plausible neural model. The model is based on the key assumption that action recognition is based on learned prototypical patterns and exploits information from the ventral and the dorsal pathway. The model makes specific predictions that motivate new experiments.

Discovering similarities in the time use patterns of the Spanish Autonomous Communities by Fuzzy techniques

In 2000 the European Statistical Office published the guidelines for developing the Harmonized European Time Use Surveys system. Under such a unified framework, the first Time Use Survey of national scope was conducted in Spain during 2002– 03. The aim of these surveys is to understand human behavior and the lifestyle of people. Time allocation data are of compositional nature in origin, that is, they are subject to non-negativity and constant-sum constraints. Thus, standard multivariate techniques cannot be directly applied to analyze them. The goal of this work is to identify homogeneous Spanish Autonomous Communities with regard to the typical activity pattern of their respective populations. To this end, fuzzy clustering approach is followed. Rather than the hard partitioning of classical clustering, where objects are allocated to only a single group, fuzzy method identify overlapping groups of objects by allowing them to belong to more than one group. Concretely, the probabilistic fuzzy c-means algorithm is conveniently adapted to deal with the Spanish Time Use Survey microdata. As a result, a map distinguishing Autonomous Communities with similar activity pattern is drawn. Key words: Time use data, Fuzzy clustering; FCM; simplex space; Aitchison distance

A new optimised De Bruijn coding strategy for structured light patterns

Coded structured light is an optical technique based on active stereovision that obtains the shape of objects. One shot techniques are based on projecting a unique light pattern with an LCD projector so that grabbing an image with a camera, a large number of correspondences can be obtained. Then, a 3D reconstruction of the illuminated object can be recovered by means of triangulation. The most used strategy to encode one-shot patterns is based on De Bruijn sequences. In This work a new way to design patterns using this type of sequences is presented. The new coding strategy minimises the number of required colours and maximises both the resolution and the accuracy