Performance Analysis of Indoor Optical Wireless Links

Indoor wireless optical communication is a good alternative to existing mature RF technology. However various challenges in indoor optical wireless technology are due to free space loss, ambient light, and multi path dispersion causing inter symbol interference (ISI). The degradation in performance due to these facts is very much influenced by the channel topology. So in this paper the performance of indoor optical configuration has been analyzed using three types of channel topologies viz., directed (LOS), non-directed (LOS), and multi beam diffused link for various transmitter and receiver design parameters. The analysis has been carried using Optiwave simulation tools

Development of Adaptive Threshold and Data Smoothening Algorithm for GPR Imaging

There are many approaches available to separate the background and foreground in image processing applications. Currently, researchers are focusing on wavelet De-noising, curvelet threshold, Edge Histogram Descriptor threshold, Otsu thresholding, recursive thresholding and adaptive progressive thresholding. In fixed and predictable background conditions, above techniques separate background and foreground efficiently. In a common scenario, background reference is blind due to soil surface moisture content and its non-linearity. There are many methodologies proposed from time to time by researchers to solve this blind reference background separation. But challenges still now remain, because there are two major problems in ground penetrating radar imaging such as targets like ground enhances the false alarm and non-metallic target detection, where the threshold decision is a critical task. In this paper, a novel real time blind adaptive threshold algorithm is proposed for ground penetrating radar image processing. The blind threshold was decided to use normal random variable variance and image data variance. Further, the image was smoothened by random variance ratio to image data variance. Experimental results showed satisfactory results for the background separation and smoothening the targeted image data with the proposed algorithm

Development of Scale and Rotation Invariant Neural Network based Technique for Detection of Dielectric Contrast Concealed Targets with Millimeter Wave System

The detection of concealed targets beneath a person’s clothing from standoff distance is an important task for protection and the security of a person in a crowded place like shopping malls, airports and playground stadium, etc. The detection capability of the concealed weapon depends on a lot of factors likes, a collection of back scattered data, dielectric property and a thickness of covering cloths, the hidden object, standoff distance and the probability of false alarm owing to objectionable substances. Though active millimeter wave systems have used to detect weapons under cloths, but still more attention is required to detect the target likes a gun, knife, and matchbox. To observe such problems, active V-band (59 GHz- 61 GHz) MMW radar with the help of artificial neural network (ANN) has been demonstrated for non-metallic as well as metallic concealed target detection. To validate ANN, the signature of predefined targets is matched with the signature of validated data with the help of the correlation coefficient. The proposed technique has good capability to distinguish concealed targets under various cloths.

Real time Adaptive Approach for Hidden Targets Shape Identification using through Wall Imaging System

In Through-wall Imaging (TWI) system, shape-based identification of the hidden target behind the wall made of any dielectric material like brick, cement, concrete, dry plywood, plastic and Teflon, etc. is one of the most challenging tasks. However, it is very important to understand that the performance of TWI systems is limited by the presence of clutter due to the wall and also transmitted frequency range. Therefore, the quality of obtained image is blurred and very difficult to identify the shape of targets. In the present paper, a shape-based image identification technique with the help of a neural network and curve-fitting approach is proposed to overcome the limitation of existing techniques. A real time experimental analysis of TWI has been carried out using the TWI radar system to collect and process the data, with and without targets. The collected data is trained by a neural network for shape identification of targets behind the wall in any orientation and then threshold by a curve-fitting method for smoothing the background. The neural network has been used to train the noisy data i.e. raw data and noise free data i.e. pre-processed data. The shape of hidden targets is identified by using the curve fitting method with the help of trained neural network data and real time data. The results obtained by the developed technique are promising for target identification at any orientation

Kinetics of Spinodal Phase Separation in Unstable Thin Liquid Films

We study universality in the kinetics of spinodal phase separation in unstable thin liquid films, via simulations of the thin film equation. It is shown that in addition to morphology and free energy,the number density of local maxima in the film profile can also be used to identify the early, intermediate and late stages of spinodal phase separation. A universal curve between the number density of local maxima and rescaled time describes the kinetics of early stage in d = 2, 3. The Lifshitz-Slyozov exponent of -1/3 describes the kinetics of the late stage in d = 2 even in the absence of coexisting equilibrium phases.Comment: 5 figure

Critical Analysis of Background Subtraction Techniques on Real GPR Data

Ground penetrating radar (GPR) is used to detect the underground buried objects for civil as well as defence applications under varying conditions of soil moisture content. The capability of detection depends upon soil moisture, target characteristics and subsurface characteristics, which are mainly responsible for contaminating the GPR images with clutter. Researchers earlier have used averaging, mean, median, Eigen values, etc. for subtracting the background from GPR images. To analyse the background subtraction or clutter reduction problems, in this paper, we have experimentally reviewed background subtraction techniques with or without target conditions to enhance the target detection under variable soil moisture content. Indigenously developed GPR has been used to collect the data for different soil conditions and several background subtraction signal processing techniques were critically reviewed like, mean, median, singular value decomposition (SVD), principal component analysis (PCA), independent component analysis (ICA) and training methods. The signal to clutter ratio (SCR) measurement has been used for performance evaluation of each technique. The relative merits and demerits of each technique has also been analysed. The background subtraction techniques have been appliedto experimental GPR data and it is observed that in comparison of mean, SVD, median, ICA, PCA, the training method shows the highest SCR with buried target. Finally, this review helps to select the comparatively better background subtraction technique to enhance the detection capability in GPR

Dynamics of bell pepper using bio nutrient sources in the northwestern Himalayas

Bionutrients play a vital role in enhancing soil productivity and sustainable agricultural production. In vegetable crops, limited information is available on the relevance of bionutrients in solanaceous crops under protected conditions. Therefore, an experiment was planned to study the response of bionutrients under the modified naturally ventilated polyhouse in mid-hill conditions of Himachal Pradesh for two consecutive years. Various bell pepper varieties, viz., Mekong, Orobelle, Indra and DPCY1, were subjected to a set of bionutrient sources (beejamrit, ghanjeevamrit, jeevamrit and mulching). The results showed that there was a substantial increase in yield parameters in the treatment module, i.e., Mekong + beejamrit@ 200 ml/kg + ghanjeevamrit@5q/ha + jeevamrit @ 500 lt/ha at 21-day intervals + mulching @ 10 t/ha. This treatment exhibited a minimum number of days to 50% flowering (24.16), maximum number of marketable fruits per plant (28.40), fruit length (7.68 cm), fruit breadth (7.70 cm), pericarp thickness (9.15 mm), average fruit weight (109.53 g), plant height (84.06 cm) and marketable yield per plant (3.11 kg). However, Mekong + beejamrit @ 200 ml/kg + ghanjeevamrit @5q/ha + jeevamrit@ 500 lt/ha at 28-day intervals + mulching @ 10 t/hattreatment proved best for total soluble solids (4.58 °Brix), ascorbic acid (166.50 mg/100 g), capsaicin content (6.64%) and carotenoid content (2.43 mg/100 g). Horticultural and biochemical traits were appreciably enhanced after bionutrient application in bell pepper. Therefore, outcomes from the study point out that it is a feasible and economical approach for farmers

Ultrafast microwave-assisted synthesis of various zinc oxide nanostructures

365-372The conventional hydrothermal process for the synthesis of zinc oxide (ZnO) nanostructures has been a slow process and provides less control in terms of shape, size and nucleation time. Whereas, synthesis through microwave heating takes only a few minutes to produce high quality, ultra-pure zinc oxide nanostructures. In this study, we have presented a protocol to fabricate various ZnO nanostructures (vertically-aligned nanorods, vertically-aligned nanowalls, nano flowers and nanopillars) using a domestic microwave oven. Based upon the process study, variation in diameter and length of vertically aligned ZnO nanorods with growth time has been reported. Uniformly distributed ZnO  nanowalls  along with ZnO nanoflowers have been fabricated in less than 5 minutes. In addition to this, ZnO nanopillars have been fabricated for the first-time using evaporation and degradation phenomena in themicrowave oven. Furthermore,the ZnO nanorods have been found to exhibit a super hydrophobic behaviour, whereas the ZnO nanowalls, nanoflowers and nanopillars have shown a hydrophobic behaviour. The developed ZnO nanostructures may have been found their applications in the areas of optics, electronics, biomedical, solar cell, sensors and transistors etc