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Tuna fish is commercially important because of its popularity as both canned and raw meat. Tuna account for a significant proportion of the world fishery products. These fishes are separated based on their types in the industry for exporting raw fishes and processed fish products. An automatic system that can classify fishes into different species will ease the work in such industries. The work proposes an automated tuna classification system using textural macro features. The system uses a dual-tree network with signal matched complex wavelet transform. The signal matched wavelet obtained by the lifting scheme is used to develop a complex wavelet. The complex wavelet-based deep architecture is used to extract translation and deformation invariant features. The system performance is evaluated using different classifiers with ten-fold cross-validation. Results show that the proposed system gives an accuracy of 94.58% using cubic support vector machine (SVM) classifier. The proposed system is evaluated using an independent dataset, and the system shows an accuracy of 92.55%, the precision of 92.52%, recall of 92.03%, and F-score of 92.27%. Performance of the system is compared with the state-of-the-art systems using different performance metrics such as accuracy, precision, recall, F-score, and misclassification error.

Tuna is superior among the marine fishes that are exported in the forms of raw fish and processed food. Separation of Tuna into their species is done in industries manually, and the process is tiresome. This work proposes an automated system for classifying Tuna species based on their images. An ensemble of region-based deep neural networks is used. A sub region contrast stretching operation is applied to enhance the images. Each fish image is then divided into three regions and is augmented before giving as input to pre-trained convolutional neural networks (CNN). After fine-tuning the models, the output from the last convolutional layer is given to a grouped 2D-local binary pattern descriptor (G2DLBP). Statistical features from the descriptor are applied to different classifiers, and the best classifier for each image region model is identified. Different ensemble methods are subsequently used to combine the three CNN-G2DLBP models. Among the ensemble techniques, super learner ensemble method with random forest (RF) classifier using 5-fold cross-validation shows the highest classification accuracy of 97.32%. The performance of different ensemble methods is analyzed in terms of accuracy, precision, recall, and f-score. The proposed system shows an accuracy of 93.91% when evaluated with an independent test dataset. An ensemble of region-based CNN with textural features from G2DLBP is applied for the first time for fish classification.

Aims / Objectives: Identification of fish species is essential in export industries. Among the different fish species exported, tuna forms a significant portion and hence the separation of tuna from other fishes is necessary. The work aims to develop automated systems for the separation of commercially important tuna from other fishes. Methodology: The work proposes two models for the classification of commercial fishes. The first model uses conventional feature descriptors, which extract features from both spatial and frequency domain. These features are combined and are reduced by an ensemble dimension reduction method. The combined and reduced feature sets are evaluated using different classifiers. The second proposed model uses four pre-trained convolutional neural networks, VGG16, VGG19, Xception, and MobileNet, for the classification. The models are fine-tuned for the classification process. Results: Results show that for the first model, extreme learning machine classifier with Mercer wavelet kernel gives high accuracy on combined feature set while the polynomial kernel ELM provides better performance with the reduced set. For the second model, a comparison of the performance of four CNN models is done, and results indicate that VGG19 outperforms other networks in the classification task. Conclusion: Among the two proposed models, pre-trained CNN based model shows better performance than the conventional method in the separation task. Different performance measures, accuracy, precision, recall, F-score, and misclassification error are used to evaluate the system. A comparison of performance of the proposed models with the state-of-the-art systems is also reported.

TErrestrial Trunked Radio (TETRA) is a Professional Mobile Radio (PMR) standard developed by European Telecommunications Standards Institute (ETSI) for critical communications. Filters form an integral part of the physical layer of any communication system. In this paper, the design and implementation of Pulse shaping filter and Digital Up Conversion(DUC) filters in the transmitter section of TETRA radio is proposed. Xilinx System generator blocks have been chosen for the design which can be easily ported from one FPGA platform to another and reduces time to development. The filters have been designed using MATLAB FDATool and Xilinx FIR compiler block. The design has been simulated in MATLAB/Simulink environment and ported on to an Artix-7 FPGA based custom hardware platform. The constellation and spectrum at the output of Digital-to-Analog Converter(DAC) is verified to meet the TETRA standard. Also the transmitter performance measurement parameters like Adjacent Channel Power Ratio (ACPR) and Error Vector Magnitude (EVM) are measured and verified.

Among the most widely traded fish in the world, Tuna is an important fish due to their nutritional value. In the export industry, these fish are manually sorted into various species. In this paper, an automated system is suggested to speed up these industries in order to satisfy the growing need for tuna and its products. Three species of tuna are used here. The contrast of each image is enhanced by using a preprocessing step. Head, abdomen and tail region images are then split from the images. Different parameters then augment these images to get a class balanced dataset. The resulting augmented images are applied to four pre-trained models. The sum rule combines the predictions from the four networks for a region. The combined scores of three region-based predictions are used in the majority voting ensemble to get the final image-wise prediction. Different performance measures are used to evaluate the system, and results show that the proposed system classifies tuna fishes with an accuracy of 95.65%.

Nowadays conversion from text to high resolution image is a challenging task due to its wide variety of application area. For text to image conversion almost all systems use Generative Adversarial Networks as the basic part of the system and GAN guarantees semantic consistency between the text input and the generated image output. In this paper we are comparing two algorithms that is used for generating image from text. The first algorithm is the AttnGAN and the second one is the DF-GAN. AttnGAN builds on top of StackGAN by using attention network which allows it to capture word level information along with the broader sentence level information. The second algorithm is the DF-GAN, which uses single generator and discriminator model to synthesize high resolution images and also uses Matching-Aware Gradient Penalty (MA-GP) to get real images with real description. The model contains a Deep text-image Fusion Block (DFBlock) to generate image features from text. Both algorithms work efficiently for image generation from text but DF-GAN generates the perfect output than AttnGAN. The AttnGAN always focus on the textual part to generate output image but DF-GAN also focuses on background of image.

Electrochemical impedance spectroscopy (EIS) has been applied to measure the H2S gas response of the sensor fabricated on reduced graphene oxide (rGO)-incorporated nano-zinc oxide (n-ZnO) composites. These nanocomposites were prepared by a facile one-step solution route at room temperature. The structural, surface morphological, and elemental analyses of the composite material have been investigated. EIS was carried out to study the H2S gas-sensing properties of fabricated sensors. The developed sensor showed an optimal H2S gas response to various concentrations ranging from 2 to 100 ppm at 90 °C. The H2S gas-sensing performances of pure n-ZnO and various concentrations of rGO-incorporated n-ZnO were evaluated. The H2S gas-sensing results showed that n-ZnO/rGO composites exhibited high response when compared to pure n-ZnO. The enhanced H2S response was speculated to be ascribed due to two factors. First, rGO creates reactive sites for H2S molecule adsorption. Second, rGO has great electrical conductivity compared to n-ZnO that enables the active transport of electrons from H2S gas on interaction with the sensing layer, resulting in enhanced gas response at 90 °C temperatures.

Today technological changes make the probability of more complex things made into simple tasks with more accuracy in major areas and mostly in Manufacturing Industry. Internet of things contributes its major part in automation which helps human to make life easy by monitoring and directed to a related person with in a fraction of second. Continuous advances and improvement in computer vision, mobile computing and tablet screens have led to a revived interest in Augmented Reality the Augmented Reality makes the complex automation into an easier task by making more realistic real time animation in monitoring and automation on Internet of Things (eg like temperature, time, object information, installation manual, real time testing).In order to identify and link the augmented content, like object control of home appliances, industrial appliances. The AR-IoT will have a much cozier atmosphere and enhance the overall Interactivity of the IoT environment. Augmented Reality applications use a myriad of data generated by IoT devices and components, AR helps workers become more competitive and productive with the realistic environment in IoT. Augmented Reality and Internet of Things together plays a critical role in the development of next generation technologies. This paper describes the concept of how Augmented Reality can be integrated with industry(AR-IoT)4.0 and how the sensors are used to monitoring objects/things contiguously round the clock, and make the process of converting real-time physical objects into smart things for the upcoming new era with AR-IoT.

Tuna is one among the popular commercial fishes and forms a major proportion of world fishery products. Separation of these fishes into different species is important to export raw fish and processed fish products. The work proposes an automatic system to separate tuna species using image processing techniques. Images are cropped to reduce the background effect and are enhanced using adaptive histogram equalization. Statistical features from colour histogram, structural features from histogram of oriented gradients, textural features from fuzzy based local binary pattern, and wavelet transform based statistical features are used for the classification. Size of the feature set is decreased by an ensemble of dimensionality reduction techniques. Performance of the system is evaluated with both non-reduced and reduced feature set using different classifiers for ten-fold cross validation. Results show that extreme learning machine classifier using Mortlet wavelet kernel gives high classification accuracy of 92.95% and 90.85% with non-reduced and reduced feature vector respectively.

In recent times, Internet of Medical Things (IoMT) and cloud enabled healthcare applications and services finds helpful for effective decision-making. Melanoma is the serious kind of skin cancer, results to high death rate. Earlier identification of skin cancer can leads to maximum survival rate. But the diagnosis process becomes difficult and expensive because of the need of medical experts and complex medical equipments. To overcome this issue, the latest developments in IoMT based decision making system with maximum performance can be used. This study introduces a new IoMT based skin lesion detection and classification model using Optimal Segmentation and Restricted Boltzmann Machines (RBM), named OS-RBM model. The proposed OS-RBM model involves a series of steps namely image acquisition, gaussian filtering (GF) based preprocessing, segmentation, feature extraction, and classification. Then, optimal segmentation using artificial bee colony (ABC) with kapur’s thresholding takes place. Besides, histogram and texture feature extraction will be carried out. Finally, RBM is applied as a classifier to detect and classify the existence of skin lesion in the dermoscopic images. A detailed simulation analysis takes place for ensuring the better outcome of the OS-RBM model and the results are assessed under diverse performance measures. The experimental outcome ensured the effective classification performance of the OS-RBM model with the maximum sensitivity of 96.43%, specificity of 97.95% and accuracy of 95.68%.

Nowadays, due to the exploding growth of vehicles which paves a way for the unusual population in the road traffic, accidents are becoming more and more common among people. There are various factors which causes accidents. This paper lists out the classification of accidents and various solutions provided to avoid accidents as well as to overcome from accidents when it is encountered. Classification of accidents includes accidents by pedestrians, cyclists, mass casualty and animal accidents. The various solutions to avoid as well as to overcome accidents include usage of smart phones, VANET and GSM along with GPS. The proposed solution detects the accident and sends ambulance to the accident area by the usage of sensors. In this paper a derived factor named Crash rate analysis is used to determine the number of ambulances required for the accident area to take up the recovery process. This work is intended to provide better and faster lifesaving solutions for the road accidents.

This paper attempts to prove that the Artificial Bee Colony algorithm can be used as an optimization algorithm in sparse-land setup to solve Video Summarization. The critical challenge in doing quasi(real-time) video summarization is still time-consuming with ANN-based methods, as these methods require training time. By doing video summarization in a quasi (real-time), we can solve other challenges like anomaly detection and Online Video Highlighting. A simple threshold function is tested to see the reconstruction error of the current frame given the previous 50 frames from the dictionary. The frames with higher threshold errors form the video summarization. In this work, we have used Image histogram, HOG, HOOF, and Canny edge features as features to the ABC algorithm. We have used Matlab 2014a for doing the feature extraction and ABC algorithm for VS. The results are compared to the existing methods. The evaluation scores are calculated on the VSUMM dataset for all the 50 videos against the two user summaries. This research answers how the ABC algorithm can be used in a sparse-land setup to solve video summarization. Further studies are required to understand the performance evaluation scores as we change the threshold function.

In this paper, we present a novel switched band pass filter bank designed using hairpin line topology. This new filter bank design is implemented to facilitate narrow bandwidth mode observations for the upgraded GMRT (uGMRT), as well as providing an option for filtering out strong radio frequency interference that may come up in some parts of the wideband system. Radio Astronomy today requires wideband frequency coverage for achieving higher sensitivity and frequency agility for varied nature of astrophysical observations. As part of a major upgrade, the Giant Metrewave Radio Telescope (GMRT) is going through an increase in the bandwidth coverage from 50 to 1500 MHz, with a maximum instantaneous bandwidth of 400 MHz for increasing the sensitivity of the telescope. As a part of this upgrade, the existing front-end receiver electronics is being modified by introducing wideband low noise amplifiers, octaveband polarizers with low insertion loss, low loss wideband directional couplers for noise injection, wideband filters and high dynamic range broadband post-amplifiers. Keyword: Filter Bank, Hairpin Microstrip filter, uGMRT.

The paper presents the Radio Frequency Interference shielded enclosure design for electrical, electronics and computer network system housed in a radio quite zone of a radio observatory. The systems equipped at the antenna needs a multiple shielding and this paper presents the low cost and custom build shielded enclosure for the sub-systems placed at the antenna and central signal processing station of the observatory. Shielding requirements are of non-standard dimensions and needs a custom design to house the sub-system and at reduced cost. The designed RFI shielded enclosure offer > 74 dB isolation over (0.07-1.6 GHz) with all types of connector interface and cooling fans to avoid heating of the systems. The design is scalable to any non-standard sizes to shield UPS, Computers, Network components, communication equipment, air-conditioner units and lights used at radio observatory.

The High Dynamic Front End Receiver for Band-I (30–80 MHz) for uGMRT developed by Front End Group at GMRT. Four dipoles are used in quad configuration, one pair of dipoles for vertical and another pair of dipoles for horizontal is connected to a power-combiner. The band pass filter is used to suppress out of band rejection and pass 30–80 MHz signal. The polarizer is used before the LNA which converts the received linear polarization to circular. To calibrate the gain of the receiver chain, there is provision to inject an additional noise signal (ENR of 30 dB) into the input of the LNA using directional coupler. It is possible to inject noise at any one of four levels. These are called Low cal, Medium cal, High cal and Extra high cal. To minimize crosstalk between two channels (CH-1 and CH-2) signals a phase switching facility using separate Walsh functions for each signal path is provided at the RF section of the receiver. Additional low pass and band stop filter is used after High Dynamic post amplifier for further suppression of SW and FM band. The RF power detector is used for RF CH power monitoring.

This paper discusses about broadband RF and Optical monitoring scheme for uGMRT, each antenna receives two polarizations signal, which is sent over two different wavelengths from remote antenna location without conversion to IF on a single fiber, and in addition it also supports return link on 1310nm wavelength in reverse direction from central processing station by using wavelength division multiplexing technique. In total we have 60 channels from 30 antennas. The optical monitoring is done for 30 antenna signals using in-line photodiode which records the incoming optical power from 30 remotely located antennas. Radio astronomy receivers are designed to sense very weak noise like signal from celestial bodies, one of the most critical parameters of receiver is sensitivity which depends on system parameters and signal quality. To continuous keep track of system health status and signal quality from 60 channels using conventional method is time consuming and may prone to human error, so automated broadband RF monitoring system is implemented. System is designed with high isolation RF switches for channel selection having adjacent ports isolation of 55 dB. The system can support frequency range from 50 MHz to 2 GHz, it runs for 24 × 7 records and display real-time 60 channels from 30 antennas in sequential manner, the RF switch logic is controlled using LabVIEW software and it also acquire respective channel RF spectrum. This has proven to be a very useful tool to study various parameter like antenna signal power levels, system gain, power level variation over band, and it also provides continuous information of RFI situation at each antenna. The recorded spectrum can be analyzed and used to flag the data corrupted due to RFI during the astronomical observation.

The GMRT is an aperture synthesis array of 30 fully steerable, 45 metre diameter parabolic dish antennae spread over 30 km region near Pune in western India. It is designed to operate at a range of frequencies from 50 MHz to 1450 MHz, in five distinct frequency bands. The legacy GMRT feeds and front-ends are designed to operate at five frequency bands centered at 150 MHz, 233 MHz, 327 MHz, 610 MHz and L-band extending from 1000 to 1420 MHz, with a final instantaneous bandwidth of 32 MHz.

With 30 antennas and a maximum baseline length of 25 km, the Giant Metrewave Radio Telescope (GMRT) is the premier low-frequency radio interferometer today. We have carried out a study of possible expansions of the GMRT, via adding new antennas and installing focal plane arrays (FPAs), to improve its point-source sensitivity, surface brightness sensitivity, angular resolution, field of view, and U-V coverage. We have carried out array configuration studies, aimed at minimizing the number of new GMRT antennas required to obtain a well-behaved synthesized beam over a wide range of angular resolutions for full-synthesis observations. This was done via two approaches, tomographic projection and random sampling, to identify the optimal locations for the new antennas. We report results for the optimal locations of the antennas of an expanded array (the "EGMRT"), consisting of the existing 30 GMRT antennas, 30 new antennas at short distances, $\leq 2.5$ km from the array centre, and 26 new antennas at long distances, $\approx 5-25$ km from the array centre. The collecting area and the field of view of the proposed EGMRT array would be larger by factors of, respectively, $\approx 3$ and $\approx 30$, than those of the GMRT. Indeed, the EGMRT continuum sensitivity and survey speed with 550-850 MHz FPAs installed on the 45 antennas within a distance of $\approx 2.5$ km of the array centre would be far better than those of any existing interferometer, and comparable to the sensitivity and survey speed of Phase-1 of the Square Kilometre Array., 16 pages, 13 figures; accepted for publication in MNRAS

To improve the meat quality of Japanese quail ( Coturnix coturnix japonica ), a new strain was developed by Tamilnadu Veterinary and Animal Sciences University named “Namakkal quail-1”. The purpose of the study is to know the sensory quality of the Namakkal quail-1. 24 Birds including 12 males and 12 females of 4 th and 6 th week birds were procured from Poultry farm Complex of Department of Poultry Science, Veterinary College and Research Institute, Namakkal and slaughtered as per the standard slaughter procedures after 4 hours of resting interval at the Department of Livestock Products Technology (Meat Science), Veterinary College and Research Institute, Namakkal. The sensory properties like colour, flavour, juiciness, tenderness and overall acceptability were estimated. Analysis of variance showed that age and sexes of the birds no significant effect on colour, flavour, juiciness, tenderness and overall acceptability of meat. But Namakkal quail-1 meat score higher than Japanese quail, Chicken, Duck and Geese meat in 9 point hedonic scale. It is concluded that Namakkal quail-1 meat is tastier than other poultry meat.

This paper presents the design of a dual band metamaterial microwave absorber using a spider like resonating structure obtained by diagonally interconnecting half cut square rings with square pads added at the open ends. Multiple resonance has been reduced to two resonating frequencies of 5.38 GHz (C band) and 9.09 GHz (X band) with 98.8% and 99.8% absorption respectively through a split in the middle of the structure. The structure is built on the top layer of FR4 dielectric substrate with a metallic ground plane at the bottom layer. The dual band absorber is characterized at various oblique incident angle and at different polarization angle for normal incidence. C band peak exhibits polarization independent performance for 0° to 45° polarization angle while the second X band peak shows polarization independency for 0° to 90°. The current distribution over the structure at the tuning frequency is presented to understand the working of the structure. The metamaterial behavior of the structure is verified with the negative permittivity and permeability parameters derived from the S parameters at the resonating frequency. The designed structure is unique without closed ring structures and exhibits both polarization independent and polarization dependent absorption on one metamaterial structure.

Nowadays robotics technology is an ever-growing advanced computing platform for real time scenario. Wild animals are entering into the human habitats due to deforestation and environmental changes. It leads to severe damage to public properties, civilization of human beings and animals. To avoid these kind of problems, wild animal tranquillizer using hexapod robot is proposed. Based on the animal motions, the new designed hexapod robot can be able to locomote at any surfaces for tranquillization of wild animal. It reduces the risk of forest rangers and also it protects human beings as well as wild animals.

Climate change has an adverse effect on climate sensitive livestock sector. A well-structured interview schedule was used to collect the practices adopted by the livestock farmers at farm-level in irrigated and rainfed areas of Namakkal district in Tamil Nadu. Practices adapted to mitigate the effects of climate change were documented from 320 livestock farmers, 160 from irrigated and 160 from rainfed areas. Providing shade during day time was the major practice adapted in housing, cooling animals by washing, alteration in the grazing time, cooling and not allowing for grazing after insemination, deworming animals two to three days prior to insemination, feeding lemon after insemination, feeding mineral mixture during summer, soaking concentrate feed in water, feeding aloevera and neem oil for 15 days before insemination and shifting from buffalo to white cattle were the practices adapted by the livestock farmers to mitigate the effect of climate change. Further, the field experts opined that feeding mineral mixture (100%), alteration in grazing time (100%), cooling animals after insemination (97.22%), deworming of animals two or three days prior to insemination (91.67%) had effect at field level. Field experts suggested that feeding lemon after insemination, feeding mineral mixture during summer and feeding aloevera and neem oil for 15 days before insemination were the practices need further scientific research for up-scaling of practices.

Liquid metal cooled Fast Breeder Reactors form the second stage of Indian nuclear programme. Prototype Fast Breeder Reactor (PFBR) is 500MWe pool type reactor, which is under construction at Kalpakkam, India. Measurement of sodium flow in the reactor system is essential from both operational and safety point of view. Primary sodium pump discharge, secondary sodium circuit, safety grade decay heat removal circuit and auxiliary sodium circuits are the critical locations in an FBR, where sodium flow measurement is of importance. Apart from this, sodium flow measurement in subassemblies in the core facilitates the detection of flow blockage in the subassemblies. Permanent magnet flow meter is widely used for pipe flow measurement in sodium systems, however, it cannot be considered for applications like subassembly and pump discharge flow measurements. From the safety point of view, flow through the core should be ensured under all operating conditions in a FBR. Development of suitable flow sensors meeting the dimensional constraints and having accessibility for maintenance is a challenge. An eddy current flow meter was designed and developed for sodium flow measurement in PFBR and the developed probe was tested for its performance in a sodium test rig. The developed ECFM was also used for core flow measurements in Fast Breeder Test Reactor (FBTR), India and in Phenix reactor, France, during its end of life test before decommissioning. This paper discusses the activities related to the development, calibration, testing of ECFM probe for PFBR and results of its utilization for flow measurement in FBTR and in Phenix reactor, France.

A modern radio astronomy observatory needs continuous monitoring of the radio spectrum to detect and characterise the sources of RFI, and ever improving plans for mitigation against such sources. With increasing population densities, accompanied by modernization in transport and communication facilities, the sources of external RFI affecting a radio observatory increase with time. The problem is aggravated by the increase in sensitivity of the observatories, as well as by the increase in the frequency range and bandwidths of observations. An additional threat comes from self-generated RFI produced by the increasingly computer controlled and data intensive operations of a typical radio telescope. These aspects of RFI significantly affect the Giant Metrewave Radio Telescope (GMRT), working at low frequency. The ongoing upgrade of the GMRT, which provides near-seamless frequency coverage from about 120 to 1500 MHz, with improved sensitivity receivers, makes it even more prone to the threat of RFI. We present here an overview of the different kinds of RFI that affect the GMRT, and the schemes used for regular monitoring to detect sources of RFI, their characterization, and the steps taken towards mitigation. The different measures for mitigating the various kinds of RFI are described. These range from coordination with various external agencies to maintain the restrictions in and around the GMRT array and reduce the impact of RFI with better shielding for equipments at the observatory. Significant work has been done for design of shielded enclosures for various kinds of equipment in the observatory, which helps to achieve 40 to 60 dB additional isolation to mitigate leakage of RFI. We present our learning and improvements achieved from these exercises. We also outline our plans for future work in RFI mitigation at the GMRT. A distributed RFI monitoring antenna array along the GMRT antenna array is planned with a dedicated analog fiber optic link for real-time RFI monitoring and software mitigation in future.

Modern radio telescopes were designed for wider bandwidth to use the interference free bands for radio astronomy. Many intentional radiations are directional and line of site, pointing can be avoided to prevent receiver saturation. About 35000 Satellites are in space to provide voice and data service, navigation, GPS, weather, military and various space programs. These satellite footprints are larger to cover wide area and produce interference to radio telescopes. These satellites are geo stationary, geo synchronous, low, and medium orbiting satellites whose locations and orbits have been characterized with the precise servo system of GMRT antennas. The individual satellite signals have been characterized for its frequency, power level and beam width using GMRT antenna and receiver. The antenna control and monitoring system of GMRT observatory is programmed to produce an alarm whenever the antenna beam is nearing a satellite. The software tools provide prediction of these satellite cross over with any scheduled radio astronomy observation, real time location of the antenna beam with adjacent line of site satellites on the sky and tools to post process the old astronomical data for flagging the duration of satellite signal overlap or saturation. The soft tools will be used to apply digital filtering techniques to mitigate these satellite signals in real time or during post processing. The paper presents the detail characterization of satellite interference to GMRT and the software tools developed to co-exist with satellite interference with detail analysis of the loss of signal or data for any given astronomical observation.

This paper presents high throughput architecture for the hardware implementation of Advanced Encryption Standard algorithm. Advanced Encryption Standard is the industry standard crypto algorithm for encryption and is used for protecting secret information. This work is mainly targeted for low-cost embedded applications. This paper introduces parallel operation in the folded architecture to obtain better throughput. The design is coded in Very High-speed Integrated Circuit Hardware Description Language. Timing simulation is performed to verify the functionality of the designed circuit. The proposed structure is implemented in Virtex-6 XC6VLX75T FPGA device. This work gives a high throughput of 37.1Gb/s with a maximum frequency of 505.5MHz, which is 20% higher than the maximum throughput reported in the literature. Copyright © 2012 John Wiley & Sons, Ltd.

Lack of availability of good quality leather and growing demand for products force the researchers to find alternative materials or to partially substitute the usage of leather in products. Eco-friendly biodegradable materials are the need of the hour owing to growing environmental issues associated with the synthetic polymers. This study aims at assessing the physical, comfort, structural and thermal properties of non-mulberry silks such as eri, muga and a blend of eri and muga (EM) fabrics for their suitability to combine with goat suede leather for apparel application. It was found that all the selected fabrics exhibit comparable or even better comfort and mechanical properties to that of goat suede leather. Indeed tensile strength of muga fabric is much superior to goat suede leather. On the other hand, goat suede leather dominates in percentage elongation compared to all the selected fabrics. Scanning electron microscopy and FT-IR spectroscopic analysis provide convincing evidences on the fact that all the selected silk fabrics are based on non-mulberry varieties. The thermal stability of all the three silk fabrics is better than goat suede leather. The results of this study suggest that the selected silk fabrics can be used for making apparel as well as other variety of products in combination with leather.

A Guest-Host system based on meta-Nitroaniline (m-NA) and recycled polystyrene (RPS) susceptible to generate nonlinear optically (NLO) active property such as second harmonic generation (SHG) has been prepared. Pure, sublimed, optical grade, crystalline m-NA is used as a guest and RPS from the disposable packaging waste as available utilized as the host polymer. In this paper we report the effect of NLO active m-NA on the bulk and optical properties of RPS. The purified m-NA was incorporated from 1-10wt% in the RPS polymer matrix by conventional solution casting method. Thin, transparent, freestanding films obtained were characterized with optical microscope, scanning electron microscope (SEM), viscosity measurement, and UV-Visible (UV-Vis) spectroscopy for bulk properties evaluation and Nd:YAG laser studies for optoelectronics application such as SHG through frequency doubling.

Organic polymer based materials are becoming the workhorse in the area of photonics and optoelectronics. These materials are rapidly replacing their inorganic counter parts due to their flexibility in manufacturing combined with the ease in fabrication and manufacturing. Polystyrene, being a low cost commercial commodity plastic material has been utilized as one of the important polymeric material for various NLO active devices. Guest-Host systems based on polystyrene and NLO active chromophores have been extensively studied. As a host polymer it can easily accommodate the NLO guest molecules by simple modification by solution casting and other processes. Thus, polystyrene based NLO active systems offers a relatively cost-effective NLO active systems. Recent investigations have confirmed the suitability of disposable recycled polystyrene as a host polymer to accommodate NLO active chromophores that can lead to dirt-cheap NLO active device materials. This review summarizes the applications of polystyrene based materials in the area of Optoelectronics. The fundamental aspects pertaining to Guest-Host NLO chromophore is also discussed. Some of the recent investigation about the usage of recycled polystyrene system is highlighted.

Emulsion-based meat products play an important role in modern meat industry. Though meat batters have been prepared traditionally since long back in the history, the scientific principles and the knowhow are significantly important in the case of commercial products. In India, the market for emulsion meat products is gaining importance in the recent years and the native producers are in critical need for the scientific basis of production of emulsion meat products with better yield, good sensory qualities and nutrition. Hence, this review will throw light on some of the important factors which influence the properties of meat emulsion such as stability, structure, etc. and the product texture and yield as the revealed by past researches which will be useful to the meat processors in their practical application in preparing meat emulsion products.

Studies of ballistic penetration into metal plates and their numerical simulation currently play a vital role in the defence sector. However, no congruent results have been presented so far, especially when it comes to impact on welded plates. Furthermore, these issues are investigated for normal impacts and very few have made an attempt for oblique impacts. Thus the aim of the present work is to conduct numerical simulation using Abaqus/Explicit in order to evaluate the ballistic performance of similar and dissimilar welded plates subjected to various bullet velocities and impact angles. The effect of post weld residual stresses and associated plastic damage on the ballistic performance of similar (Al6061) and dissimilar (Al 6061- SS 304) welded plates is also determined. The energy absorbed by the welded plates for various configurations was determined and the results are critically evaluated.

An adaptive carrier interferometry (CI) scheme is proposed for multicarrier code-division multiple-access (MC-CDMA) systems where it is assumed that there is a feedback channel between the receiver and the transmitter. By exploiting the additional degree of freedom in selecting the amplitudes of the subcarriers in accordance with the channel condition, the proposed scheme attains a significant performance gain over the conventional CI-MC-CDMA systems in which a constant amplitude is set for all the carriers. Two adaptation strategies, namely 1) local adaptation and 2) global adaptation, are considered for estimating the appropriate subcarrier amplitudes at the receiver in the proposed systems. Both single-user adaptation, where the other users do not adapt, and multiuser adaptation, in which all users adapt, are investigated. A further advantage of the proposed scheme is that it eliminates the peak-to-average power ratio problem present in the conventional CI-MC-CDMA systems

To rise above the limitation of the Traditional load forecasting method using data warehousing system, a new load forecasting system basing on Radial Basis Gaussian kernel Function (RBF) neural network is proposed in this project. Genetic algorithm adopting the actual coding, crossover and mutation probability was applied to optimize the parameters of the neural network, and a faster growing rate was reached. Theoretical analysis and models prove that this model has more accuracy than the traditional one. There are several methods available to integrate information source, but only few methods focus on evaluating the reliability of the source and its information. The emergence of the web and dedicated data warehouses offer different kinds of ways to collect additional data to make better decisions. The reliable and trust of these data depends on many different aspects and metainformation: data source, experimental protocol. Developing generic tools to evaluate this reliability represents a true challenge for the proper use of distributed data. In this project, RBF neural network based approach to evaluate data reliability from a set of criteria has been proposed. Customized criteria and intuitive decisions are provided, information reliability and reassurance are most important components of a data warehousing system, as their power in a while retrieval and examination.

This paper fully based on the Interline Power Flow Controller(IPFC) with optimal power flow in Transmission System, because the flow of electricity through the transmission lines can be effectively controlled by using IPFC. This paper contains IPFC is developed for four bus system. The performance of IPFC with Genetic controller and PI controller can evaluate in single-machine and multimachine power systems subjected to various transient disturbances. Optimal injected parameters will be installed IPFC derived for superior transient stability performance using Genetic Algorithm (GA). Genetic optimization parameter has been developed to design intelligent adaptive controllers for improving the transient stability compared with other controller. Simulation is done by MATLAB/ SIMULINK.

Wetland paddy culture is being considered as one of the important biogenic sources of methane (CH4) emission. A study was undertaken to understand the relationship between soil nutrients and CH4 emission dynamics from a traditional integrated agriculture (Fish– Rice) system practiced in the high-altitude region of Arunachal Pradesh. Organic form of agriculture is practiced in the study site because of which most of the soils are rich in nutrients. Further, efficient management of water through a network of secondary and tertiary canals makes sure that the nutrients are not washed out from the fields. In the present study, CH4 emission showed a significantly (p < 0.05) positive correlation with soil temperature, moisture content, soil organic carbon, water holding capacity and available phosphorous, whereas a negative correlation was found with soil respiration. It was also found that the CH4 emission was greater during active tillering stage of rice and lowest recorded after harvesting.

Restoration of images has become a major stream in the digital image processing. Restoring blurred images for effective information retrieval and feature extraction has been focused by researchers worldwide. The Simulink model of an iterative algorithm has been presented in this paper. Restoration has been achieved iterative filtering approach followed by a contrast enhancement module. The images are blurred using mean blurring function with BSNR of 100. The performances are estimated using objective function and PSNR. The obtained value of the PSNR is about 6.25.

Software development has nowadays evolved into a extreme change that uses the best modules being run in various closed and open source software. Extracting the best component and fit them into an ongoing component based development software poses great challenges to run the software error free with desired outcomes. In this proposal we have introduced an `Intelligent Risk Analysis Model (IRAM) for reusability in developing component service oriented software, which are developed using eminent object oriented programming language paradigm Java. This model performs surfing operation into Java object oriented programming modules warehouse, which consists of several availability modules of various projects, and gives a list of suitable module. Those modules are tested on cohesion /coupling testing analysis to determine the individual strength and binding capacity of modules before performing Regression test. Final desirable outcomes are tested on performing regression test while integrating successful level module with domain being developed and proper deployment is made on successful expected outcome of the product. Risk analysis of software project is analyzed for transformation of reusability components risk before transformation Analysis, adaptable risk Analysis, and reusability risk Analysis for package in Java programming. In this paper IRAM model to focus Java package the domain and size of package, integration and dependency relationship of package, measuring the coupling and cohesion in risk metric for development and implementation of reusability package without any risk factor.

Embedded systems are becoming increasingly complex, networked, and functionally extensible through software, exposing them to a large number of security problems that have plagued general-purpose systems and thereby a need for an efficient monitoring method arises. Various security attacks exist and a major concern is memory attack. Any change in the memory content of the processor will change the flow of execution. In order to ensure secure execution and detect intrusion of an embedded processor, effective intrusion monitoring technique is proposed in this paper. The technique uses run-time verification of the program at instruction level. The instruction integrity is verified using hash function. Due to limited memory and processing capabilities of embedded systems this technique functions within the constraints, by focusing on effective detection and low overhead.

Cryptographic algorithms are the most essential elements in designing the system security. Though there are numerous encryption systems used in security systems by various organizations, for the wider use, a particular encryption method is used as a standard. The internationally accepted and acclaimed algorithm is Advanced Encryption Standard. Here in this paper we have implemented the Advanced Encryption Standard (AES) using hardware descriptive language (HDL) and constructed a modified S-box. Area and power of both S boxes are compared and their resistance to attack is also analyzed.

The need to revise the curriculum for the postgraduate course (M.D.) in Pharmacology has been perceived by the academicians in India since quite some time. The changing professional requirements of the graduating students, the current scenario vis a vis animal experimentation and the emphasis of the Medical Council of India on a competency based curriculum has triggered this felt need. In spite of the fact that most medical institutions and universities in India offer postgraduate courses in pharmacology, the curriculum lacks uniformity with extreme variations observed at some places. This article attempts to analyze the existing curricula in pharmacology in India and suggest modifications that could be recommended to the suitable regulatory bodies for implementation. A revision of objectives in the three domains of learning, development of skills that help develop suitable competencies, adoption of teaching learning methods in addition to the conventional methods, and a rethink on the assessment methods have been recommended. Development and validation of alternatives skill-based modules in lieu of animal experiments are recommended. Additional skills like medical writing and communication skills, professionalism and ethics, multi and inter-disciplinary integration and collaboration and a wider exposure of students to the pharmaceutical, academic, regulatory and research institutions for onsite learning were also recommended to fulfill their future career requirements.

This paper jointly optimizes the chip waveform and the carrier spacing in order to minimize the multiple access interference (MAI) in band-limited asynchronous multicarrier direct sequence code-division multiple access (MC-DS-CDMA) systems. The methodology uses a polynomial to synthesize the elementary density function, which characterizes the band-limited chip waveform. It is shown that using a simple polynomial representations for the elementary density functions (with only a few terms) the proposed chip waveforms and carrier spacings considerably reduce the MAI compared to the existing chip waveforms, particularly the commonly used raised cosine waveform, when the roll-off factor is large

This paper considers signature waveform design for downlink communications in a multicarrier direct sequence code division multiple access (MC-DS-CDMA) system. The design introduces a carefully chosen phase offset in each carrier to minimize the multiple access interference (MAI). With the proposed signature waveform design, a significant performance improvement over the existing MC-DS-CDMA systems is achieved.

Background Sleep apnoea can result in traffic accidents, and the British Lung Foundation9s (BLF) “Snoring and Sleep Apnoea” and the Driver and Vehicle Licensing Agency9s (DVLA) “Think! Tiredness can kill” leaflets are commonly used to inform patients about this. We wished to assess the impact of such knowledge on the general understanding and motivation of patients undergoing formal assessment for sleep apnoea in a sleep clinic. Methods In a prospective survey, patients were provided with the above leaflets when they underwent the sleep study, and completed a structured questionnaire when attending the results clinic several weeks later. Results 125 consecutive patients (92 male) with a mean (SD) age of 51 (14) years, BMI of 33.6 (6.9) and Epworth Sleepiness Scale of 10 (6) completed the questionnaire. 51 (41%) were eventually diagnosed with significant obstructive sleep apnoea/hypopnoea syndrome (OSAHS) requiring referral for continuous positive airway pressure therapy. 105 patients (84%) read the BLF leaflet and 91 (87%) assumed they understood about sleep apnoea from it. 28 (27%) believed they had sleep apnoea, 26 (25%) believed they did not, while the remainder (48%) were unsure. Although 28 (27%) became more worried about themselves, 56 (53%) were more keen to undertake the tests but 5 (5%) were not. 92 participants (74%) were current drivers and 84 (91%) read the DVLA leaflet. Only 10 of these (12%) thought they might have a disorder that could impact on their driving abilities although 38 (45%) were concerned they might not be allowed to drive in future. However, only 4 (5%) were discouraged to undertake the tests because of this. Overall, most patients (80%) found these leaflets informative and easy to understand. Conclusions These leaflets appear to improve patients9 understanding of OSAHS and its implications, particularly regarding driving. Although they can engender concern and anxiety among some, the majority of patients felt motivated to undertake the tests. Improving the level of patient education and awareness through such leaflets may positively influence their involvement in overall management, potentially improving compliance and outcomes in the long term.