Age Invariant Face Recognition using Convolutional Neural Network

In the recent years, face recognition across aging has become very popular and challenging task in the area of face recognition.  Many researchers have contributed in this area, but still there is a significant gap to fill in. Selection of feature extraction and classification algorithms plays an important role in this area. Deep Learning with Convolutional Neural Networks provides us a combination of feature extraction and classification in a single structure. In this paper, we have presented a novel idea of 7-Layer CNN architecture for solving the problem of aging for recognizing facial images across aging. We have done extensive experimentations to test the performance of the proposed system using two standard datasets FGNET and MORPH(Album II). Rank-1 recognition accuracy of our proposed system is 76.6% on FGNET and 92.5% on MORPH(Album II). Experimental results show the significant improvement over available state-of- the-arts with the proposed CNN architecture and the classifier

Colour Image Segmentation using Fast Fuzzy C-Means Algorithm

This paper proposes modified FCM (Fuzzy C-Means) approach to colour image segmentation using JND (Just Noticeable Difference) histogram. Histogram of the given colour image is computed using JND colour model. This samples the colour space so that just enough number of histogram bins are obtained without compromising the visual image content. The number of histogram bins are further reduced using agglomeration. This agglomerated histogram yields the estimation of number of clusters, cluster seeds and the initial fuzzy partition for FCM algorithm. This is a novell approach to estimate the input parameters for FCM algorithm. The proposed fast FCM(FFCM) algorithm works on histogram bins as data elements instead of individual pixels. This significantly reduces the time complexity of FCM algorithm. To verify the effectiveness of the proposed image segmentation approach, its performance is evaluated on Berkeley Segmentation Database(BSD). Two significant criteria namely PSNR(Peak Signal to Noise Ratio) and PRI (Probabilistic Rand Index) are used to evaluate the performance. Although results show that the proposed algorithm applied to the JND histogram bins converges much faster and also gives better results than conventional FCM algorithm, in terms of PSNR and PR

ESTIMATION OF THE DRUG-DRUG AND DRUG-POLYMER OPHTHALMIC COMPLEX AT STOICHIOMETRY BY TERNARY PHASE BEHAVIOUR

Objective: The study focus on the drug-drug and drug-polymer interaction and their estimation at stoichiometry when such systems were formed. In this discovery we tried to make use of the latest research and novel concepts to explore the drug-polymer-polymer Ionic ternary InteractionMethods: Partial ternary phase diagrams were constructed and the stoichiometry of the ciprofloxacin/anionic polymer interaction was assessed in distilled water by means of dialysis equilibrium. The polymers were completely hydrated in distilled water by gentle stirring at room temperature and studied for viscosity and turbidimetric measurements.Results: Comparing the partial ternary phase diagrams of the different anionic to each other. PAA exhibited the largest gel area even with low polymer content. The anionic polymers HA and PAA showed good capability to interact with the drug giving soluble drug/polymer complexes; moreover they were able to form polymer/polymer complexes with Poloxamer and HCS, with a stoichiometry depending on the polymers involved.Conclusion: From the results of the present study, it can be concluded that formulations were made isotonic and favours corneal permeation of both the drug. Ocular Irritancy denotes formulations were quite stable & useful in novel format of sol-gel transformations.Â

Effect of foliar spray of zinc, iron and boron on the growth, yield and sensory characters of guava (Psidium guajava L.) Cv. Sardar L-49

The field experiment was carried to evaluate the response to the foliar application of micronutrients viz. zinc, iron and boron in single or in different combinations on guava (Psidium guajava L.) cv. Sardar L-49 for various growth, yield and sensory parameters. From various combinations of micronutrients growth characters were remain uninfluenced. Combination of 0.5% Zinc sulphate + 0.5% Ferrus sulphate + 0.3% Borax significantly influenced fruit per shoot (3.6), overall yield (57.1 kg/tree) and sensory characters like aroma (7.7), taste (8.1), flavour (8.2), texture (7.5) and also overall acceptability (7.9). Application of 0.3% Borax significantly influenced flowers per shoot (5.3). Minimum fruit drop was recorded with application of 0.5% Ferrus sulphate + 0.3% Borax and minimum fruit drop per shoot observed in 0.5% Zinc sulphate + 0.3% Borax foliar application. The present study indicated that combined application of micronutrients enhanced fruit set, minimized fruit drop and overall yield. This has resulted in improved sensory characters in the guava fruit. This will lure consumers with appealing fruit that would enable farmers to earn a decent sum of money

FPGA Based Embedded Multiprocessor Architecture

Multiprocessor is a typical subject within the Computer architecture field of scope. A new methodology based on practical sessions with real devices and design is proposed. Embedded multiprocessor design presents challenges and opportunities that stem from task coarse granularity and the large number of inputs and outputs for each task. We have therefore designed a new architecture called embedded concurrent computing (ECC), which is implementing on FPGA chip using VHDL. The design methodology is expected to allow scalable embedded multiprocessors for system expansion. In recent decades, two forces have driven the increase of the processor performance: Advances in very large-scale integration (VLSI) technology and Micro architectural enhancements. Therefore, we aim to design the full architecture of an embedded processor for realistic to perform arithmetic, logical, shifting and branching operations. We will be synthesize and evaluated the embedded system based on Xilinx environment. Processor performance is going to be improving through clock speed increases and the clock speed increases and the exploitation of instruction- level parallelism. We will be designing embedded multiprocessor based on Xilinx environment or Modelsim environment

Health at Home System Design for Remote Patient Monitoring

This paper focuses on the design and development of the Health at Home (H@H) system for remote patient monitoring. The system is integrated with the windows PC for data acquisition. The implemented design contains Disease Detection Algorithm (DDA) for disease detection and metabolic parameter monitoring on health at home platform. Regular real-time monitoring in human beings is needed for early detection of abnormalities in metabolic parameters and prevention of disease occurrence. The general conditions of a person’s body depend on many vital parameters which lead to consideration towards the system design. The system focuses on the monitoring of vital signs and work as early detection of disease. The proposed system consists of sensing devices and sensor processing using Arduino for remote monitoring of vital signs in human beings. DOI: 10.17762/ijritcc2321-8169.15084

Two Channel Estimation Methods for MIMO-OFDM System

Adaptive Filter is a part of the modern communication system. The applications of the adaptive filters are channel equalization, noise cancellation, system identification and adaptive beam forming. So the proper implementation of adaptive filter is a great deal. The intersymbol interference (ISI) caused by the multipath in band limited frequency selective time dispersion channel distort the transmitted signal.  In this paper, we have concentrated on modifying the algorithm for the adaptive filter. The proposed VSS-LLMS and Modified Variable Step Size Leaky LMS (MVSS-LLMS) which improves the channel estimation in the noisy environment. Also we compared the results of our proposed algorithms with the LMS, RLS and VLLMS and observed that it improves in computational complexity and Bit Error Rate (BER) performance. Keywords: Adaptive Channel Estimation, Adaptive filter, LMS, RLS, VLLMS and MVSS-LLM

Axisymmetric Thermoelastic Response in a Semi-elliptic Plate With Kassir’s Nonhomogeneity in the Thickness Direction

The main objective is to investigate the transient thermoelastic reaction in a nonhomogeneous semi-elliptical elastic plate heated sectionally on the upper side of the semi-elliptic region. It has been assumed that the thermal conductivity, calorific capacity, elastic modulus and thermal coefficient of expansion were varying through thickness of the nonhomogeneous material according to Kassir’s nonhomogeneity relationship. The transient heat conduction differential equation is solved using an integral transformation technique in terms of Mathieu functions. In these formulations, modified total strain energy is obtained by incorporating the resulting moment and force within the energy term, thus reducing the step of the calculation. The thermal deflection equation derived from the Berger approach is compared with Von Karman approaches, and its maximum normal stresses are determined. The numerical calculation is performed over the metal-metal based composite and graphically portrayed. Furthermore, by applying limiting conditions, the semi-elliptic region can be degenerate into a semi-circular plate. Results reveal that the highest tensile stress exists on the semi-circular core relative to the semi-elliptical core, suggesting the propagation of low heating due to insufficient heat penetration into the elliptic surface