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Amino acid added sodium ion-conducting Polyvinyl Alcohol (PVA), Polyvinyl Pyrrolidine (PVP) blend polymers are sythesised as thick films using solvent casting method. Prepared films are subjected to its characterization through FTIR, XRD and dielectric analysis. The electrical conductivity properties of SPEs are done for various frequencies and temperatures through an AC dielectric analysis. The ionic conductivity of 6.03 × 10–5 S/cm has been obtained as maximum for the higher concentration of aminoacid in blend polymer at room temperature. The way of increasing electrical conductivity due to temperature seems to obey the Arrhenius behaviour. The magnitude of the electric modulus peak has been observed for temperature variation and suggested the multiplicity phenomena in relaxation. Relaxation-activation energies calculated from electric modulus and tangent analysis are found to be same. From the cyclic voltammetry analysis, the electrochemical performances are observed. The fabricated electrochemical cell shows the potential window in the range of 2.16 V.

In this current study, Na+ ion conducting solid blend polymer electrolytes (NCSBPEs) based on polyethylene oxide (PEO) / polyvinyl pyrrolidine (PVP) / sodium nitrate (NaNO3) with the addition of different wt.% aluminum oxide (Al2O3) as filler were prepared using solution casting technique. The prepared solid blend polymer electrolytes are subjected to X-ray diffraction (XRD), Fourier transforms infrared (FTIR), and AC-impedance techniques. The complexation has been studied using X-ray diffraction (XRD) and Fourier transform infrared spectroscopy (FT-IR) measurements. AC-impedance spectroscopy has been used to analyze the ionic conductivity of the solid blend polymer electrolytes. The higher ionic conductivity $$(\sigma )$$ ~10–7 S/cm−1 is obtained for PEO: PVP: NaNO3 film and it was enhanced to ~ 10–5 S/cm−1 with the addition of Al2O3 filler at the ambient temperature. The dielectric and tan δ values were also calculated using the impedance analysis. In LSV (linear sweep voltammetry) studies, a broad electrochemical stability window was observed for polymer electrolytes besides CV (cyclic voltammetry) studies confirm the electrochemical behavior of the electrolytes.

Sodium-ion conduction-based blend polymer films have been developed with the incorporation of amino acid and L-phenylalanine for electrochemical storage device applications. The X-ray diffraction and Fourier transform infrared spectroscopy techniques are used to characterize the structural identification, which concerns enhancing the ionic movement and the existence of ions in blended polymer with the interaction of amino acid and salt. Variations in asymmetrical and symmetrical stretching vibrations of ions were investigated by the appeared partition peaks of FTIR in absorbance mode. Electrical impedance analysis has explained the microstructural properties of polymers through the complex impedance spectra. The enhanced electrical conductivity of 2.56 ×10−5 S cm−1 has been identified for 2.5 wt% of L-phenylalanine added blend polymer electrolyte system at ambient temperature. From the frequency dependence conductivity analysis, σdc values are calculated from Jonscher’s power law. In temperature-dependent conductivity analysis, two different types of activation energies are obtained for lower and higher temperatures. The dielectric and loss tangent analyses are also calculated and analysed the relaxation process based on the hopping mechanism. The electrochemical stability of higher conductivity solid polymer electrolytes is also verified by cyclic voltammetric analysis.

Solid polymer blend electrolytes (SPBEs) were prepared using poly(ethylene oxide) (PEO), poly(vinylidene fluoride-hexafluoro propylene) (P(VdF-HFP)) as polymer hosts, zinc triflate (ZnTr) as an electrolyte, and 1-butyl-3-methylimidazolium hexafluorophosphate (1B3MIHFP) as an ionic liquid (IL) via a conventional solvent casting technique. Various techniques like AC impedance spectroscopy, X-ray diffraction (XRD) analysis, scanning electron microscopy (SEM), and thermogravimetric/differential thermal analysis (TG/DTA) respectively were carried out for the prepared samples. From AC impedance spectroscopic studies, maximum ionic conductivity of 95.72 × 10−4 S cm−1 was observed for the system with 20 wt% of 1B3MIHFP at room temperature. Further, the temperature-dependent ionic conductivity study seems to obey Arrhenius behavior. Complexation and increase in degree of amorphicity for IL incorporated system was confirmed through XRD analysis. Ionic transference number was calculated by Wagner’s polarization technique, and it was found to be 0.991 for the sample which possessed maximum ionic conductivity. This value suggested that the charge transport in the polymer blend electrolyte matrix is mainly due to the Zn2+ ions. The dielectric properties of the SBPEs were also studied using the complex dielectric permittivity spectra, complex electric modulus spectra, and loss tangent analysis. Significant morphological changes were observed from SEM micrographs. From the TG-DTA analysis, thermal stability of the sample was found to be 245 °C.

In the modern years, multimedia security has become a prime agenda for secure transmission over unsecured channels due to the increase in digitalization of media. Cryptography is one of the techniques, which can be used for security of exchanged data. The visual cryptographic scheme generates numerous unreasonable shares of the image with specific information. The secret information hidden in the image can be retrieved by accumulating all the shares. The basic idea behind this cryptographic scheme is the encryption of image which hides the secret into m several image shares. By this process, it turns to be complex for the hackers to retrieve the original data of the image. Furthermore, to increase the confidentiality and privacy of the original image, there is in demand to make use of the efficient encryption algorithm. According to this, a new image encryption and decryption is developed using diffusion method with a combination of chaotic maps. Overall, the proposed visual cryptographic method is divided into three phases namely, i) Separation of color bands, ii) Generation of several shares and iii) Encryption & Decryption. Firstly, the color image is divided into three bands (R, G and B) and then various shares of the image are generated based on the pixel measures. After that, the encryption and decryption are done by using diffusion process associated with chaotic map. Experimental results of various analysis and computer simulation confirm that the new algorithm offers high security and is suitable for practical image encryption.

Image registration is computationally intensive and applied in a variety of applications, for example, multispectral classification, change recognition, climate prediction and multi-view analysis in GIS and medicine. There are three types of registration namely multi-view, multimodal and multi-temporal. In multi-view based registration, the images of the same scene taken at different viewpoints are analyzed and modeled for the requirement. Hence stereoscopic image sequences of the same view are acquired, and accurate comparison for the image classification is essential. This paper presents a robust method which has three steps. The first phase includes obtaining hyper spectral (satellite) images and preprocessing of them, the second period subdivides into image blocks for alignment, and the final step focuses on classification based on hyper graph structure using deep learning approach. For processing of satellite images, a new method linear iterative clustering and deep neural network classification are employed. Previous works in remote sensing applications involve training samples and hence prior knowledge of image sets which incurs more computational time. The implementation of this method shows an automatic, achieving better accuracy and dynamic reconfigurable image registration in reduced complexity. The mathematical model used is hidden markov chain model for clustering which provides region-wise feature construction for evaluating region shape and contextual information. The work yields classification accuracy of 94.12% which is far better than past outcomes in this engaged field of research. The execution of the usage is examined, a comparison is additionally influenced regarding false classification ratio, time complexity and clustering accuracy is demonstrated.

The complex patterns of the neuroimaging data are analyzed successfully with bio-medical imaging applications. The patients with/without AD can be discriminated effectively through several biomedical imaging modalities such as, sMRI, fMRI, PET and so on. In this paper, brain images from structural MRI (sMRI) are used for better categorization of 3 subjects namely, NC (Normal Control), MCI (Mild Cognitive Impairment) and AD (Alzheimer’s disease). Moreover, ambiguous training data employed for the discrimination of subjects may mislead the classifier to take incorrect decisions and in turn degrades the classification performance. In order to recover these hurdles, we propose an automated reliable system for the detection of AD affected patients accurately from the brain images of sMRI. The proposed system is a multi-stage system comprising four key phases namely, i) pre-processing, ii) feature extraction, iii) feature selection and iv) detection phase. In the initial phase, ROI regions related to Hippocampus (HC) and Posterior Cingulate Cortex (PCC) from the brain images are extracted using Automated Anatomical Labeling (AAL) method. In the feature extraction stage, important texture and shape features are extracted from HC and PCC involved in three brain planes. Nearly, 19 highly relevant AD related features are selected through a multiple-criterion feature selection method. It should be noted that, the class labels when explored manually consumes more time and turns to be an expensive process. Therefore, it is essential to construct an automatic method to identify irrelevant samples in the training data to enhance the decision-making process. With this in mind, at the detection phase, a novel classification technique is proposed by combining the Kernel fuzzy c-means clustering (i.e. unsupervised learning technique) and Back-propagation artificial neural network (i.e. supervised learning technique) to categorize NC, MCI and AD from the brain images of sMRI. This proposed KFCM based BPANN algorithm can improve the classification performance by removing the suspicious training samples. The proposed frameworks efficiency is evaluated with the ADNI subset and then to the Bordeaux-3 city dataset. The experimental validation of our proposed approach attains an accuracy of 97.63%, 95.4%, 96.4% for the most challenging classification tasks AD vs NC, MCI vs NC and AD vs MCI, respectively.

The Internet of Things (IoT) is the all-around trusted technology that associates natural objects to the web for giving straightforwardness and different functionalities and the hybrid power system has characterized as the power grid incorporated with an extensive network. With the change in innovation and developments needs to tackle the energy crises by utilizing hybrid renewable energy resources. The failure of electrical power in remote territories drives associations to investigate elective arrangements, for example, renewable energy power systems. The energy created by hybrid renewable energy sources are dependent on the variation and load demand, such a renewable power system must be equipped for fulfilling the necessities whenever and store the extra power for usage in deficiency situations. An independent renewable energy network to meet the coveted electric load with some sources, little excess power and minimal cost of energy. The essential goal of the design criteria is to limit the entire cost which incorporates initial, operational and support cost. In this work life-cycle cost (LCC), loss of load probability (LOLP) and loss of power supply probability (LPSP) have considered as the genuine factors and a Generous Transformational Optimization Algorithm (GTOA) has projected to pick the greatest possible configuration of a hybrid power framework. Internet of Things (IoT) conveyed in crossover control framework and gave a valuable proposition about assorted advances and norms of a renewable power source, and it additionally gives a review of a few applications and driving variables of a hybrid control framework. Simulation work done with MATLAB software and result helps the efficiency of the proposed technique and confirm that it is 97% efficiency than other ordinary strategies.

Nanocomposite polymer blend electrolytes composed of PEO–P(VdF-HFP)–LiClO4 were prepared for various concentrations of TiO2 nanofiller. All the composite electrolytes were subjected to ultrasonic irradiation for enhancing the ionic conductivity of the composite electrolytes. It was noted that the ultrasonic irradiated samples exhibited a higher ionic conductivity than the non-radiated samples. In addition, filler concentration in the complex was also optimized based on ionic conductivity, and it was noted that the sample containing 6 wt% showed maximum value about 1.451 × 10−5 S cm−1; however, this is lower than the value obtained from the irradiated samples (2.27 × 10−4 S cm−1). The dielectric, modulus and tangent loss behaviour of the samples were also estimated and discussed. Thermal and surface images studies were also carried out using TG/DTA and AFM studies, respectively. In addition, mobility and diffusion coefficient characteristics were also evaluated.

In the present work, PEO:P(VdF-HFP) polymer blend was prepared. The blend was complexed with lithium perchlorate (LiClO4), and nanosized strontium titanate (70.60 nm) SrTiO3 particles were dispersed into the complex in different weight ratios. Acetonitrile was used as solvent. The nanocomposite polymer blend electrolytes (NCPBEs) were prepared by the solvent-casting technique. Ionic conductivity of polymer blend electrolyte, PEO:P(VdF-HFP):LiClO4, was found to enhance at room temperature by the addition of nanoSrTiO3, and it was further confirmed through PL studies. Two ionic conductivity maxima, one at 2 wt% and another at 6 wt% of SrTiO3 were observed for NCPBEs. Out of the two peak maxima, the maximum ionic conductivity, 4.827 × 10−5 S cm−1, was obtained for 2 wt% SrTiO3. This is attributed to the increase in amorphicity of the polymer blend electrolytes, resulting from the polymer–salt–filler interactions. The crystalline and amorphous phases of the complex were identified through X-ray diffraction. The dielectric behavior was analyzed using complex dielectric permittivity ( $$\varepsilon^{*}$$ ), electric modulus ( $$M^{*}$$ ), and loss tangent. From the loss tangent spectra, relaxation times were evaluated, and the relaxation is found to be consistent with the conductivity of the samples. AFM and SEM analyses revealed significant changes in the surface morphology, which is in accordance with the ionic conductivity of the samples. The thermal stability was ascertained through TG/DTA studies.

The role of transition metals of the 3d series from V (Z = 23) to Zn (Z = 30) is investigated in modifying the crystallographic phase contents, microstructure and the dielectric properties of BaTiO3 ceramics containing ≤10 at% substituents. All the transition metals brought about the phase conversion to hexagonal BaTiO3 and the hexagonality is found to depend on Ba/Ti ratio as well as the processing conditions including the sintering temperature and the post sinter annealing. The er-T characteristics are modified with increasing hexagonality by way of the tremendous decrease in dielectric constant with broad and diminished emax for the mixed phase ceramics giving way to flat er-T curves for totally hexagonal specimens. Doping with >1% Zn2+ or ≥5% Mg2+ also render the ceramics completely hexagonal indicating that the crystal field effects of the 3d orbital electrons are not the cause for the conversion to hexagonal phase. Electron paramagnetic resonance (EPR) spectra of Mn-doped ceramics reveal the prevalence of defect complexes involving oxygen vacancies and different valence states of Mn occupying the Ti-sites within the corner-sharing as well as face-sharing octahedra present in hexagonal BaTiO3. EPR results also indicate defect complexes involving electron localization at Ti-sites and oxygen vacancies around the face-sharing octahedra. On annealing the ceramics in lower oxygen partial pressures at elevated temperatures leads to the reversion to corner shared (Ti3+–VO) defect complex accompanied by the conversion to cubic/tetragonal phase. The alterations in the oxygen vacancy-metal impurity defect complexes and the modifications in the oxygen close packing are the cause for the prevalence of hexagonal BaTiO3 at room temperature.

The influence of B2O3, and Al2O3 as segregative additives in modifying the ρ–T characteristics has been studied in BaTiO3 ceramics with positive temperature coefficient of resistance (PTCR). Reaction of Al2O3 at the grain boundary regions of BaTiO3 ceramics leads to the segregation of the secondary phase, BaAl6TiO12 resulting in broad PTCR jump, whereas B2O3 addition gives rise to steeper resistivity jump. Microstructure studies by SEM reveal the formation of coherent second phase layer of barium aluminotitanate surrounding the BaTiO3 grains. The EDX results shows varying Al to Ti ratio in the early stage of phase formation in BaAl6TiO12 resulting in electrically active layer around the BaTiO3 grains. The TiO2-excess melt formation results in lower resistivity for 2–4% Al2O3 containing n-BaTiO3 ceramics whereas at higher alumina contents, BaAl6TiO12 phase becomes dominant leading to higher resistivity in the sample. Complex impedance analyses support the three-layer regions, corresponding to the contributions from grain interior resistance (R g), grain boundary resistance (R gb), and that from secondary phase (R sec). Electron paramagnetic resonance spectroscopy (EPR) indicated barium vacancies, V Ba / as the major electron trap centers which are activated across the tetragonal-to-cubic phase transition. A charge trapping mechanism is proposed wherein the segregation of secondary phases bring carrier redistribution among the various acceptor states thereby affecting the electrical conductivity of n-BaTiO3 ceramics. The presence of Al3+–O−–Al3+ or Ti4+–O−–Al3+ type hole centers at the grain boundary layer (GBL) regions results in charge redistribution across the modified phase transition temperature due to symmetry-related vibronic interactions resulting in broad PTCR characteristics extending to higher temperatures.

High permittivity ceramics with $\epsilon_{eff} > 10^5$ can be realized from semiconducting $BaTiO_3$ by the two-step processing namely, sintering the donor doped samples in static air followed by electroding with the fired-on silver/glass composites. Doping with $Sb^5^+$ and $Bi^3^+$ not only enhances the grain conductivity but also increases the grain size $(10–60 \mu m)$, when sintered at $1370 ^oC$ in static air. The ceramic samples are electroded with the paste containing nanometer particles of silver dispersed in varied amounts of low melting $(600-900 ^oC)$ glass compositions $PbO + Bi_2O_3 + B_2O_3\pm SiO_2 \pm CuO$. High permittivities are obtained for these capacitors stable over a wider range of temperature and over a broad frequency range. The grain boundary layer effect superimposed with the contributions from the barrier layers formed during electroding, related to ceramic microstructure is proposed to be responsible for the unusual high permittivity in semiconducting $BaTiO_3$. The energy dispersive X-ray analyses indicate selective melting reactions at the grain boundary layers with higher concentrations of the low melting oxides at the grain boundaries near to the electrodes. Impedance spectroscopy on $BaTiO_3$ ceramics demonstrates that they are electrically heterogeneous with insulating grain boundaries together with the ceramic/electrode interface acting as barrier layers. On the basis of the symmetrical Schottky-barrier model of the grain boundary region, the barrier height $\phi$ and donor concentration $N_d$ of the grains were obtained by the modified $1/C^2-V$ plot. These modified boundary layer capacitors having high field strength withstandability can be used in a wide range of frequencies.

The Wigner-Seitz cell of a lattice inn-dimensional space displays the complete point group of such a lattice. The vertices of the cell when projected onto pseudo space can serve as the outer shape of acceptance domain or motif. This general procedure leads to acceptance domain or motif identical to those discussed in literature for primitive orthogonal hyperlattices.

The effect of DL α-lipoic acid, a potent antioxidant was studied in relation to certain erythrocyte membrane parameters in calcium oxalate stone forming rats. Induction of calcium oxalate lithiasis was done by feeding a diet containing 3% w/w sodium glycollate. Erythrocyte membrane (Na+, K+)-ATPase showed a significant decrease in stone formers whereas (Ca2+)-ATPase showed a significant increase. Lipoic acid administration brought about an elevation in the activity of (Ca2+)-ATPase. Changes in membrane (Mg2+)-ATPase was minimal. Membrane cholesterol and phospholipids were found raised significantly in lithogenic rats. The changes may be attributed to enhanced lipid peroxidative mechanisms and altered serum lipid profile observed in this group. Treatment with lipoic acid reduced membrane cholesterol levels. Phospholipids were also decreased moderately. The above observations suggest that lipoic acid administration to calculogenic rats reduces the erythrocyte strucutral changes observed in this condition.

Preharvest seed infection byAspergillus flavus and aflatoxin contamination in selected groundnut genotypes (fourA. flavus-resistant and fourA. flavus-susceptible) were examined in different soil types at several locations in India in 1985–1990. Undamaged mature pods were sampled at harvest and seed examined forA. flavus infection and aflatoxin content in two or more trials at ICRISAT Center on light sandy soils and red sandy loam soils (Alfisols), and on Vertisols, at Anantapur on light sandy soils, and at Dharwad and Parbhani on Vertisols. Rainy season trials (1985–1989) were all rainfed. Post-rainy season trials were irrigated; late-season drought stress (90 days after sowing (DAS) until harvest at 125 DAS) was imposed in the 1987/88 and 1989/90 seasons.A. flavus infection and aflatoxin contamination levels were much lower in seed of all genotypes from Vertisols than in seed from Alfisols across locations and seasons. Vertisols also had significantly lower populations ofA. flavus than Alfisols. There were no marked differences between light sandy soils and red sandy loam soils (Alfisols) in respect of seed infection byA. flavus and aflatoxin contamination. Significant interactions between genotypes and soil types were evident, especially in theA. flavus-susceptible genotypes. Irrespective of soil types,A. flavus-resistant genotypes showed lower levels of seed infection byA. flavus and other fungi than didA. flavus-susceptible genotypes. The significance of the low preharvest aflatoxin risk in groundnuts grown on Vertisols is highlighted.