Effect of Sizes of Nano Ca3(PO4)2 on Mechanical and Thermal Properties of Polyurethane Foam Composites

Particular sizes of nano inorganic filler, Ca₃(PO₄)₂ were prepared by following the matrix mediated growth technique. Composite foams were prepared on addition of different concentration (0.5–2.5 wt.%) of nano size filler in a single–phase polyurethane matrix. The differential Scanning Calorimetry (DSC) for composite as well as pure polyurethane was done to ascertain the degree of interaction of filler with the structure of the matrix as active sites. The degree of cell formation increases on increase in amount of reduced size nano filler in the composites where as decrease in case of larger size filler in composites. The increment in specific gravity from 0.17–0.25 for reduced nano size filler and 0.17–0.18 in case of larger size filler makes a strong support for the increment of cell numbers. The significant enhancement 250% in compressive strength, and the reduction of cell sizes shown in optical photographs satisfies the reasons of increment in heat of fusion (ΔH) in DSC. The decrement in (ΔH) cal/g in case of larger size filler for curing shows the conduction of heat is more due formation of cells less in numbers results in reduction of rate of heating more. Thermal gravimetric analysis (TGA) was done to know the degradation behavior. The TGA results, shows increment in onset temperature and mid temperature of the first step degradation in case of larger size nano filler. Decrement of flammability from 0.47–13.14 sec/mm for reduced nano size filler and 0.47–8.23 sec/mm in case of larger size filler, show that the incorporation of nano particles not only improves the mechanical properties but also retards the flammability.     

Multimode vibration control of a flexible structure usingH∞-based robust control

This paper presents the experimental results of a robust control scheme to suppress the vibration of a flexible structure. The feedback controller is designed using the H_∞-based robust control theory. For this purpose, a flexible bridge tower connected with a crane structure is considered to control its first five vibration modes using a static state feedback controller. A five-degrees-of-freedom reduced-order lumped parameter mass model is derived by neglecting high-frequency vibration modes. The neglected vibration modes constitute the unstructured system uncertainties. An attempt has been made to reduce the unmodeled uncertainties by placing actuators and/or sensors at the node points of a neglected mode. The H _∞-based control law is able to suppress the low-order vibration modes without any spillover instability due to neglected modes. The proposed control scheme is also shown to be robust against parameter variations. The performance of the control scheme is verified both by simulation and experimental studies     

Interaction of the properties of individual cotton fibres in a blend

Yarn engineering plays an important role in producing fabric for particular use. It is a common practice that yarn properties are predicted from constituent fibre properties. Cotton properties being highly variable in nature attracted various scientists from all over the world to derive prediction equations. More than 200 articles have been published in this area. Most of these predictions are based on single cotton, whereas in practice, more than one cotton is mixed together to optimise cost and quality. This study reports the accuracy of using weighted average method to determine the properties of blended cottons. Also, a set of prediction equations, derived for single cotton, tried to predict the properties of blended cotton yarns. To increase the accuracy of predictions, a new set of equations have been derived for binary cotton-blended yarns.     

Combinational domain encryption for still visual data

Image data has distinct regions of different importance. This property of image data has extensively been used to develop partial encryption techniques, but it is still unnoticed for total encryption. Providing similar security level to data of varied significance consumes more computational resources. This necessitates the development of an encryption framework that considers data significance while implementing total encryption. This article proposes a new framework of combinational domain encryption that encrypts significant data in spatial domain and insignificant data in wavelet domain. Experiments have been performed to analyze the effect of proposed framework as compared to encryption technique in a single domain. Significant reduction in computational time has been observed without compromising on the security. Medical applications or security applications requiring fast computation would be benefitted by implementation of the proposed technique.     

AFM and photoluminescence studies of swift heavy ion induced nanostructured aluminum oxide thin films

E-beam evaporated aluminum oxide films were irradiated with 120 MeV swift Au⁹⁺ ions in order to induced nanostructure formation. Atomic force microscope (AFM) results showed the formation of nanostructures for films irradiated with a fluence of 1 × 10¹³ ions cm⁻². The particle size estimated by section analysis of the irradiated film was in the range 25-30 nm. Glancing angle X-ray diffraction (GAXRD) revealed the amorphous nature of the films. Two strong Photoluminescence (PL) emission bands with peaks at ∼430 nm and ∼645 nm besides a shoulder at ∼540 nm were observed in all irradiated samples. The PL intensity is found to increase with increase of ion fluence.     

Deep Learning Guided Double Hidden Layer Neural Synchronization Through Mutual Learning

Neural Processing Letters - In this paper, a Double Hidden Layer Neural Networks synchronization mechanism using Generative Adversarial Network (GAN) and mutual learning is used for the development...     

Non-linear weight adjustment in adaptive gamma correction for image contrast enhancement

Multimedia Tools and Applications - Image enhancement remains an intricate problem, crucial for image analysis. Several algorithms exist for the same. A few among these algorithms categorize images...     

A novel solution of enhanced loss function using deep learning in sleep stage classification: predict and diagnose patients with sleep disorders

Multimedia Tools and Applications - Sleep stage classification is important to accurately predict and diagnose patients with sleep disorders. Though various deep learning approaches have been...     

Faster Synchronization of Triple Layer Neural Network Using Nature Inspired Whale Optimization: A Key Exchange Protocol

Wireless Personal Communications - The secret key swap over protocol is developed using a Whale Optimization-guided Three Layer Neural Networks coordination mechanism in this article. An adversary...     

Simultaneous Phenomenon of Particle Deposition and Reentrainment: Effects of Surface Roughness on Deposition Layer of Striped Pattern

Formation of particle deposition layers on rough wall surfaces was studied as a simultaneous phenomenon of particle deposition and reentrainment. The test powders used were alumina of micron sizes and the experiments were conducted under turbulent aerosol flows. After particle deposition and reentrainment reached an equilibrium state, deposition layer of a striped pattern was formed. The striped pattern was characterized by the interval and the thickness, which decreased when the roughness of the wall surface increased. Further, the striped deposition layers moved slowly downstream, and the velocity of the moving deposition layers decreased with the increase of the surface roughness. A moment balance model was used to explain the effect of the surface roughness on the velocity of the moving deposition layers.