Growth and physiochemical characterization studies on 4-chloro-2-nitroaniline nonlinear optical single crystals

The non-centrosymmetric space group organic nonlinear optical single crystal of 4-chloro-2-nitroaniline (4Cl2NA) was developed by slow evaporation method at 40 °C. Grown 4Cl2NA was monoclinic structure with Pc space group which was recognized by single-crystal XRD analysis. An intermolecular contact of 4Cl2NA was visually analysed by Hirshfeld surface analysis. Active functional groups and their respective vibrations were identified by FTIR and FT-Raman spectral analysis. Optical properties were evaluated by UV–Visible spectral analysis. Thermal TG/DTA thermogram analysis and mechanical Vickers hardness analysis revealed that the synthesis material was thermally stable up to 115 °C and mechanical work hardness coefficient (n?=?2.98) confirmed the grown crystal was soft material. Laser beam-irradiated LDT analysis expressed the laser utility limitation of the 4Cl2NA crystal. The NLO second harmonic generation efficiency was tested by Kurtz Perry powder method.

     

Review on Dynamic Bandwidth Allocation of GPON and EPON

The passive optical network (PON) technology has been drastically improved in recent years. In spite of using the optical technology, the utilization of the entire bandwidth is a very challenging task. The main categories of PON are the Ethernet passive optical network (EPON) and gigabit passive optical network (GPON). These two networks use the dynamic bandwidth allocation (DBA) algorithm to attain the maximum usage of bandwidth, which is provided in the network dynamically according to the need of the customers with the support of the service level agreement (SLA). This paper will provide a clear review about the DBA algorithm of both technologies as well as the comparison.     

Implementation of Extra Efficient Bandwidth Utilization Dynamic Bandwidth Allocation Algorithm to Support Differentiated Service Classes in XGPON

Wireless Personal Communications - The Dynamic Bandwidth Allocation (DBA) algorithm is required for efficient bandwidth utilization in XG-PON. The majority of existing DBA algorithms do not make...     

On the interfacial adhesion of fiber metal laminates using surface modified aluminum 7475 alloy for aviation industries – a study

Abstract

Aluminum-based hybrid laminates are used extensively during the fabrication process of structural components in aviation industries due to its light weight and mechanical properties. A majority of airframe components are usually fitted with adhesion joints and, hence, surface adhesion has a great deal with surface and subsurface properties. To promote adhesion between substrates, various surface activating techniques could be followed. The main objective of this work is to enhance the interfacial adhesion strength between the thin aluminum alloy (AA 7475) and glass fiber. Experimentation was carried out to monitor the increase in the interfacial adhesion, by investigating the change in surface free energy which is influenced by the effect of surface etching. Aluminum sheets were treated using alkali (NaOH), iron (III) sulfate (Fe₂(SO₄)₃) and potassium dichromate (K₂Cr₂O₇). Etching effects were analyzed using water contact angle (W_CA), profilometry, scanning electron microscope (SEM images), X-ray diffractometer (XRD) and Fourier transformed infrared spectroscopy (FTIR-ATR). Tensile strength testing was done to evaluate the interfacial adhesion strength. The outcome of experimentation proves that, iron (III) sulfate treated condition laminates have higher tensile strength and it has also increased the interfacial adhesion.     

NLCC controller for SEPIC-based micro-wind energy conversion system

The growth of the power industry is gaining greater momentum as the usage of the non-conventional energy sources that include fuel, solar, and wind energies, increases. Wind energy conversion systems (WECSs) are gaining more popularity and are expected to be able to control the power at the output. This paper describes the current control (CC), non-linear carrier charge control (NLCCC), and fuzzy logic control (FLC) applied to the single-ended primary inductor converter (SEPIC)-based WECS. The current controller has an inherent overcurrent protection with better line noise rejection. The pulses for the switch of the SEPIC are obtained by comparing the current flowing through it with the virtual current reference. FLC is also investigated for the micro-wind energy conversion system (μWECS), since it improves the damping characteristics of WECS over a wide range of operating points. This cannot attain the unity power factor rectification. In this paper, NLCCC is proposed for high-power factor rectifier-based SEPIC in continuous conduction mode (CCM) for μWECS. The proposed converter provides an output voltage with low input current ripple due to the presence of the inductor at the input side. By comparing the signal proportional to the integral of switch current with a periodic non-linear carrier wave, the duty ratio of the converter switch is determined for the NLCC controller. By selecting the shape of the periodic non-linear carrier wave the input-line current can be made to follow the input-line voltage. This work employs a parabolic carrier waveform generator. The output voltage is regulated for changes in the wind speed. The results obtained prove the effectiveness of the NLCC controller in improving the power factor.     

Factorization-based active contour segmentation and pelican optimization-based modified bidirectional long short-term memory for ovarian tumor detection

This paper proposes a novel three-dimensional convolution neural network-based modified bidirectional long short-term memory with pelican optimization (3D CNN based MBiLSTM with PO) algorithm for multiclass ovarian tumor detection. Initially, the International Collaboration on Cancer Reporting endometrial cancer dataset images are provided in pre-processing phase, which uses a pre-emphasis filter to process the input image. In the segmentation phase, pre-processed data is then partitioned into diverse subgroups (i.e., pixels), which minimizes the complexity of images. In this paper, a factorization-based active contour technique is employed in the effective segmentation of images. The segmented features are then extracted and classified using the 3D CNN-MBiLSTM with PO algorithm. Finally, the experimental results are conducted and compared with various other approaches for various performance metrics. Each metric is evaluated with respect to the different number of iterations. The accuracy, sensitivity, and specificity have reached a higher value of 98.5%, 96%, and 98.25%, respectively.