Defected Ground Structure Multiple Input-Output Antenna For Wireless Applications

In this paper, the investigation of a novel compact 2 × 2, 2 × 1, and 1 × 1 Ultra-Wide Band (UWB) based Multiple-Input Multiple-Output (MIMO) antenna with Defected Ground Structure (DGS) is employed. The proposed Electromagnetic Radiation Structures (ERS) is composed of multiple radiating elements. These MIMO antennas are designed and analyzed with and without DGS. The feeding is introduced by a microstrip-fed line to significantly moderate the radiating structure’s overall size, which is 60 × 40 × 1 mm. The high directivity and divergence characteristics are attained by introducing the microstrip-fed lines perpendicular to each other. And the projected MIMO antenna structures are compared with others by using parameters like Return Loss (RL), Voltage Standing Wave Ratio (VSWR), Radiation Pattern (RP), radiation efficiency, and directivity. The same MIMO set-up is redesigned with DGS, and the resultant parameters are compared. Finally, the Multiple Input and Multiple Output Radiating Structures with and without DGS are compared for result considerations like RL, VSWR, RP, radiation efficiency, and directivity. This projected antenna displays an omnidirectional RP with moderate gain, which is highly recommended for human healthcare applications. By introducing the defected ground structure in bottom layer the lower cut-off frequencies of 2.3, 4.5 and 6.0 GHz are achieved with few biological effects on radio propagation in human body communications. The proposed design covers numerous well-known wireless standards, along with dual-function DGS slots, and it can be easily integrated into Wireless Body Area Networks (WBAN) in medical applications. This WBAN links the autonomous nodes that may be situated either in the clothes, on-body or beneath the skin of a person. This system typically advances the complete human body and the inter-connected nodes through a wireless communication channel.     

Synthesis, characterization and electrical conductivity studies on A3Bi2P3O12 (A = Na, K) materials

Crystalline Na₃Bi₂P₃O₁₂, K₃Bi₂P₃O₁₂ and glassy K₃Bi₂P₃O₁₂ compounds were prepared by solid-state reaction method. The prepared samples are characterized by X-ray powder diffraction, Fourier transform infrared spectroscopy and differential scanning calorimetry. The crystalline materials are found to be orthorhombic. The electrical conductivity measurements on the crystalline and glassy samples show that at ∼373 K, the σ_DC for crystalline K₃Bi₂P₃O₁₂ (0.81 × 10⁻⁸ S/cm) is about two orders of magnitude higher than the corresponding glassy phase (1.25 × 10⁻¹⁰ S/cm). The scaling results show that the conductivity relaxation mechanism is independent of temperature.     

Impact of Mutual Coupling on Adaptive Switching Between MIMO Transmission Strategies and Antenna Configurations

Adaptive switching between multiple-input multiple-output (MIMO) transmission strategies like diversity and spatial multiplexing is a flexible approach to respond to channel variations. It is desirable to obtain accurate estimates of the switching points between these transmission schemes to realize the capacity gains made possible by adaptive switching. In this paper, it is shown that the accuracy of switching point estimates for switching between statistical beamforming and spatial multiplexing is improved by taking into account the effects of mutual coupling between antenna array elements. The impact of mutual coupling on the ergodic capacities of these two transmission strategies is analyzed, by deriving expressions for the same. Adaptive switching between combinations of transmission strategies and antenna array configurations (using reconfigurable antenna arrays) is shown to produce maximum capacity gains. Expressions for the switching points between transmission strategies and/or antenna configurations, including mutual coupling effects, are derived and used to explore the influence of mutual coupling on the estimates. Finally, measurements taken from reconfigurable rectangular patch antenna arrays are used to validate the analytical results.     

Mass Transfer,Kinetic, Equilibrium,and Thermodynamic Study on Removal of Divalent Lead from Aqueous Solutions Using Agrowaste Biomaterials,Musa acuminata,Casuarina equisetifolia L., and Sorghum bicolor

Theoretical Foundations of Chemical Engineering - Three distinct agricultural waste materials, viz., casuarina fruit powder (CFP), sorghum stem powder (SSP), and banana stem powder (BSP) were used...     

Modified spider monkey optimization algorithm based feature selection and probabilistic neural network classifier in face recognition

This paper proposes a novel and robust predictive method using modified spider monkey optimization (MSMO) and probabilistic neural network (PNN) for face recognition. The limitation of the traditional spider monkey optimization (SMO) approach to obtaining an optimal solution for classification problems is overcome by enhancing the performance of SMO by modifying the perturbation rate with a non-linear function, thereby improving the convergence of SMO. The framework comprises image preprocessing, feature extraction using dual tree complex wavelet transform (DT-CWT), feature selection using the modified spider monkey optimization algorithm (MSMO), and classification using PNN. The proposed method is tested on the Yale and AR Face datasets. Experimental outcomes reveal that the proposed framework attain an accuracy of 99.4% with appreciable sensitivity, specificity, and G-mean. To examine the efficacy of MSMO, parametric studies are conducted, which showed that MSMO converges faster with high fitness when compared to similar evolutionary algorithms like Genetic Algorithm (GA), Grey Wolf Optimization Algorithm (GWO), Particle Swarm Algorithm (PSO), and Cuckoo Search (CS) in selecting the optimal feature set. The MSMO-PNN method outperforms similar state-of-the-art methods, which reveals that the method proposed is competitive. The proposed model is robust to Gaussian and salt–pepper noise, obtaining the highest accuracy of 97.89% for varied noise density and variance.     

Selection of geometry for nonlinear rheology using large amplitude oscillatory shear: Poly (vinyl alcohol) based complex network systems

Oscillatory rheology is a common technique to characterize the linear and nonlinear mechanical response of complex materials. The present work studies two crosslinked systems of poly(vinyl alcohol) (PVA): physically crosslinked PVA-Borax, and glutaraldehyde (GA) based chemically crosslinked PVA-hyaluronic acid (HA) gel. Both exhibit nonlinear viscoelasticity with characteristic intracycle mechanisms during large amplitude oscillatory shear (LAOS), owing to H-bonding (physical) and covalent (chemical) interactions respectively, unlike PVA solutions/vinyl polymer melts. Parallel plate (PP) geometry is commonly utilized for rheology of crosslinked systems due to flexible gaps, and ease to retain exact material shapes. Unlike the widely employed cone and plate (CP) geometry for LAOS analysis, the inherent deformation and flow fields are not uniform in PP, which manifests as qualitative difference in the response of the material within the two geometries. A quantitative dissimilarity in the response of PVA based crosslinked systems is demonstrated in this work. Three approaches for PP correction from literature are explored to obtain a geometry independent response of the systems. Therein, the true stresses are computed from the apparent stresses via torque balance, their harmonics, and harmonic ratios based single-point correction. The first two are shown to have limited application, owing to their implicit assumption of geometry independence in the linear regime. The third approach is found to be effective upto medium strain amplitudes. We outline these shortcomings, and present guidelines to analyze PP LAOS results for the two PVA systems. The analysis can be generalized for the broader class of complex network systems' nonlinear rheology.