Adaptive Group Teaching Based Clustering and Data Aggregation with Routing in Wireless Sensor Network

Wireless Personal Communications - Nowadays, Wireless Sensor Networks (WSNs) is enhancing for different applications. Simultaneously, energy consumption for processing the tasks in most of the...     

Gamma ray-irradiated induced effects on SCN ligand-based MMTC single crystals for optoelectronic applications synthesized by SR method

Journal of Materials Science: Materials in Electronics - Nonlinear optical organometallic single crystal of manganese mercury thiocyanate (MMTC) has been grown by SR method in aqueous solution. The...     

A Review of Transmission Rate over Wireless Fading Channels: Classifications,Applications, and Challenges

To address the explosive traffic demands, the capacity of the fading channel is increasingly becoming a prime concern in the designing of the wireless communication system. The channel capacity is an extremely important quantity, since it allows the transmission of the data through the channel with an arbitrarily small probability of error. In other words, capacity dictates the maximum rate of information transmission, called as ‘capacity’ of channel, determined by the intrinsic properties of the channel and is independent of the content of the transmitted information. In this paper, we present a comprehensive survey of the existing work related to the channel capacity model over various fading channels. With an elaborated explanation of the theory of channel capacity, definitions of channel capacity based on the channel state information are reviewed. To compliment this, review of the technique to enhance the channel capacity is discussed and reviewed. An effective capacity model to overcome the channel capacity limitation is also explained. Furthermore, as the secure transmission of data is of utmost importance, to address this physical layer security model is also reviewed. We also summarize the work related to channel capacity in various types of wireless networks. We finally cover the future research directions, including less explored aspects of the channel capacity that can be studied to design efficient communication systems.

     

Domain Adaptation for POS Tagging with Contrastive Monotonic Chunk-wise Attention

Neural Processing Letters - Part of Speech (POS) tagging is a sequential labelling task and one of the core applications of Natural Language Processing. It has been a challenging problem for the...     

Extrinsic parameter's adjustment and potential implications in Plasmodium falciparum malaria diagnosis

Malaria is a major public health concern, affecting over 3.2 billion people in 91 countries. The advent of digital microscopy and Machine learning with the aim of automating Plasmodium falciparum diagnosis extensively depends on the extracted image features. The color of the cells, plasma, and stained artifacts influence the topological, geometrical, and statistical parameters being used to extract image features. During microscopic image acquisition, custom adjustments to the condenser and color temperature controls often have an influence on the extracted statistical features. But, our human visual system sub-consciously adjusts the color and retains the originality in a different lighting environment. Despite the use of appropriate image preprocessing, findings from the literature indicate that statistical feature variations exist, allowing the risk of P. falciparum misinterpretation. In order to eliminate this pervasive variation, the current work focuses on preprocessing the extracted statistical features rather than the prepossessing of the source image. It begins with the augmentation of series images for a microscopic field by inducing illumination variations during the microscopic image acquisition stage. A set of such image series is analyzed using a Nonlinear Regression Model to generalize the relationship between microscopic images acquired with variable ambient brightness and a specific feature. The projection point of the centroid feature onto the brightness parameter is identified in the model and it is denoted as the optimum brightness factor (OBF). Using the model, the feature correction factor (CF) is calculated from the rate of change of feature values over the interval OBF, and the brightness of the test image is processed. The present work has investigated OBF for selected image textural features, namely Contrast, Homogeneity, Entropy, Energy, and Correlation individually from its co-occurrence matrices. For performance analysis, the best state-of-the-art method uses selected texture as a subset feature to evaluate the effectiveness of P. falciparum malaria classification. Then, the impact of proposed feature processing is evaluated on 274 blood smear images with and without Feature Correction (FC). As a result, the “p” value is less than .05, which leads to the result that it is highly significant and the classification accuracy and F-score of P. falciparum malaria are increased.     

Large eddy simulation of flow over square cylinder arrays in an octagonal configuration at subcritical Reynolds numbers

In this study, fluid flow over an array of eight, 0.029 m × 0.029 m, square cross‐section cylinders in an octagonal configuration is studied numerically. The mean force coefficients (drag and lift) and the vortex formation characteristics of the array are calculated numerically by utilizing a three‐dimensional large eddy simulation mathematical model for turbulence. The numerical simulation is performed with commercial software ANSYS Fluent 19R1. To investigate the parametric influences, three spacings between the cylinders (0.07, 0.14, and 0.2 m), two array attack angles (0° and 15°), and two Reynolds numbers (4060 and 45 800) are considered. The results comprise flow patterns and force coefficients' variations with Reynolds numbers. The lift force of the downstream cylinder reaches its maximum at α = 15°, and the drag force of the upstream cylinders finds its peak at α = 0°. It is observed through velocity and viscosity contour plots that vortex formation length near the cylinder increases at higher Reynolds number. Velocity vector plots are also presented to show fluid flow behavior near the cylinder. Furthermore, the predicted mean forces on the cylinders are slightly different for different Reynolds numbers, spacings, and angles of attack.     

Fractional Gravitational Grey Wolf Optimization to Multi-Path Data Transmission in IoT

Wireless Personal Communications - The advancements of technology in the field of communication made WSN based IoT attractive and applicable to various areas. It is comprised IoT nodes that work on...     

Fabrication of dense Ce0.9Mg0.1P2O7-PmOn composites by microwave heating for application as electrolyte in intermediate-temperature fuel cells

In the present work, we report a method of fabrication of dense 10 mol% Mg²⁺-doped cerium pyrophosphate-phosphate (Ce_0.9Mg_0.1P₂O₇-P_mO_n; CMP-P) composites by microwave heat-treatment of the preformed Ce_0.9Mg_0.1P₂O₇ substrates in the presence of phosphoric acid. The composite was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS). The microwave heating at 375 °C for 5 min resulted in the formation of dense CMP-P composites which retained most of the pyrophosphate phase. The electrical conductivity was extracted from the EIS data and for the CMP-P composite prepared by H₃PO₄ loading for 10 h and microwave heat-treatment for 5 min it was found to be >10^?2 S m^?1 in 100–250 °C range with a maximum of 0.062 S cm^?1 at 190 °C, which was significant for its application as electrolyte in intermediate temperature fuel cells.     

Binary whale optimization algorithm: a new metaheuristic approach for profit-based unit commitment problems in competitive electricity markets

This article presents a metaheuristic approach, the binary whale optimization algorithm (BWOA), to solve complex, constrained, non-convex, binary-nature profit-based unit commitment (PBUC) optimization problems of a price-taking generation company (GenCo) in the electricity market. To simulate the binary-nature PBUC problem, the continuous, real-value whale position/location is mapped into binary search space through various transfer functions. This article introduces three variants of BWOA using tangential hyperbolic, inverse tangent (arctan) and sigmoidal transfer functions. The effectiveness of the BWOA approaches is examined in test systems with different market mechanisms, i.e. an energy-only market, and energy and reserve market participation with different reserve payment methods. The simulation results are presented, discussed and compared with other existing approaches. The convergence characteristics, solution quality and consistency of the results across different BWOA variants are discussed. The superiority and statistical significance of the proposed approaches with respect to existing approaches is also presented.     

ZnO–SnO2 nanocubes for fluorescence sensing and dye degradation applications

ZnO–SnO₂ nanocubes were used as promising material for efficient sensing of p-nitrophenol and faster photocatalytic degradations of dyes like methyl orange (MO), methylene Blue (MB) and acid orange 74 (AO74). ZnO–SnO₂ nanocubes were prepared by the facile solution process at 50 °C using Zn(NO₃)₂·6H₂O and SnCl₂·2H₂O as a precursor in the presence of ethylenediammine. The synthesized material was examined for its morphological, structural, crystalline, optical, vibrational, and compositional studies by using field emission scanning electron microscopy (FESEM), X-ray diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS) and photoluminescence spectroscopy. FESEM studies revealed the formation of well-defined ZnO–SnO₂ nanocubes where the structural examinations revealed the formation of a crystalline tetragonal rutile phase for SnO₂ with some crystal sites doped with Zn. The as-synthesized nanocubes were explored for their photocatalytic activities towards three different dye viz. MO, MB, and AO74. Practically, complete degradation of AO74 was seen within 4 minutes of photo-irradiation in the presence of 0.05 g ZnO–SnO₂ nanocubes. However, 97.17% and 41.63% degradations were observed for MB and MO within 15 and 60 minutes, respectively. All the dye degradation processes followed the pseudo-first-order kinetic model. Moreover, the as-synthesized nanocubes were utilized to fabricate highly sensitive and selective fluorescent chemical sensor for the detection of p-nitrophenol (PNP). ZnO–SnO₂ nanocubes showed a very low detection limit of 4.09 μM for the detection of PNP as calculated according to the 3σ IUPAC criteria. Further, the as-synthesized ZnO–SnO₂ nanotubes were found to be highly selective for p-nitrophenol as compared to the other two isomers.