Influence of calcium substitution on structural and electrical properties of substituted barium titanate

Ba_0.80−xCa_xPb_0.20Ti_0.90Zr_0.10O₃ ceramics (x = 0, 0.10 and 0.20) were synthesized by solid state reaction. Samples microstructure and dielectric, ferroelectric and piezoelectric properties were studied. Dielectric constant (?), coercive field (E_c), remanent polarization (P_r) and ratio of remanent to spontaneous polarization (P_r/P_s) were studied at different temperatures. Sample with x = 0.10 was found to have maximum and comparatively more stable P_r/P_s ratio over a wide temperature range. Dielectric loss was found to improve with increase in x whereas piezoelectric charge coefficient d₃₃ was found to decrease with increase in x.     

Quadratic Discriminant Analysis Based Ensemble Machine Learning Models for Groundwater Potential Modeling and Mapping

In this study, the AdaBoost, MultiBoost and RealAdaBoost methods were combined with the Quadratic Discriminant Analysis method to develop three new GIS-based Machine Learning ensemble models, i.e., ABQDA, MBQDA, and RABQDA for groundwater potential mapping in the Dak Nong Province, Vietnam. In total, 227 groundwater wells and 12 conditioning factors (infiltration, rainfall, river density, topographic wetness index, sediment transport index, stream power index, elevation, aspect, curvature, slope, soil, and land use) were used for this study. Performance of the models was evaluated using the Area Under the Receiver Operating Characteristics Curve AUC (AUC) and several other performance metrics. The results showed that the ABQDA model that achieved AUC?=?0.741 was superior to the other models in producing an accurate map of groundwater potential for the Dak Nong Province. The models and potential maps produced here can help policymakers and water resources managers to preserve an optimal exploit from these vital resources.

     

Robust Model Reference Adaptive Intelligent Control

In this paper a Neural Network based Model Reference Adaptive Control scheme (NNMRAC) is proposed. In this scheme, the controller is designed by using parallel combination of the conventional Model Reference Adaptive Control (MRAC) scheme and Neural Network (NN) controller. In the conventional MRAC scheme, the controller is designed to realize plant output converging to reference model output based on the plant which is linear. This scheme is used to control linear plant effectively with unknown parameters. However, it is difficult for a nonlinear system to control the plant output in real time applications. In order to overcome the above limitations, the NN-MRAC scheme is proposed to improve the system performances. The control input of the plant is given by the sum of the MRAC output and NN controller output. The NN controller is used to compensate the nonlinearities and disturbances of the plant that are not taken into consideration in the conventional MRAC. The simulation results clearly show that the proposed NN-MRAC scheme have better steady state and transient performances than those of the current adaptive control schemes. Thus, the proposed NN-MRAC scheme named as Robust Model Reference Adaptive Intelligent Control (RMRAIC) is found to be extremely effective, efficient and useful in the field of control system.     

Minimum assured fidelity and minimum average fidelity in quantum teleportation of single qubit using non-maximally entangled states

We study use of non-maximally entangled states (NME) in quantum teleportation (QT) of single qubit. We find that if NME states are written in the form ${| E \rangle =\sum_{j,k} {E_{jk} | j \rangle | k \rangle}}$ , where (j, k) = 0 and 1, and maximally entangled Bell-basis is used in measurement by the sender, the ??Minimum Assured Fidelity?? (the minimum value of fidelity for all possible information states) for QT is 2C/(1?+?C), where C is the concurrence of ${| E \rangle }$ given by C?=?2|det (E)| and E is the matrix defined by the coefficients E _jk . We also find the average of fidelity over various results of Bell-state measurement and its minimum value over all possible information states and discuss it for some special cases. We also show that, to evaluate quality of imperfect QT, minimum assured fidelity is a better measure than concurrence or minimum average fidelity.     

Volatile Ultrafast Switching at Multilevel Nonvolatile States of Phase Change Material for Active Flexible Terahertz Metadevices

Phase change materials provide unique reconfigurable properties for photonic applications that mainly arise from their exotic characteristic to reversibly switch between the amorphous and crystalline nonvolatile phases. Optical pulse based reversible switching of nonvolatile phases is exploited in various nanophotonic devices. However, large area reversible switching is extremely challenging and has hindered its translation into a technologically significant terahertz spectral domain. Here, this limitation is circumvented by exploiting the semiconducting nature of germanium antimony telluride (GST) to achieve dynamic terahertz control at picosecond timescales. It is also shown that the ultrafast response can be actively altered by changing the crystallographic phase of GST.  The ease of fabrication of phase change materials allows for the realization of a variable ultrafast terahertz modulator on a flexible platform. The rich properties of phase change materials combined with the diverse functionalities of metamaterials and all-optical ultrafast control enables an ideal platform for design of efficient terahertz communication devices, terahertz neuromorphic photonics, and smart sensor systems.     

Energy-efficient data transmissions in heterogeneous ultra-dense networks using a hybrid metaheuristic optimization

The heterogeneous ultra-dense network (UDN) is a complex network environment where the small cells (SCs) are densely populated to acquire data transmission. The UDN is mainly adopted to deal with the explosive growth of mobile data and its consequential energy consumption issues. The UDN consists of mobile users, restricting the SCs from offering seamless services as the movement may disrupt the transmissions. To provide an effective solution, this paper introduces an energy-efficient framework that enables effective data transmissions irrespective of the users' mobility. The proposed model considers the clustered SC deployment where the four-tiered architecture is adopted. The architecture includes a macro base station (BS), microcells, picocells, and femtocells. The SCs are responsible for transferring the data received from the mobile users to the macro BS. The proposed model introduces the hybrid algorithm called the firefly oriented multiverse optimization (FF-MVO) algorithm to identify the most optimal path for data transmission. This algorithm works iteratively to identify the optimal path to reach the macro BS for each transmission from the user. The proposed model is simulated in the network simulator 3 (NS3) platform, and the results are evaluated with the existing models. The outcomes proved that the proposed algorithm is more optimal than the other models in finding the optimal path to result in energy-efficient transmissions. The proposed method achieved an average energy consumption of 0.24 J, an average energy efficiency of 10.965 bits/s/J and an average network throughput of 33.907 Gbps.     

Doppler shift with Archimedes Optimization Algorithm for localizing unknown nodes in underwater sensor networks

The issue of underwater sensor network (UWSN) localization has led to the aim of techniques presented in recent years. In this paper, we develop Doppler shift with Archimedes Optimization Algorithm for localizing unknown nodes in UWSN. The projected method predicts that sink node plays a major function in managing the computational load contrasted with the remaining nodes in the network of underwater. This node localization is proceeding with frequency shifts of sound waves contrasted toward real, which are present once observer in addition source can be mobile as they do in a marine atmosphere. The proposed technique is utilized to compute the estimated position of an unknown sensor node; here Archimedes' optimization algorithm is utilized to reduce the error during localization of nodes in UWSNs. This proposed technique can be enhancing the accuracy of the localization of nodes in UWSNs. This proposed methodology can be implemented and evaluated with the help of performance metrics. To validate the proposed technique's efficiency, it is contrasted with conventional techniques like Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA).     

DABPR: a large-scale internet of things-based data aggregation back pressure routing for disaster management

In this paper, we propose a data aggregation back pressure routing (DABPR) scheme, which aims to simultaneously aggregate overlapping routes for efficient data transmission and prolong the lifetime of the network. The DABPR routing algorithm is structured into five phases in which event data is sent from the event areas to the sink nodes. These include cluster-head selection, maximization of event detection reliability, data aggregation, scheduling, and route selection with multi attributes decision making metrics phases. The scheme performs data aggregation on redundant data at relay nodes in order to decrease both the size and rate of message exchanges to minimize communication overhead and energy consumption. The proposed scheme is assessed in terms of packet delivery, network lifetime, ratio, energy consumption, and throughput, and compared with two other well-known protocols, namely “information-fusion-based role assignment (InFRA)” and “data routing for in-network aggregation (DRINA)”, which intrinsically are cluster and tree-based routing schemes designed to improve data aggregation efficiency by maximizing the overlapping routes. Meticulous analysis of the simulated data showed that DABPR achieved overall superior proficiency and more reliable performance in all the evaluated performance metrics, above the others. The proposed DABPR routing scheme outperformed its counterparts in the average energy consumption metric by 64.78% and 51.41%, packet delivery ratio by 28.76% and 16.89% and network lifetime by 42.72% and 20.76% compared with InFRA and DRINA, respectively.

     

Polarization independent quad‐bandpass frequency selective surfaces with wide‐band ratio

A single layer polarization independent quad‐bandpass frequency selective surface (FSS) with wide‐band ratio is demonstrated theoretically as well as experimentally. The proposed structure passes four frequency bands with wide band ratio. The proposed FSS design is implemented by incorporating alternate arrangement of four units which are rotated 90° clockwise to form a unit cell of metal over a FR4 substrate. The geometrical dimensions of proposed unit cell are optimized and arranged in such a way that the structure possesses the quad bandpass characteristic and aspect dimensions of one unit is 0.11λ × 0.11λ with respect to first resonant frequency. This FSS provides stable response for different angle of incidence in transverse electric (TE) mode and transverse magnetic (TM) mode. To validate the results proposed FSS array has been fabricated and measured in free space environment. The measured results are in good agreement with the simulated results. Excellent stability is also observed for different incident angle.