A novel low‐cost high‐gain antenna design from cuboids and differential strips

This article proposed a novel broadband high‐gain antenna designed by suspended cuboids and differential shorting strips on a circular ground plane. The design structure of the proposed antenna is simple and all its components such as cuboids, strips, and ground plane are fabricated by a copper sheet of thickness 0.5 mm. The proposed antenna has measured ?10 dB impedance bandwidth (IBW) 45% (2.35‐3.7 GHz) with broadside gain of 10.1 ± 0.4 dBi over IBW. The use of differential strips in inner cuboid improved the cross polarization and enhanced the broadside gain. The measured antenna has low cross polarization is below 25 dB in the broadside direction over IBW. The proposed antenna has 1 dB gain‐bandwidth 53% (2.2‐3.8 GHz) in the broadside. The antenna has been fabricated and measured; the results show a good agreement with simulated results.     

Optimal Error Estimates of Two Mixed Finite Element Methods for Parabolic Integro-Differential Equations with Nonsmooth Initial Data

In the first part of this article, a new mixed method is proposed and analyzed for parabolic integro-differential equations (PIDE) with nonsmooth initial data. Compared to the standard mixed method for PIDE, the present method does not bank on a reformulation using a resolvent operator. Based on energy arguments combined with a repeated use of an integral operator and without using parabolic type duality technique, optimal $L^2$ L 2 -error estimates are derived for semidiscrete approximations, when the initial condition is in $L^2$ L 2 . Due to the presence of the integral term, it is, further, observed that a negative norm estimate plays a crucial role in our error analysis. Moreover, the proposed analysis follows the spirit of the proof techniques used in deriving optimal error estimates for finite element approximations to PIDE with smooth data and therefore, it unifies both the theories, i.e., one for smooth data and other for nonsmooth data. Finally, we extend the proposed analysis to the standard mixed method for PIDE with rough initial data and provide an optimal error estimate in $L^2,$ L 2 , which improves upon the results available in the literature.     

Group search optimiser-based optimal bidding strategies with no Karush–Kuhn–Tucker optimality conditions

Abstract

General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush–Kuhn–Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.     

Soil Moisture Flow Modeling with Water Uptake by Plants (Wheat) under Varying Soil and Moisture Conditions

A variably saturated soil moisture flow model is developed for planted soils with depth varying properties by incorporating a nonuniform macroscopic root water uptake function. The model includes spatial and temporal variation of the root density with dynamic root growth for simulating water uptake by plants along with the impact of soil moisture availability. The governing partial differential moisture flow equation integrated over the depth with a plant water uptake term is solved numerically by the implicit finite difference method using an iterative scheme. The model is first tested for barren soils for two profiles considering constant and depth varying soil characteristics under constant inflow condition. The results obtained are later tested with experimental data available in the literature. A nonuniform plant water uptake term is subsequently incorporated in the model and water uptake by wheat plants under different soil moisture availability conditions is studied. Finally, the moisture flow model is validated with field data of rain fed wheat (Triticum aestivum) using a dynamic root growth model for a layered root zone soil profile. The simulated soil moisture regime of the layered root zone shows a reasonably good agreement with the observed data.     

Using data mining synergies for evaluating criteria at pre-qualification stage of supplier selection

A company must purchase a lot of diverse components and raw material from different upstream suppliers to manufacture or assemble its products. Under this situation the supplier selection has become a critical issue for the purchasing department.The selection of suppliers depends on number of criteria and the challenge is to optimize selection process based on critical criteria and select the best supplier(s). During supplier selection process initial screening of potential suppliers from a large set is vital and the determination of prospective supplier is largely dependent on the criteria chosen of such pre-qualification. In the literature, many judgments based methods are proposed and derived criteria selection from the opinion of either the customers or the experts. All these techniques use the knowledge and experience of the decision makers. These methods inherit certain degree of uncertainty due to complex supply chain structure. The extraction of hidden knowledge is one of the most important tools to address such uncertainty and data mining is one such concept to account for such uncertainty and it has been found applicable in many scenarios. The proposed research aims to introduce a data mining approach, to discover the hidden relationships among the supplier’s pre-qualification data with the overall supplier rating that have been derived after observation of previously executed work for a period of time. It provides an overview that how supplier’s initial strength influence its final work performance.     

Thermal instability in a rotating porous layer saturated by a non-Newtonian nanofluid with thermal conductivity and viscosity variation

The stability of a non-Newtonian nanofluid saturated horizontal rotating porous layer subjected to thermal conductivity and viscosity variation is investigated using linear and nonlinear stability analyses. The model used for the non-Newtonian nanofluid includes the effects of Brownian motion and thermophoresis. The Darcy law for the non-Newtonian nanofluid of the Oldroyd type is used to model the momentum equation. The linear theory based on the normal mode method, and the criteria for both stationary and oscillatory modes are derived analytically. A weak nonlinear analysis based on the minimal representation of truncated Fourier series method containing only two terms is used to compute the concentration and thermal Nusselt numbers. The results obtained during the analysis are presented graphically.     

ΛCDM type Heckmann–Schuking model and Union 2.1 compilation

We study a ΛCDM type cosmological model in Heckmann-Schucking space-time, by using 287 high redshift (.3 ≤ z ≤ 1.4) SN Ia data on observed absolute magnitude along with their possible error from Union 2.1 compilation. We use the χ² test to compare Union 2.1 compilation observed data and the corresponding theoretical values of the apparent magnitude (m). It is found that the best fit value of (Ω _m )₀, (Ω_Λ)₀ and (Ω _σ )₀ are 0.2940, 0.7058 and 0.0002, respectively, and the derived model represents the features of an accelerating universe which is consistent with the recent astrophysical observations.     

Information-sharing and decision-making in networks of radiation detectors

A network of sensors observes a time-inhomo-geneous Poisson signal and within a fixed time interval has to decide between two hypotheses regarding the signal’s intensity. The paper reveals an interplay between network topology, essentially determining the quantity of information available to different sensors, and the quality of individual sensor information as captured by the sensor’s likelihood ratio. Armed with analytic expressions of bounds on the error probabilities associated with the binary hypothesis test regarding the intensity of the observed signal, the insight into the interplay between sensor communication and data quality helps in deciding which sensor is better positioned to make a decision on behalf of the network, and links the analysis to network centrality concepts. The analysis is illustrated on networked radiation detection examples, first in simulation and then on cases utilizing field measurement data available through a U.S. Domestic Nuclear Detection Office (dndo) database.     

Stability Analysis,Chaos Control of Fractional Order Vallis and El-Nino Systems and Their Synchronization

In this article the authors have studied the stability analysis and chaos control of the fractional order Vallis and El-Nino systems. The chaos control of these systems is studied using nonlinear control method with the help of a new lemma for Caputo derivative and Lyapunov stability theory. The synchronization between the systems for different fractional order cases and numerical simulation through graphical plots for different particular cases clearly exhibit that the method is easy to implement and reliable for synchronization of fractional order chaotic systems. The comparison of time of synchronization when the systems pair approaches from standard order to fractional order is the key feature of the article.