Design of a wideband microstrip antenna and the use of artificial neural networks in parameter calculation

This paper deals with the design of a multi-slot hole-coupled microstrip antenna on a substrate of 2 mm thickness that gives multi-frequency (wideband) characteristics. The Method of Moments (MoM)-based IE3D software was used to simulate the results for return loss, VSWR, the Smith chart, and the radiation patterns. A tunnel-based artificial neural network (ANN) was also developed to calculate the radiation patterns of the antenna. The radiation patterns were measured experimentally at 10.5 GHz and 12 GHz. The experimental results were in good agreement with the simulated results from IE3D and those of the artificial neural network. A new method of using a genetic algorithm (GA) in an artificial neural network is also discussed. This new method was used to calculate the resonant frequency of a single-shorting-post microstrip antenna. The resonant frequency calculated using the genetic-algorithm-coupled artificial neural network was compared with the analytical and experimental results. The results obtained were in very good agreement with the experimental results.     

Eradication of Barrett''s mucosa with argon plasma coagulation and acid suppression: immediate and mid term results

Microcapsules are used for the formulation of drug controlled release and drug targeting dosage forms. Encapsulated hydrophobic drugs are often applied as their solutions in plant oils. The uptake of the oils in the complex coacervate microcapsules can be improved by the addition of surfactants. In this study, soybean, olive and peanut oils were chosen as the representatives of plant oils. The well characterized complex coacervation of gelatin and acacia has been used to produce the microcapsules. The amount of encapsulated oil has been determined gravimetrically. The encapsulation of the oils was high (75-80%). When the surfactants with HLB values from 1.8 to 6.7 were used, the amount of encapsulated oil was high (65-85%). A significant decrease of the oil content in the microcapsules was found when Tween 61 with HLB = 9.6 had been added into the mixture. No oil was found inside the microcapsules from the coacervate emulsion mixture containing Tween 81 (HLB = 10) and Tween 80 (HLB = 15), respectively. The results of the experiment confirm the dependence of hydrophobic substance encapsulation on the HLB published recently for Squalan.     

Ageing studies of pineapple leaf fiber–reinforced polyester composites

This experimental study evaluated the water absorption characteristics of pineapple leaf fiber (PALF)–polyester composites of different fiber content. The degree of water absorption was found to increase with fiber loading. The mechanism of diffusion was analyzed and the effect of fiber loading on the sorption kinetics was studied. The diffusion coefficient was calculated and found to increase with fiber content. Studies were also made to correlate water absorption with the cross‐sectional areas of the specimens. The effects of ageing on the tensile properties and dimensional stability of PALF polyester composites were studied under two different ageing conditions. Ageing studies showed a decrease in tensile strength of the composites. The composite specimens subjected to thermal ageing showed only a slight deterioration in strength. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 94: 503–510, 2004     

Thermal error measurement and modelling in machine tools.: Part I. Influence of varying operating conditions

Thermal error in machine tools has been observed to be closely linked to the temperature of critical elements of the machine. It was found, in the experiments conducted herein, that there was a significant increase in the axis positioning error on account of an increase in the temperature of the machine elements due to continuous operation. However, it was also observed that the specific operating parameters of the test cycles carried out also significantly affected the positioning error. Different sets of operating parameters generated significantly different error values even though the temperature of the machine elements generated by those operating conditions was similar. As such, this observation forms a very important consideration in the development of a generic thermal error compensation system. It appears to indicate that such a system needs to be capable of evaluating the compensation depending upon the temperature values of the machine elements as well as account for the effect that different operating parameters induce upon the positioning error under the same thermal condition of the machine. This paper attempts to analyse the thermal behaviour of a three-axis vertical machining centre under the influence of various operating parameters and, through the experimental results obtained, point out and explain the effect of these parameters on the axis positioning error. This behaviour forms the basis of an improved modelling methodology that is presented separately in Part II of this paper.     

Equivalence of classicality and separability based on P phase–space representation of symmetric multiqubit states

Classical and quantum world views differ in peculiar ways. Understanding decisive quantum features—for which no classical explanation exist—and their interrelations is of foundational interest. Moreover, recognizing non-classical features carries practical significance in information processing tasks as it offers insights as to why quantum protocols work better than their classical counterparts. We focus here on two celebrated notions of non-classicality viz., negativity of P phase–space representation and entanglement in symmetric multiqubit systems. We prove that they imply each other.     

Discrete GWO Optimized Data Aggregation for Reducing Transmission Rate in IoT

The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced technologies. Early diagnosis of many diseases will improve the patient life. The cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things (IoT), Wireless Sensor Networks (WSN), Embedded systems, Deep learning approaches and Optimization and aggregation methods. The data generated through these technologies will demand the bandwidth, data rate, latency of the network. In this proposed work, efficient discrete grey wolf optimization (DGWO) based data aggregation scheme using Elliptic curve Elgamal with Message Authentication code (ECEMAC) has been used to aggregate the parameters generated from the wearable sensor devices of the patient. The nodes that are far away from edge node will forward the data to its neighbor cluster head using DGWO. Aggregation scheme will reduce the number of transmissions over the network. The aggregated data are preprocessed at edge node to remove the noise for better diagnosis. Edge node will reduce the overhead of cloud server. The aggregated data are forward to cloud server for central storage and diagnosis. This proposed smart diagnosis will reduce the transmission cost through aggregation scheme which will reduce the energy of the system. Energy cost for proposed system for 300 nodes is 0.34μJ. Various energy cost of existing approaches such as secure privacy preserving data aggregation scheme (SPPDA), concealed data aggregation scheme for multiple application (CDAMA) and secure aggregation scheme (ASAS) are 1.3 μJ, 0.81 μJ and 0.51 μJ respectively. The optimization approaches and encryption method will ensure the data privacy.     

Stochastic Gradient Boosting Model for Twitter Spam Detection

In today’s world of connectivity there is a huge amount of data than we could imagine. The number of network users are increasing day by day and there are large number of social networks which keeps the users connected all the time. These social networks give the complete independence to the user to post the data either political, commercial or entertainment value. Some data may be sensitive and have a greater impact on the society as a result. The trustworthiness of data is important when it comes to public social networking sites like facebook and twitter. Due to the large user base and its openness there is a huge possibility to spread spam messages in this network. Spam detection is a technique to identify and mark data as a false data value. There are lot of machine learning approaches proposed to detect spam in social networks. The efficiency of any spam detection algorithm is determined by its cost factor and accuracy. Aiming to improve the detection of spam in the social networks this study proposes using statistical based features that are modelled through the supervised boosting approach called Stochastic gradient boosting to evaluate the twitter data sets in the English language. The performance of the proposed model is evaluated using simulation results.

     

Deformation due to expanding ring load in modified couple stress thermoelastic diffusion in time and frequency domain

The two-dimensional problem of expanding ring load in a modified couple stress theory of thermoelastic diffusion with heat sources in time and frequency domains is investigated. The mathematical formulation prepared for thermoelastic diffusion solids with one and two relaxation times using Laplace and Hankel transforms. The displacements, stress components, temperature change, and chemical potential are obtained in a transformed domain. Numerical computation is performed for these quantities and the resulting quantities are shown graphically for the time and frequency domains. Comparisons are made with the results predicted by the two theories and different values of time and frequency. Particular cases of interest are also deduced.     

Biogenic synthesis,characterisation and antifungal activity of gum kondagogu‐silver nano bio composite construct: assessment of its mode of action

The biogenic synthesis of silver nanoparticles was achieved by using gum kondagogu (Cochlospermum gossypium), a natural biopolymer (Gk‐AgNPs). Synthesised nanoparticles were characterised by using UV–visible spectroscopy, inductively coupled plasma‐atomic emission spectrometer, X‐ray diffraction, transmission electron microscope techniques. The silver nano particle size determined was found to be 3.6 ± 2.2 nm. The synthesised Gk‐AgNPs showed antifungal activity and exhibited minimum inhibitory concentration and minimal fungicidal concentration values ranging from 3.5 to 6.5 µg mL⁻¹ against Aspergillus parasiticus (NRRL‐2999) and Aspergillus flavus (NRRL‐6513). Scanning electron microscopy–energy dispersive spectroscopy analysis revealed morphological changes including deformation, shrunken and ruptured mycelium of the fungi. At the biochemical level, the mode of action revealed that there was an elevated level of reactive oxygen species, lipid peroxidation, superoxide dismutase, and catalase enzyme activity. Increased oxidative stress led to increased outer membrane damage, which was confirmed by the entry of N ‐phenyl naphthylamine to the phospholipid layer of outer membrane and higher levels of K⁺ release from the fungi treated with Gk‐AgNPs. This study explores the possible application of biogenic silver nanoparticles produced from gum kondagogu as potent antifungal agents. The potent antifungal activity of Gk‐AgNPs gives scope for its relevance in biomedical application and as a seed dressing material.Inspec keywords: antibacterial activity, nanocomposites, silver, nanofabrication, nanoparticles, biomedical materials, polymers, visible spectra, ultraviolet spectra, atomic emission spectroscopy, X‐ray diffraction, transmission electron microscopy, scanning electron microscopy, microorganisms, X‐ray chemical analysis, enzymes, lipid bilayers, biomembranes, biomechanics, nanomedicineOther keywords: antifungal activity, gum kondagogu‐silver nanobiocomposite, Cochlospermum gossypium, natural biopolymer, UV‐visible spectroscopy, inductively coupled plasma‐atomic emission spectrometer, X‐ray diffraction, transmission electron microscope, fungicidal concentration, Aspergillus parasiticus, Aspergillus flavus, scanning electron microscopy, SEM‐energy dispersive spectroscopy, fungi deformation, ruptured mycelium, reactive oxygen species, lipid peroxidation, superoxide dismutase, catalase enzyme activity, oxidative stress, membrane damage, N‐phenyl naphthylamine, phospholipid layer, potassium ion release, biogenic silver nanoparticle, antifungal agent, seed dressing material, Ag