Dynamic analysis of a composite moving beam

In this thesis, an attempt is made at studying the dynamic characteristics of a composite-moving beam.;The model considered is an overhang beam on simple supports oscillating in the longitudinal direction. The lateral response of the beam is studied due to an initial lateral deflection. The beam is made-up of laminated composite materials. Both symmetric and unsymmetrical lay ups are considered. Since unsymmetrical lay ups introduce bending-axial coupling, axial deformation needs to be considered also. First Order Shear Deformation theory (FSDT) is used to formulate the problem since transverse shear deformations are important for composite beams. When reducing laminate plate theory to corresponding beams, plane strain and plane stress assumptions are considered. Within the plane stress approximation, two ways of reduction from (x,y) equations to x-equations are possible. One is to set all y-related forces and moment resultants zero; other is to keep the cross resultants non zero. Also, as a comparison, results are obtained based on Classical Laminate Plate theory (CLPT). (Abstract shortened by UMI.)

EFFECT OF SOLUTIONISING TIME ON MECHANICAL PROPERTIES OF SQUEEZE CASTED AL 6082 – SICP COMPOSITE

Aluminum matrix composites refer to the class of light weight high performance aluminum centric material systems. The unique tailorability of the composite materials for the specific requirements makes these materials more popular in a variety of applications such as aerospace, automotive (pistons, cylinders, liners, bearings), and structural components, resulting in savings of material and energy. In this project, fabrication of Aluminum MMC by liquid metallurgy route (Squeeze Casting) is discussed in detail. The mechanical properties of 6082 aluminum alloy discontinuously – reinforced with fine particulates of SiCp reinforcement and solutionising time during heat treatment of the composite on hardness, density and impact strength have been evaluated. The cardinal reasons behind the variation in the hardness and impact strength have been discussed

A systematic literature review on spam content detection and classification

The presence of spam content in social media is tremendously increasing, and therefore the detection of spam has become vital. The spam contents increase as people extensively use social media, i.e ., Facebook, Twitter, YouTube, and E-mail. The time spent by people using social media is overgrowing, especially in the time of the pandemic. Users get a lot of text messages through social media, and they cannot recognize the spam content in these messages. Spam messages contain malicious links, apps, fake accounts, fake news, reviews, rumors, etc. To improve social media security, the detection and control of spam text are essential. This paper presents a detailed survey on the latest developments in spam text detection and classification in social media. The various techniques involved in spam detection and classification involving Machine Learning, Deep Learning, and text-based approaches are discussed in this paper. We also present the challenges encountered in the identification of spam with its control mechanisms and datasets used in existing works involving spam detection

Potential control of Echinochloa crus-galli (Barnyard grass) by Curvularia lunata as a mycoherbicide

Echinochloa crus- galli (Barnyard grass) is a world’s most harmful weed species.  Echinochloa crus-galli weed species compete with many economically important crops and causes serious problem in rice production. The virulent strain LD2 (leaf disease) of Curvularia lunata was screened out from 25 fungus strains isolated from the diseased leaves of barnyard grass (Echinochloa crus-galli). Greenhouse pot studies were conducted to the feasibility of the strain being as a mycoherbicide for barnyard grass control. The results of pathogenicity experiments showed that this strain was highly pathogenic to barnyard grass at the 2 to 3 leaf stages. Strain LD2 provided excellent barnyard grass control when it was applied at the concentration of 1×104, 1×106 conidia ml1. This strain was very safe to rice and the most plant species except wheat, barley and corn. Findings of this study indicated that this strain could be a potential mycoherbicide for barnyard grass control in paddy fields in the future. Keywords: Barnyard grass, Bioherbicides, Curvularia lunata, Echinochloa crus-galli, Mycoherbicide

Towards D2D-based opportunistic data relay service in partial not-spots

With the recent development of Device-toDevice (D2D) communication technologies, mobile devices will no longer be treated as pure “terminals”, but they could become an integral part of the network in specific application scenarios. In this paper, we introduce a novel scheme of using D2D communications for enabling data relay services in partial Not-Spots, where a client without local network access may require data relay by other devices. Depending on specific social application scenarios that can leverage on the D2D technology, we consider tailored algorithms in order to achieve optimised data relay service performance on top of our proposed networkcoordinated communication framework. The approach is to exploit the network’s knowledge on its local user mobility patterns in order to identify best helper devices participating in data relay operations. This framework also comes with our proposed helper selection optimization algorithm based on reactive predictability of individual user. According to our simulation analysis based on both theoretical mobility models and real human mobility data traces, the proposed scheme is able to flexibly support different service requirements in specific social application scenarios

A comparative study on chitosan nanoparticle synthesis methodologies for application in aquaculture through toxicity studies

Abstract Chitosan nanoparticles (CSNPs) have been recently used for various applications in aquaculture, especially as drug carriers. The aim of this study was to synthesise and investigate a superlative method of CSNP synthesis for application in aquaculture through aquaculture‐based toxicology screening methods. Two different methods were analysed: the first a direct ionic gelation method (A) and the other involving a low‐molecular‐weight chitosan microparticle intermediate method (B). Dynamic light scattering characterisation revealed that the CSNP particle sizes were 192.7 ± 11.8 and 22.9 nm from methods A and B, respectively. The LC50 values for brine shrimp toxicity were found to be 1.51 and 0.02 ppt in 24 h for methods A and B, respectively. Acute toxicity studies in Litopenaeus vannamei rendered LC50 values of 3235.94 and 2884.03 ppt in 24 h for methods A and B, respectively. Zebrafish toxicity studies revealed mortality rates of 21.67% and 55% at 20 mg/L concentration for methods A and B, respectively, with an increased expression of intracellular reactive oxygen species in method B. From these findings, it can be concluded that a comparatively reduced toxicity of CSNPs derived from ionic gelation method makes it more appropriate for application in aquaculture

Factors affecting innovation and imitation of ICT in the agrifood sector

Diffusion of innovations has gained a lot of attention and concerns different scientific fields. Many studies, which examine the determining factors of technological innovations in the agricultural and agrifood sector, have been conducted using the widely used Technology Accepted Model, for a random sample of farmers or firms engaged in agricultural sector. In the present study, a holistic examination of the determining factors that affect the propensity of firms to innovate or imitate, is conducted. The diffusion of ICT tools of firms which are engaged in the NACE 02/03 as well as in the NACE 10/11 classifications for 49 heterogeneous national markets is examined, using the Bass model. The innovation parameter is positively associated with rural income, female employment, export activity and education of farmers, while the imitation parameter is increased in countries whose societies are characterized by uncertainty avoidance

Device-level content management in LTE-A based network environments.

It has been envisaged that in future 5G networks user devices will become an integral part of the network by participating in the transmission of mobile content traffic typically through Device-to-device (D2D) technologies. In this context, we promote the concept of Mobility as a Service (MaaS), where the mobile network edge is equipped with necessary knowledge on device mobility in order to meet specific service requirements for clients via a small number of helper devices. In this thesis, we propose a MaaS paradigm based frameworks to address clients’ requirement with regards to content offloading service and connectivity relaying service via network assisted D2D communication framework. To address content traffic offloading, we present a device-level Information Centric Networking (ICN) architecture that is able to perform intelligent content distribution operations according to necessary context information on mobile user mobility and content characteristics. Based on such an architecture, we further introduce device-level online content caching and offline helper selection algorithms in order to optimise the overall system efficiency. In particular, this piece of work sheds distinct light on the importance of user mobility data analytics based on which helper selection can lead to overall system optimality. Based on representative user mobility models, we conducted realistic simulation experiments and modelling which have proven the efficiency in terms of both network traffic offloading gains and user-oriented performance improvements. In addition, we show how the framework can be flexibly configured to meet specific delay tolerance constraints according to specific context policies. With regard to connectivity relaying service, we introduce a novel scheme of using D2D communications for enabling data relay services in partial Not-Spots, where a client without local network access may require data relay by other devices. Depending on specific social application scenarios, this piece of work introduces tailored algorithms in order to achieve optimised data relay service performance. The approach is to exploit the network’s knowledge on its local user mobility patterns to identify best helper devices for participating in data relay operations. This framework is also supported with our proposed helper selection optimisation algorithm based on prediction of individual user mobility. According to our simulation analysis, based on both theoretical mobility models and real human mobility data traces, the proposed scheme is able to flexibly support different service requirements in specific social application scenarios

Device-level content management in LTE-A based network environments.

It has been envisaged that in future 5G networks user devices will become an integral part of the network by participating in the transmission of mobile content traffic typically through Device-to-device (D2D) technologies. In this context, we promote the concept of Mobility as a Service (MaaS), where the mobile network edge is equipped with necessary knowledge on device mobility in order to meet specific service requirements for clients via a small number of helper devices. In this thesis, we propose a MaaS paradigm based frameworks to address clients’ requirement with regards to content offloading service and connectivity relaying service via network assisted D2D communication framework. To address content traffic offloading, we present a device-level Information Centric Networking (ICN) architecture that is able to perform intelligent content distribution operations according to necessary context information on mobile user mobility and content characteristics. Based on such an architecture, we further introduce device-level online content caching and offline helper selection algorithms in order to optimise the overall system efficiency. In particular, this piece of work sheds distinct light on the importance of user mobility data analytics based on which helper selection can lead to overall system optimality. Based on representative user mobility models, we conducted realistic simulation experiments and modelling which have proven the efficiency in terms of both network traffic offloading gains and user-oriented performance improvements. In addition, we show how the framework can be flexibly configured to meet specific delay tolerance constraints according to specific context policies. With regard to connectivity relaying service, we introduce a novel scheme of using D2D communications for enabling data relay services in partial Not-Spots, where a client without local network access may require data relay by other devices. Depending on specific social application scenarios, this piece of work introduces tailored algorithms in order to achieve optimised data relay service performance. The approach is to exploit the network’s knowledge on its local user mobility patterns to identify best helper devices for participating in data relay operations. This framework is also supported with our proposed helper selection optimisation algorithm based on prediction of individual user mobility. According to our simulation analysis, based on both theoretical mobility models and real human mobility data traces, the proposed scheme is able to flexibly support different service requirements in specific social application scenarios