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Corrosion of structural metals is a universal problem that causes economic and environmental damage every year due to the gradual failure of conventional protective coatings over time. In the past, graphene has emerged as a promising anticorrosive material owing to its unique properties such as chemical inertness, impermeability, and high conductivity, although scalability is still a big issue. This chapter outlines the utility and recent advances in graphene and graphene-derived materials containing polymer-based anticorrosive coatings. Additionally, an overview of pure graphene corrosion protective coating is also given. The potential applications of various polymer-graphene composites in the field of metal corrosion protection and their viability and challenges in near-future applications are also discussed.

Polyacrylonitrile copolymers with different molecular weights (Mws) are synthesised by aqueous free-radical redox polymerisation technique. Polyacrylonitrile (PAN) and lignin-blended solutions are prepared in dimethyl sulphoxide solvent by varying the polyacrylonitrile/lignin content. The effect of lignin addition to PAN copolymer having different weight-average Mws on the rheological properties is explored. Rheological measurements indicate that the solution viscosity reduces with the increase in the lignin content. The Cole–Cole plot or Han plot and Casson plot are used to characterise the solution homogeneity. The slope value of the plot suggests that the molecular-level homogeneity of the solution is not affected much by the addition of lignin. Thermal-induced gelation of concentrated solution has been rheologically investigated to avoid overheating of solution during the dissolution, storage and transportation for further wet spinning process.

Polyacrylonitrile copolymer (PAN) fiber and PAN/lignin (PL) fiber were wet spun from the PAN copolymer solution and PAN/Lignin blend solution using dimethyl sulphoxide (DMSO) solvent. A blend of 90% by weight (wt %) PAN terpolymer and 10wt% lignin dissolved in DMSO was used in wet spinning of PL fiber. Viscoelastic properties of PAN solution and PAN/lignin solution in DMSO were determined by rheometer. The properties of precursor fiber with and without lignin were evaluated by differential scanning calorimetry (DSC), Fourier transform infrared spectroscopy (FTIR) and mechanical testing. The diffusion of lignin out of coagulated filament was observed during wet spinning of PL solution and was quantitatively estimated by UV–Vis studies. DSC results showed that blending lignin with PAN copolymers can improve the thermal oxidation performance of the precursor fiber and accelerate the thermal stabilization process. A schematic illustration has been deduced for the decrease in tensile strength of PL fiber compared to that of PAN fiber.

Personal protective equipment (PPE) Coverall is an essential protective garment for frontline healthcare workers involved in mitigation of COVID-19. Comfort and safety are the prime theme of design...

Classification is an important technique in data mining which is applied in many fields including medical diagnosis to find diseases. In this research work, the multi-linear regression algorithm is used to find the possibilities of occurrence of diabetes. This research work would help the developers to identify the characteristics and flow of algorithms. This implementation helps the diabetalogist to make decision quickly. The explict outcome of the performance of the algorithm is reported for the chosen data.

Objective: Predict the total traffic count of streaming data in various routes to reduce traffic congestion and informing public about current traffic condition by displaying it in dashboard. Analysis: Real-time traffic monitoring can be made with the help of sensor connected devices, it generates huge volume and high speed data, Apache Kafka and Spark streaming engine is used for Processing these data. Findings: In existing system Traffic is predicted by deploying sensors in traffic signal lane and Apache hadoop used for processing data, it is batch processing system takes more time to process the data. In Proposed system total count of traffic predicted by using connected vehicles and Apache spark is used for processing live streaming data, by using spring boot total count of traffic is displayed in dashboard. Improvement: Real-time traffic prediction is done with live streaming data, Apache spark process data in-memory and dashboard updated for every five seconds

Objective: To predict a suitable fertilizer that yields profitable results for a given plant soil combination with the help of Big Data analytics. A fertilizer is any material of natural or synthetic origin that is applied to soils or to plant tissues to supply one or more plant nutrients essential to the growth of plants. It is the basic source of agricultural crops that helps most of the farmers yield profitable result. The type of soil and the plant plays a vital role in production. Every combination of soil and plant are unique and they require different form of nutrients. So the type of fertilizer required for them also vary. Farmers may not know the exact requirement by the soil or plant until they get the result. Hence, farmer in one region may end up with good yield due to the right selection of fertilizer while farmer in a different region with same type of soil and plant yield improper result. Though, the surveys are useful to find out the right type of fertilizer in some weeks or months, it is not possible to conduct the survey on every plant soil type combination. Hence there is a need to regularly keep track of the fertilizers used by the farmers and make decisions based on them., {"references":["1.\tBig Data In Smart Farming – A Review \"Agricultural Systems\" Volume 153, May 2017, Pages 69–80 2.\tKarthika, K. P. Porkodi ,\"Fraud Claim Detection Using Spark\" International Journal of Innovations In Engineering Research and Technology ISSN: 2394-3696 Volume 4, Issue 2, Feb.-2017 3.\tKarthika, K. P. Porkodi,\" Automatic Monitoring And Controlling Of Weather Condition Using Big Data Analytics , International Journal Of Advanced Research In Computer And Communication Engineering Vol. 6, Issue 1, January 2017 4.\tKarthika, P. Gokulraj, S. Saravanan\" Prediction of Sales Using Big Data Analytics\" Journal Of Advances In Chemistry Vol 12, No 20 5.\tKarthika, S. Priyadharshini \" Survey On Location Based Sentiment Analysis Of Twitter Data\" © 2017 IJEDR | Volume 5, Issue 1 | ISSN: 2321-9939 6.\tS Saravanan, V Venkatachalam, \"Advance Map Reduce Task Scheduling Algorithm Using Mobile Cloud Multimedia Services Architecture\" Ieee Digital Explore, Pp21-25, 2014. 7.\tS Saravanan, V Venkatachalam, \"Enhanced Bosa For Implementing Map Reduce Task Scheduling Algorithm\" International Journal Of Applied Engineering Research, Vol 10(85),Pp60-65,2015. 8.\tD.Umapriya, I. Karthika \"A Gis -Based Framework For Catastrophe Management\", International Journal Of Modern Trends In Engineering And Science Volume 3 Issn No: 2348-3121 2016 9.\tKarthika \",Safeguarding Scada Network By Captious State Based Filter\", International Journal Of Innovative Research In Computer And Communication Engineering Volume 2 Special Issue 1 –ISSN (Online): 2320-9801 2014 10.\tBennett, 2015 J.M. Bennett agricultural Big Data: Utilisation To Discover The Unknown And Instigate Practice Change farm Policy Journal, 12 (2015), Pp. 43–50 11.\tFujitsu Rolls Out Cloud-Based Big Data Platform For Farmers Fiercecio (2012) Http://Www. Fiercecio.Com/Story/Fujitsu-Rolls-Out-Cloud-Based-Big-Data-Platform-Farmers/2012-07-19 (Accessed: 7 May 2015) 12.\tCarolan, 2016, M. Carolan Publicising Food: Big Data, Precision Agriculture, And Co-Experimental Techniques of Addition Social Rural (2016)"]}

Objective:To reduce the fraud claims in health insurances companies and to improve outcomes in health care industry Analysis:In the existing system,Apache hadoop and Apache hive is used for processing data,it is a batch processing syste m. In proposed system,Apache spark is used for processing streaming data. Findings:EHR record is used as data source,it contains unique id for patients across world,so it is very easy to detect fraud claim with help of patientid. Apache spark processing streaming data on regular basis. But in existing system Apache hadoop and Apache hive takes hours of time to process the stored data. Improvement:Rule based model machine learning algorithm is used for detecting and automating the fraud claim and Apache spark is used for fast processing data,so it is more accurate and fast. https://www.ijiert.org/paper-details?paper_id=140995

Polyol mediated synthesis for the preparation of tungsten trioxide and titanium doped tungsten trioxide has been reported. The reaction was carried out using chlorides of tungsten and titanium in diethylene glycol medium and water as the reagent for hydrolysis at 190 deg. C. Formation of a blue coloured dimensionally stable suspension of the precursor materials was observed during the course of the reaction. The particle sizes of the precursor materials were observed to be around 100 nm. The precursor materials were annealed to give tungsten trioxide and titanium doped tungsten trioxide. The precursor materials were characterised using TGA/DTA, FT-IR, optical spectra, SEM, TEM and powder XRD methods. It was observed that the doping of titanium could be effected at least up to 10% of Ti in WO{sub 3}. The TGA/DTA studies indicated that WO{sub 3-x}.H{sub 2}O is the dominant material that formed during the polyol mediated synthesis. The XRD data of the annealed samples revealed that the crystalline phase could be manipulated by varying the extent of titanium doping in the tungsten trioxide matrix.

Phosphosilicate molecular precursor for the synthesis of NASICON, natrium super ionic conductor, Na1+xZr2SixP3−xO12 (x = 1 and 2) has been devised and prepared by the hydrolysis of tetraethoxysilane (TEOS) employing sodium phosphate solution. The molecular precursor was reacted with Zr(OC3H7)4 in ethanol under solvolytic condition to yield nano precursor material of NASICON. This material was annealed at high temperature to yield phase-pure NASICON. The molecular precursor was characterized using 31P NMR, FTIR spectral data, powder XRD pattern and TG/DTA studies. The structure of the molecular precursor was deduced from the powder XRD data, which indicates the presence of edge sharing tetrahedral arrangement of −O−Si−O−P−O−Si− chain. The NASICON precursor material was characterized using TG/DTA, FTIR, TEM, SEM, MAS 31P NMR and XRD. The conductivity of the synthesized NASICON material was measured using the pellet annealed at 900 °C and was found to be 5.5 x10−3 S cm−1. The details on the preliminary inves...