Volume 9 | Issue 6 |

 Abstract

The internship program is a resourcefulness which bridges the gap between the knowledge and its application through a series of interventions which enables the learners to obtain awareness and experience to the business. The program extends for a period of 10 weeks which provides a good opportunity to experience the practicality in terms of subjects studied. It also gives practical exposures. H & R Johnson (India) a division of prism cement limited manufacturers of exclusive brand of white body wall and floor tiles and fully vitrified tiles, is the trailblazer in the tile industry with a dominant presence all over the globe for over 100 years, the brand has gained the trust of over four generations. H & R Johnson (India) a private limited company was established in 1958 which currently owns and operates tile manufacturing plants at Pen (Maharashtra), Kunigal (Karnataka), Karaikal (Pondicherry),Dewas (Madhya Pradesh),Vijayawada (Andhra Pradesh). H & R Johnson (India) Kunigal plant came into existence in the year 1989 and commercial production was started in the year 1990. It has modernized plant with new technology equipments.

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A Study “ON EMPLOYEE ENGAGEMENT ACTIVITIES AT H & R JOHNSON (INDIA) A DIVISION OF PRISM CEMENTS

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 Abstract

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Lung infection detection, CT scan, Machine Learning, Respiration

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 Abstract

Now-a-days most of the applications are requires the effective security system for managing the transaction details and other information. Other than the CCTV security process, biometric systems are utilized in several application to monitor the people activities and helps to authenticate the person. Even though, the biometric systems are failing to authenticate the right person some times which reduces the efficiency of authentication system. For achieve this goal, in this paper dorsal vein biometric features are used to authenticate the user information. Initially, dorsal vein images are collected from different person, which are processed by applying the median filter that eliminates the noise from image. After that vein regions are located with the help of the deep learning approach which recognize the vein information using different layers. From the extracted vein region, various statistical features are derived that are processed by the intelligent classifier called ant colony optimized compositional neural network which train the features and authenticate the user information effectively. Then the efficiency of the system is evaluated using experimental results such as FAR, FRR and ERR.

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 Keywords

Biometrics system, authentication, Dorsal vein, Median filter, Deep learning approach, Intelligent machine learning technique.

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Phyllanthus amarus has long been used as a medicinal herb. This plant has been used to cure a variety of severe ailments traditionally, and it has been scientifically proven to be safe and effective against a variety of ailments. The aim of this research was to see whether the separated alkaloid rich fraction from P.amarus has any hepatoprotective property. We successfully isolated the alkaloid fraction from this plant and tested it on male albino rats suffering with D-galactosamine induced hepatitis. We looked at endogenous antioxidant enzymes in the liver tissue to see whether alkaloid fraction has hepatoprotective activity. The results showed that antioxidant enzymes such SOD, CAT, GR, GPx, and GSH levels were considerably higher in the alkaloid rich fraction that treated to hepatitis group, but they were lower in the hepatitis alone rat group. In addition, in the hepatitis group, however, GST enzyme activity and lipid peroxidation in the form of MDA were significantly higher, but these values were also considerably decreased in the alkaloid rich fraction treatment of hepatitis rats. In conclusion, the alkaloid-rich fraction separated from P.amarus displays hepatoprotective effects in the liver via boosting endogenous antioxidant enzymes. In future, the mechanism of action of the alkaloid fraction of P.amarus must be determined, as well as the isolation of individual alkaloid compounds.

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 Keywords

Phyllanthus amarus, Antioxidant enzymes, hepatoprotective, alkaloid-rich fraction, D-galactosamine

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 Abstract

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Covid-19, CT Scan, Machine Learning, Medical Images

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Renewable energy sources have become a popular alternative electrical energy source where power generation in conventional ways is not practical. In the last few years the photovoltaic and wind power generation have been increased significantly. In this study, we proposed a hybrid energy system which combines both solar panel and wind turbine generator as an alternative for conventional source of electrical energy like thermal and hydro power generation. A simple control technique which is also cost effective has been proposed to track the operating point at which maximum power can be coerced from the PV system and wind turbine generator system under continuously changing environmental conditions. The entire hybrid system is described given along with comprehensive simulation results that discover the feasibility of the system. The model is intended to be used as an optimization and design tool for such hybrid systems applied to organic constructions. After an error analysis it was determined that this model predicted quite interesting results compared to the experimental data under various conditions. It is important to indicate that this analysis has been carried out so that in future, these power generation systems can be exploited and applied more efficiently in areas far from the public electricity grid.

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 Keywords

Renewable energy, hybrid system, and photovoltaic

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The intent of this paper is to establish a model to classify outdoor images to different weather classes and then using this classification as basis of many actions that can be provided to driverless cars. While performing the literature survey about field related to weather prediction we found out that the best results for weather classification are obtained while using the CNN models. This paper proposes a method of implementing convolutional neural networks to get the desired result of classifying separate weather conditions into four classes, namely foggy, rainy, sunny and snowy. And according to the weather condition predicted, the project will provide the necessary actions that need to be taken by the driverless cars. Convolutional neural networks (CNNs) are widely accepted and acknowledged in the fields of image analysis, image recognition, video recognition, face recognition, image classification and activity detection. CNNs have images as their input; process those images; assign adaptive weights and biases to many features of the image; and then classify them into various categories.

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Convolutional neural networks, sequential model, model layers, image classification

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 Abstract

As the demand of energy is increasing day by day, so the ultimate solution to deal with these sorts of problems is just to implement the renewable sources of energy Humans are using the renewable energy which are solar, wind etc. but we still could not satisfy our power needs, because of that we have to generate electricity through each and every possible Ways.The objective of this work is to produce power through footsteps as a source of renewable energy that we can obtained while walking or standing on to the certain arrangements like footpaths, stairs, plate forms and these systems can be install specially in the more populated areas. In this project the force energy is produced by human foot step and force energy is converted into mechanical energy by the rack and pinion mechanism. electricity is produced by DC generator. We are supposed to study existing methods of foot step power generation that are rack and pinion arrangement and piezoelectric crystals and supposed to modified the existing system.

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Power Generator, Piezoelectric Device, Foot Step Electronics Tools

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 Abstract

The study delineates effect of a polymorphism in NLR family pyrin domain containing 1 (NLRP1) protein which causes dysfunction, leading to a compromised immune response resulting in increased susceptibility of the host towards the foreign pathogenic infections. NLRP1 inflammasome promotes the activation of interleukin IL-1, IL-18, IL-33 which are effective mediators of inflammatory innate immune response to tissue damage and pathogen invasion. The retrieval of SNPs of the NLRP1 gene has been carried out through dbSNP. The deleterious SNPs were discerned using the computational tools SIFT, I-MUTANT, PhD-SNP and PROVEAN. The SNP V939M of NLRP1 was predicted to be the most deleterious on the basis of the outcomes from the computational tools. The protein structure of NLRP1 was retrieved from PDB (Protein Data Bank) and the structural mutations were carried out in Pymol. (patchdock)

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NLRP1, Dysfunction, Innate Immunity, Inflammasome, Interleukin IL-1, Caspase-1, V939M

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This paper presents a farm monitoring system by using Smartphone application and Internet of Things. Using this system, farmers can remotely monitor farm for soil moisture, pH level in the soil, temperature and humidity in the environment, level of water using the sensors soil moisture sensor,ph sensor, temperature sensor and humidity sensor and microcontroller is used to control and automate the farm processes and The User or the farmer in this case registers himself in the system using the Android Application on his phone. The users fetch the data related to crop requirement as a whole which includes the number of acres registered by other farmers and the demand status for various crops. The information gets updated in real time so that farmers get to know which crops will be in demand and which crops will not be in demand. This is a predicted demand information that a farmer would get to make the right decision of crops.

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Keywords:Internet of things,Temperature, Humidity, soil moisture,Arduino MEGA,GSM

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Creative Commons Attribution 4.0 and The Open Definition