Volume 9 | Issue 6 |

 Abstract

As we as a whole, realize that the information which is created by the administrations are should have been Put away and used are quickly expanding. Cloud computing is a stage that can grow the abilities and can faster the possibilities powerfully without utilizing new programming frameworks. The primary benefit of cloud computing is this load of administrations is given for minimal expense to the client. Hence, every one of the clients was Moving their information on the cloud. The significant justification for the increment utilization of cloud computing is the absence of security and furthermore, the client can store and access the put-away information in the cloud from any place at any time. So the clients of this cloud administration should know the Perils of transferring the information to the general public. This paper manages the Cryptography method and it principally centers around the cloud storage administrations. The paper means to shows the particular security issues which are brought by the utilization of Cryptography in a cloud computing framework and inspect an assortment of cryptographic strategies utilized by significant cloud suppliers.

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 Keywords

Cloud, Cryptography, Cloud Computing, Cryptographic algorithms, Encryption, Decryption, Cipher text, Security, Symmetric-Key, Asymmetric-Key

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The green concrete term is not related to the color of the concrete. The term is related to the eco-friendly nature of the concrete, sustainable development, and decreasing the greenhouse effect. This research article discusses the significance of green concrete shortly. Most of the big construction companies are now focusing on green infrastructure. They are trying their best to decrease the load on the environment in various steps for sustainable development. Concrete is among the highest percentage of materials used at the construction site. We can utilize the waste and demolished concrete materials by crushing them and passing through the required sieve size, both fine aggregates and coarse aggregates were recovered. The mix is prepared with different percentages of fly ash replacing Portland pozzolana Cement. Compressive Strength tests were performed at the lab for different Percentages of replacement of cement with fly ash.

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 Keywords

Concrete, Sustainable Development, Green, materials, Compressive Strength

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 Abstract

This research looked into the behaviour of an SCC reinforced concrete (RC) beam with a biaxial geogrid as an extra reinforcement. The use of geogrid in concrete gave geosynthetics a whole new meaning in structural engineering. Geogrids are utilised in asphalt concrete layer stability, confinement, and strengthening, as well as to decrease reflective cracking in pavement applications. The purpose of examining the behaviour of geogrids in structural members gives opportunity to observe benefit and feasibility of using geogrid in thin concrete layers. One control beam (CB) and four geogrid reinforced concrete beams (GB) with variable geogrid layers from one to five are used in the experiment. The two-point stress on these beams was gradually increased until they collapsed. The first crack load, ultimate load carrying capacity and behaviour was observed till collapse occurred. The behavior and flexural strength of these geogrid beams were compared with that of a control beam that had the steel reinforcements alone. The results of the tests show that geogrid can be utilised as a substitute for steel in structural parts

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

SCC (Self comapcting Concrete), biaxial geogrid, and flexural strength

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pulse Oximeter, HR, Arduino, bpm, SpO2, Photoplethysmography, NodeMCU, LCD, MAX 30102

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: With the development of deep learning, the combination of computer vision and natural language process has attracted a lot of attention in the last few years. Caption embedding is representative of this file, which enables the computer to learn to use one or more sentences to understand the visual content of the image. The efficient process of producing high-definition semantics is required not only for the recognition of an object and the scene, but also for the ability to analyze the state, attributes and relationships between these objects. Although captioning is a difficult and difficult task, many researchers have found significant improvements. In this project, we describe in detail the three ways to insert image captions using deep neural networks CNN-RNN based, CNN-CNN-based framework and based on reinforcement. We then present the work representing the top three methods in a row, explain the metrics for testing and summarize the main advantages and disadvantages. Over the past few years, the problem of making automated descriptive sentences for photographs has gained a growing interest in natural language research and computer-based research. Image captioning is an important task that requires a basic understanding of images and the ability to produce descriptive sentences with appropriate and appropriate structure. In this study, the authors propose a hybrid system that uses the multilayer Convolutional Neural Network (CNN) to produce visual vocabulary and Long Short Term Memory (LSTM) to organize sound sentences using generated keywords. A convolutional neural network compares the image to a large database of training images, and creates an accurate description using trained captions.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Image Caption, CNN, RNN.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study has been undertaken to investigate the front layer deflection of metallic sandwich panel under blast loads. This study analytically evaluated the deformation of front layer of honeycomb sandwich panel using different core materials (Steel and Aluminium) and fixed outer layer material (Steel). Results shows Aluminium core with steel outer layer combination shows better performance under blast load. 500 g of Trinitrotoluene (TNT) used as blasting material and the finite-element model simulated using dynamic nonlinear explicit software ANSYS Workbench 16. 1.

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 Keywords

Honeycomb sandwich panel, TNT, Core topology

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The role of Cryptocurrency has been really important in reshaping the financial system due to its increasing popular appeal and worldwide acceptance. A lot of people have started to make investments in Cryptocurrency, but the dynamical features, uncertainty, and predictability of Cryptocurrency are still mostly unknown, which dramatically risks the investments. It is a matter of trying to understand the factors that influence the value formation. In this study, we use advanced artificial intelligence frameworks of Long Short Term Memory (LSTM) and Recurrent Neural Network (RNN) to predict the price of different cryptocurrencies. Evaluation of these algorithms is carried out to determine better prediction to analyze the price dynamics of different cryptocurrencies including Bitcoin, Ethereum, and Ripple. However, the explanation of the predictability could vary depending on the design of the machine-learning model which is implemented.

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 Keywords

Long Short Term Memory, Recurrent Neural Network, Cryptocurrency, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Health information needs also are changing the knowledge seeking behavior and may be observed round the globe. Challenges faced by many folks are looking online for health information regarding diseases, diagnoses and different treatments. If a recommendation system can be made for doctors and medicine while using review mining will save plenty of some time. In this system like these, the user faces many problems in understanding the core medical vocabulary as the users are laymen. User is confused because an outsized amount of medical information on different mediums are available. The idea behind recommender system is to adapt to affect the special requirements of the health problems of a user.

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Python machine learning disease symptoms identifier

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study has been undertaken to investigate the load carrying capacity of different bolt arrangement in HSS steel beam column joint with damage control fuse plate connection. Fuse plate with 4 bolt arrangements are analyzed using ANSYS 16.0. Extensive research has been carried out on steel moment frames to improve the cyclic performance of moment connections with different bolt arrangements. . The connection features are modified bolt arrangements designed to promote distribution of forces across the bolt group. The behavior of twelve bolt fuse plate connection with butterfly, zigzag, hexagonal, x-shape, configuration under cyclic loading was analyzed using ANSYS 16.0. Here four models of bolt arrangements are introduced. .This paper aims to obtain proper ranges for the geometric design parameters such as pitch, spacing for different bolt arrangements. In this order, 4 bolt fuse plate connection were tested under the cyclic loading to evaluate the performance of connections, and then a parametric study was carried out using the verified numerical models

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bolt arrangement, fuse plate, connection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Movies are a worldwide source of entertainment, and a powerful medium for educating or indoctrinating citizens. As far as the current pandemic situation is concerned, OTT platforms act as one of the most entertaining factors and a significant stress reliever for people around the globe. This project aims to explore all the movies in popular OTT platforms, in order to gain interesting insights. This is carried out with the aid of a Kaggle dataset, collected from Netflix, Prime Video, Hulu and Disney+ API. Dataset contains the complete information of all the movies, their ratings and the corresponding OTT platforms in which they are available. It provides detailed information such as Year of release, Genre, IMDb rating, Director and the Language of each movie. Here in this project we are using Multiple linear regression and Random forest to analyse our data and to get meaning full insights from the data collected from different OTT platforms collected from Netflix, Prime Video, Hulu and Disney+. Furthermore, the result obtained from each of these algorithms are compared to understand their respective suitability under varied conditions

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Multiple linear regression, Random forest Algorithms, OTT Platform Analysis, Netflix, Disney, Prime Video, Hulu , R programming

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Creative Commons Attribution 4.0 and The Open Definition