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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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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 Keywords

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

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

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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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Image Caption, CNN, RNN.

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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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Honeycomb sandwich panel, TNT, Core topology

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

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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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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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Bolt arrangement, fuse plate, connection

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

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 Abstract

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Erosion of values, impartial elections, improve efficiency, political reality of rural India.

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ABSTRACT The two types of devices, Single Electron tunneling devices (SEDs) and Threshold Logic Gates (TLGs), both have the power of controlling the transport of an electron through a tunnel junction at a certain time. A single electron has the charge which is adequate to store an information in a SED. The switching delay of a Threshold Logic Gate is very small and speed of the processing of TLG based devices will be in the order of? 10?^9. For implementing logic gates and a sequential circuit, TLG, of course, will be a best candidate to fulfill the necessities. When an Ultra-low noise is considered, TLG based circuit will be the best selection for implementing our desired tunneling circuits. Different TLGs like 2-input AND/NAND, 2-input XOR/XNOR, RS Flip-flop, T-Flip-flop have been implemented with the help of concept of linearly separable threshold logic gate of multiple inputs. Almost in every instances, the threshold logic equations, Truth tables and simulated results for them are provided in parallel in due places.

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Keywords: Electron-tunneling, XOR, T Flip-flop, Coulomb-blockade, sequential circuit

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Erosion of values, impartial elections, improve efficiency, political reality of rural India.

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Antibody therapeutics and vaccines are among our pis aller to finish the raging COVID-19 pandemic. They, however, are susceptible to over 5000 mutations on the spike (S) protein uncovered by a Mutation Tracker supported over 200?000 genome isolates. Recent variants of the virus within the UK, South Africa, and Brazil seem to spread more easily, which have the potential to steer to more hospitalizations and deaths. RNA sequence analysis of emerging SARS-CoV-2 infection is effective for tracking viral evolution and developing novel diagnostic tools. Furthermore, SARS-CoV-2 sequence analysis can provide insight into potential antigenic drift events that cause strain speciation and changing clinical outcomes. The tactic is definitely adaptable to research potential mutations of the virus, ensuring the simplest possible vaccines are quickly identified. This will give humans a big advantage over evolving mutations, with the model accomplishing vaccine design cycles that when took months or years during a matter of seconds or minutes. This text is an effort to predict mutations of novel coronavirus by applying machine learning techniques over bioinformatics.

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COVID-19, Machine Learning, Sequential Pattern Mining, Corpus, Genome.

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Internet of Things (IoT), Mobile application, Mobile sites, E-books, Social Media, Online Marketing, E-Commerce, women entrepreneurship

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Examining air quality has become one of the most essential activities for the peoples in many industrial and urban areas today. The quality of air is adversely affected due to various forms of pollution caused by electricity, transportation, fuel uses etc. The deposition of harmful gases is creating a serious problem for the quality of life in smart cities. With this increasing air pollution, we need to implement efficient air quality monitoring and prdiction models which collect information about the concentration of air pollutants and provide assessment of air pollution in area. Particulate matter contains microscopic solids or liquid droplets that are so small that they can be inhaled and cause serious health problems. Of these, particles less than 2.5 micrometres in diameter, also known as fine particles or PM2.5, pose the greatest risk to health. Hence, air quality evaluation and prediction has become an important research area. The focus of this project is to study about the data mining and machine learning techniques used for prediction of air pollution and the mainly focus is on the prediction of PM2.5 on the basis of all the other air pollutants and temperature and humidity.

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Air quality, PM 2.5, Prediction

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This study has been undertaken to investigate the stress concentration capacity of different bolt arrangements in chord member of the built up K-joint. Chord member with three bolt arrangements are analysed using ANSYS 16.0. The behavior of 10 bolts arrangements including zigzag, arch shape, X-shape configurations under incremental loading was analysed using ANSYS 16.0. Here three 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, 3 bolt connection were tested to evaluate the performance connections, and then a parametric study was carried out using the verified numerical models

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Bolt, loading, stress

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The static simulation is conducted on a crankshaft from a single cylinder 4- stroke diesel engine. A three-dimension model of diesel engine crankshaft is created using CATIA V5 software Static structural analysis is performed to obtain the stress magnitude at critic allocations of crankshaft in. The static analysis is done using Software ANSYS 2021R1 which resulted in the stresses, deformation and elastic strain. Boundary conditions are applied at bearings.Crankshafts find many applications in various branches of engineering. They are used whenever there is the need to translate reciprocating linear motion into rotation or vice-versa.In their more varied configurations, crankshafts are usually used in internal combustion engines but also in piston steam engines. It lays on the former the vaster and varied range of applications of crankshafts. The internal combustion engines cover various fields of uses, from small scale model planes to large maritime engines.

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Crankshaft,Composite Materials,Al7075,SiC,Catia,Ansys

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The article discusses in detail the concept of juvenile delinquency. A child is not a criminal from the womb of his mother but he is forced to become one due to various factors during his life. This article enlists such factors that lead a child to become delinquent. It is in the interest of society to prevent and eliminate juvenile delinquencies because such activities not only impact the juvenile himself but also the victim, his families, community and society. A society needs to be peaceful and safe for people for their overall growth and development and incidents of juvenile delinquencies become hurdle in the normal and smooth functioning of a society.

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Juvenile, Criminal, Sexual, Delinquency, Education

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The paper aims to document the historic events of the immediate years before and after India attained its freedom in 1947, as perceived by Indian sculptors of that period. The subject matters adopted by these sculptors were directly or indirectly influenced by the political environment of the times discussed. While some of the sculptors and their work discussed in this paper revolves around the general idea of freedom, while others chose to portray the sentiment of nationalism, patriotism, and nation building. The independence of India was earned at a cost. The partition of India left an everlasting and traumatic impression on many of the sculptors who were displaced. The paper also highlights how as compared to painting, the reflection of the historical events that predate and follow the independence of India through sculptures is relatively less.

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Nationalism, Independence, Partition, Expression, Sculpture.

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