Reviewerly/exHarmony huggingface dataset:
Hybrid Deep Model for Sentiment Analysis of COVID-19 Twitter Data

Sentiment analysis is a natural language processing technique used to analyse textual data generated on social media platforms like Facebook and Twitter. Ever since the Covid19 pandemic started many posts were shared on the social media platform as videos and messages with real-time updates about the spread of the pandemic across all countries. Several misconceptions led the public to panic in addition to the health deterioration created by the disease due to the false information spread through social media. This has paved the way for this research on the sentiment analysis of reviews posted on Twitter related to the spread of Covid-19 disease. The dataset used for the proposed work is taken from the IEEE data port which is an open access dataset platform. The Hybrid Deep Sentiment Analysis (HDSA) model which is a fusion of the deep learning algorithms is employed in this work to analyse the sentiments in Covid-19 tweets. Stacked Denoising autoencoders are used for feature extraction from the dataset. Bi-Convolutional neural networks and Bi-Long Short-Term Memory Networks are used to reduce the feature dimensionality and obtain the long-term dependencies in the extracted data. The classification of the sentiments is implemented using the GANBERT technique. The proposed model exhibited 94°/0 accuracy compared to the other state-of-the-art models in the research of Sentiment Analysis of Covid-19-related tweets.
A reliable security model that protects ultra-dense enterprise cloud networks from highly vulnerable cyber attacks

Ransom ware is dangerous software that can steal data from a computer. Also worth making files unusable. After the attack through this, the hackers will ask for money to release these hacked files on the Enterprise's financial assets or the assets of its customers. Insider attacks by individuals trusted by organizations have become more prominent in recent years, leading years. That's a big question in today's cyber security world. However, it is an unnecessary question for two reasons. Because the time to help many victims of cyber-attacks has probably passed.. In this paper a smart security algorithm was proposed to prevent the ultra-dense organizational cloud network users from the cyber attacks. However, it also relates to good practices for protecting information and preventing or detecting cyber-attacks to which any organization or person is exposed. In a comparison tip, the proposed model achieved 92.26% of VPN data transfer rate, 93% of information protection, 96.74 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> of file back-up protection, 94.94 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> of HTTPS and SSL protection and 95.85% of codeword protection. Companies in dire straits have already paid hackers. Other companies have found a way to recover their files without hackers. The second reason is that the unnamed credible person may be in direct contact with the perpetrators..
Designing Microgrid Energy Markets Using Smart Information System and Blockchain Technology

Energy generated through centralized power plants is eventually being replaced by Renewable energy. Due to its highly volatile nature, it aids to the fluctuations in the generation of power. These fluctuations cause major inconvenience to the consumers. Due to these disadvantages, the integration of RE into the grid poses serious challenges. The conventional grid system is also not secure from hacking. We must ensure a reliable balance between generation, consumption, and the players in the grid. We also need to make sure the grid and the communication in the grid network is secure. To tackle these challenges, we introduce a trade between the prosumers and consumers in a Peer-to-Peer fashion. All this can be achieved with the help of a blockchain network and smart contracts. Blockchain is a safe, secure and reliable platform and is tamper-proof. This paper presents the use of Blockchain and smart contracts to design a framework for energy trading in the developing countries.
Double Phased Algorithm for Frequent Sub Graph Mining with More Security

A crucial issue for machine learning on vertices is the collection of frequent subgraphs from a group of networks or a single graph. However, if the initial networks contained sensitive information, disclosing the discovered similar subset might pose major risks to people's privacy. The issue of occasional graph g minor (Spaghetti monster) is discussed in this study under a strict privacy preserving architecture. We outline a numerous private information FSM technique we refer to as Generator. In Two - dimensional array, the whole first step involved the secret discovery of widespread summary study, and the second phase involves the computation of the anarchic supporting of each recognised often snippet. We provide a commonly substrings locator, that might improve the quality of detected commonly subgraphs by option reduction, particularly to covertly share similar subgraphs. Moreover, we develop a vector noisy assist calculating method that uses the inclusion correlations between both of the discovered regular sub bands to increase the accuracy of the loud offers in order to compute the quiet follower of each detected shared subnetwork. We contend that Facts and figures satisfies more could privacy via formalised risk control. Lab tests on real study shows that Facts and figures can achieve great data value and covertly share similar subsets.
Desktop Application- Interactive Zira Voice Assistant

over the last decade, the number of cars has skyrocketed. Around the world, there are over 1 billion active vehicles, with 60 to 70 million in India. Managing such traffic situations and finding enough parking spaces is not an easy job. Vehicle counting and classification on congested streets can aid authorities in obtaining traffic flow statistics and understanding an incident. In the field of highway management, intelligent vehicle detection and counting are becoming increasingly relevant. However, vehicle identification remains a challenge due to varying vehicle sizes, which has a direct impact on the precision of vehicle counts.
You Only Look Once(YOL O) Object Detection with COCO using Machine Learning

Object Detection is the most important mission in computer imaginative and prescient within the latest times. It is widely used in Autonomous driving, wildlife protection, security system, etc. The orthodox processing objects of the image have various shortcomings in order to achieve the requirements of the latest current improved high level computer vision needs. With the recent advancement in deep neural network and various different image processing and machine learning algorithms, now things are quite comfortable to go with object detection, classification and many more. In this paper, Convolution Neural Network (CNN) is employed in YOLO (You Only Look Once) algorithm to detect Objects in real-time. Object Detection includes various approaches inclusive of fast R-CNN, Retina-Net, and Single-shot Multi Box Detector (SSD). YOLO is used in real-time image processing at a larger extend because of its great performance with superior speed and accuracy over the aforementioned object detection techniques. In this project,COCO model is used with YOYO algorithm in order to achieve the requirements of latest object detection of the advancedworld.
An Examining the role of AI in electronics, and instrumentation engineering

Artificial intelligence and electrical automation control technologies are evolving and growing together with science and technological advancement. More and more artificial intelligence technology is being used in electrical automation control, which provides a good foundation for the development of automation control technology support. This paper introduces artificial intelligence and outlines its future research objectives encompassing artificial neural networks, pattern recognition, expert systems, machine learning, and such as deep learning finally, numerous perspectives are used to assess the applications of artificial intelligence perspectives. Researchers studying AI may find some guidance in this publication.
IoT based Intelligent Cattle Shed Management

By giving residents access to resources for the information exchange, a village may be transformed into a smart village. The IoT is proving to be the foundation of smart towns. Health care, irrigation, climate monitoring, dairy, cattle surveillance, training and education of the agricultural and related sectors, water and drainage management, recycling and reuse, smart homes, smart lighting, wearable technology, and other verticals need to be prioritised in order to develop a smart village. Agriculture and related industries are the major arteries of the village-based economy. IoT is essential for increasing agricultural output and agro-related business revenues. It aids in lowering production costs for dairy, poultry, fish, grains, fruits, and vegetables. By managing cow sheds and the outputs produced by cattle, the suggested strategy in this study will serve to enhance the socio-economic environment while ensuring the greatest possible sustainability of natural resources and infrastructure.
Personalized Desktop App Based Interactive Means of Zira Voice Assistant

Python is a growing language, therefore writing a voice recognition script in python is simple. Life got increasingly intelligent and technologically linked as time went on. Some speech services, such as Google, Siri, etc., are already well known. Today, it can serve as a scheduling reminder, send emails, music playback, calculator and act as a search engine in Zira voice assistance system. The proposed work uses voice input, outputs speech, and converts the voice command to words on a screen. The main goal for voice assistance is to increase computer speed and human intelligence. Voice Help uses our microphone to record voice input and translates it into comprehensible computer language, providing the user with the answers and solutions they need. By working on this project, I came to understand how the idea of AI diminished living person effort and time to save in all sectors.
Commputation of Maximum permissible voltage value for long-term permissible current loads for UPS power system

Increasing use of modern technological facilities to secure facilities in professional activities. It allows you to improve the quality of services while reducing costs. We can provide customers with a wide range of technical security equipment at affordable prices. Our experts provide a full range of services: from the design and installation of the system to its subsequent maintenance. In this paper, Computation of Maximum permissible voltage value for long-term permissible current loads for UPS power system. A video surveillance system is a security device designed for continuous visual monitoring of a selected area of an object, allowing timely response to illegal activities. Today, there are complexes where you can monitor not only individual parts of the building, but the entire structure. Also, it should be noted that in this case it is not necessary to turn on the UPS with the button - it is enough to connect it to an external power source. For some reason, it is not mentioned in the available materials.
Communication Size Reduction of Federated Learning based on Neural ODE Model

Federated learning is a machine learning method in which data is not aggregated on a server, but is distributed to the edges, in consideration of security and privacy. ResNet is a classic but representative neural network that succeeds in deepening the neural network by learning a residual function that adds the inputs and outputs together. In federated learning, communication is performed between the server and edge devices to exchange weight parameters, but ResNet has deep layers and a large number of parameters, so communication size becomes large. In this paper, we use Neural ODE as a lightweight model of ResNet to reduce communication size in federated learning. In addition, we newly introduce a flexible federated learning using Neural ODE models with different number of iterations, which correspond to ResNet with different depths. The CIFAR-10 dataset is used in the evaluation, and the use of Neural ODE reduces communication size by approximately 90% compared to ResNet. We also show that the proposed flexible federated learning can merge models with different iteration counts.
A System Development of biometric system design for the Field Oriented Students

One meaning of a biometric framework portrays it as “an example acknowledgment framework that recognizes a client by deciding the realness of a given physical or social characteristic the individual has.” In its most fundamental structure, a biometric framework is an example acknowledgment framework. As individuals become more dependent on PCs and the web in their everyday lives, it is a higher priority than at any other time to guarantee the security of delicate and individual information. The multidisciplinary and interdisciplinary designing practice known as biometrics is unique. Our senior college understudies in the divisions of electrical, PC, and programming have the chance to take classes in which they gain proficiency with the “Basics of Biometric Framework Plan.” These classes put an accentuation on this specific application space. This one-semester course will cover various points, including the detailing and examination of plan objectives, the determination of a registering stage, including application-explicit DSP processors, demonstrating and prototyping, relieving assaults utilizing an assortment of configuration approaches. The given methodology consist a carryable self contained hardware which is able to be utilized independently. It also has number pad and a chip to be used together. The results compared the error rate at 0.41
Study of the Software Development Life Cycle and the Function of Testing

A construction investigation and configuration process that is imposed on the development of a software item is known as the software development life cycle. Testing is now an important and crucial phase in the software development life cycle in every organisation. Fundamentally important to the software development cycle is testing. Testing should begin early in the software development process to prevent potential bugs, reduce costs, and aid in determining requirements. Software testing is done with the intention of strengthening software and preventing problems. The testing phase of the software development life cycle is critical and vital. However, the manner in which it is finished varies from one association to the next. Software testing has evolved into a component of development, and it is wiser to start testing in the early phases in order to avoid problems by fixing bugs at the end. Additionally, the purpose of testing in the software development life cycle is to improve steadfast quality, execution, and other crucial components that may be characterized as SRS. The SDLC consist an explanatory plan that described to create, schedule, and maintain specific software. The organizational framework that explains the tasks carried out at each level of the software development procedure.
The intelligent management and monitoring human capital asset model for network monitoring organization using machine learning model

Generally, companies have access to labor-produced goods that are typically employed for more production. Investing is the term used to describe the creation of capital. Investments are by nature an original expenditure that yields returns over time. The notion of personal capital states that individuals may expand their prospects by spending in oneself, and governments can raise national income by supporting the development. The major justification for making such investment is that the cash may be repaid via better production and earnings, making them justified. Numerous kinds of human capital exist. Generally speaking, discovered knowledge, skills, and even data may be seen as a kind of human resources that helps a person to boost production and profit. In this research, a machine learning model was suggested for the management and tracking of human resources. The economic benefits of spending money on human capital may be shown clearly and completely by looking at the rate at which the investment returns. The main issue is figuring out how investment in human capital will affect the economy. Numerous empirical studies demonstrate that returns on investments in capital equipment are similar, however returns on investments in human capital might vary depending on the sort of capital invested.
The smart detection for anonymous web browsing in high density cloud network by using secured onion routing model

The Onion routing is the technology behind the TOR browser, is a method of anonymously exchanging information over the Internet. In this case, messages are repeatedly encrypted and sent through multiple routers, each applying an encryption layer of its own. Thus, the intermediate points of communication have no information about the content or purpose of the message, nor about the sending point or the receiving point. In this paper a secured onion routing model was proposed to detect the anonymous web browsing in the high density cloud network. The main idea of the proposed onion routing model is to ensure maximum anonymity of users - the sender and receiver of information, as well as to protect the content of the message from strangers. Of course, onion routing technology does not guarantee secrecy, but it does make it more difficult for eavesdroppers to discover the data.
Weaving Heart Rate into the Authentication Based on Spatiotemporal Information and Actions

To enhance the security of an authentication method, we proposed weaving the user's heart rate into a spatiotemporal authentication method. Currently, the method requires users to perform predetermined actions repeatedly at predetermined areas. We proposed using the heart rate as a substitute for predetermined actions at the areas. Our method avoids privacy concerns related to biometrics based authentication.
A New Higher Order Differential of RAGHAV

RAGHAV is a 64-bit block cipher proposed by Bansod in 2021. It supports 80-, and 128-bit secret keys. The designer evaluated its security against typical attack, such as differential cryptanalysis, linear cryptanalysis, and so on. On the other hand, it has not been reported the security of RAGHAV against higher order differential attack, which is one of the algebraic attacks. In this paper, we applied higher order differential cryptanalysis to RAGHAV. As a results, we found a full-round higher order characteristic of RAGHAV using 1-st order differential. Exploiting this characteristic, we also show that a full-round of RAGHAV is attackable by distinguishing attack with 2 chosen plaintexts.
The DOS based recovery model of new cloud server storage hard disk from the vulnerable network attacks

When replacing a hard drive, this utility transfers all your data (operating systems, applications, files) from the old hard drive to a new disk. Every file and directory will be carefully restored. The new disk may have different sizes and layout, but the size of the partition will be set at the time of copying as required by the new disk. The multifunctional program is primarily aimed at creating archives containing any files and directories, with the possibility of recovery from under “deaf” DOS and directly from Windows. In this paper, The DOS based recovery model of new cloud server storage hard disk from the vulnerable network attacks. The utility allows you to scan any files, directories, registry keys and variables, as well as DOS files and files. Scanning information is stored in report files, which can then be compared and archived based on differences. Although the program is very small (189 KB) and does not require installation, it is suitable for backing up any individual program or the entire operating system.
Survey on analysis of Blockchain Technology

Decentralization, autonomy, integrity, immutability, verification, fault tolerance, anonymity, auditability, and transparency are all desirable qualities in a system, and all of them are present in blockchain. In this paper, we first conduct a more in-depth survey of blockchain technology, focusing on its origins, the quantitative comparisons of consensus algorithms, the specifics of the cryptography employed in the blockchain (including public key cryptography, Zero-Knowledge Proofs, and hash functions), and the exhaustive list of use cases. Moreover, this study focuses on the blockchain's security measures. In specifically, we use a risk-based approach to evaluate blockchain security, developing a taxonomy of blockchain security risks, examining actual attacks and defects, and summarising newly created blockchain security solutions. We conclude with a discussion of the obstacles and emerging research trends that must be overcome to develop blockchain systems that are both scalable and secure enough for large-scale deployments.
Accelerating Next Generation Genome Sequencing Leveraging High Bandwidth Memory on FPGAs

Next Generation Sequencing (NGS) technology im-poses high demands on the performance of read mapping software, leading to increased interest in leveraging hardware accelerators such as field programmable gate arrays (FPGAs). Only few works accelerating the state of the art read mapper BWA-MEM focus on the memory latency bound supermaximal exact match (SMEM) subroutine. With the advent of FPGA devices with on-package high bandwidth memory (HBM) resources, the applicability of such accelerators to the SMEM problem deserves reconsideration. This work introduces BWA-HBM, which accelerates the SMEM algorithm of BWA-MEM by offloading it towards an HBM-supported accelerator card. On a human reference genome the pure SMEM algorithm of BWA-HBM achieves a speedup of 36%, resulting in an overall runtime improvement of 15% compared to BWA-MEM.