Reviewerly/exHarmony huggingface dataset:
The Impact of COVID - 19 to the Trade in India Using Digital, IOT and AI Techniques

The Corona virus also called SARS- CoV-2which spreads a disease called COVID-19. It has been documented that this disease has been spreading at an exponential rate and conquered 6 out of 7 continents sparing Antarctica. Since its outbreak it has been a close end to most industries and did not spare the consumer able industry. The pandemic creates a new door in digital transformation. Indian economy is adversely affected due the consequences of COVID-19. The traditional model of doing business has to be change as per the demand of current situations. The transformation in the context of digital is observed in all the sectors i.e., in culture, organization as well as in the work execution of an organization, in the industries as well as in the ecosystem via a smart assimilation of digital technologies, procedure and proficiency in every level and functions. The technologies are leveraged with digital transformation (also DX or DT) for creating worth for different stakeholders (customers in the broadest possible sense), create as well as obtain the potential for swiftly adjusting with the circumstances that are ever changing. Transformation done on digitalized mode is a strategy where any product or services are sold and promoted to the buyers digitally, it has removed the role of any mediator. COVID-19 is affects the whole world and it create a social distancing among the consumers, which in turns affecting a lot of businesses. A broad categories of industries and business will affect because of social distancing. In this study a perceived way out is suggested as a concept of Digital Transformation. The buying culture and the parameters might change due to social distancing. This research is conducted to see how the consumer's buying behaviour will change after the crisis of COVID-19. The consumer is transforming the traditional methods of buying goods and services by using online tools and techniques. According to the studies, the model of digital marketing has entered in our visualization for learning the techniques which are best for marketing strategies from various leading and successful companies. One thing is important that the demand and supply of commodities will marginally remain the same after the recovery of COVID-19, the only changes will come in terms of the buying behaviour of the customers. Consumer will make a habit to buy digitally and directly from the producers as precautionary measure.
Secured Cloud Data Outsourcing Model Using Two Party Integrity Scheme

Securing the data in the cloud is very challenging problem because security model proposed by the cloud service provider may not be acceptable by the client on many occasions. Inspite of those security concerns organizations show interest in outsourcing their data because of the variety of benefits offered by the cloud. To enhance the security, the cloud clients usually encrypt the data before outsourcing to it to the cloud service provider. Encryption alone will not provide sufficient guarantee for providing storage security to the outsourced data. To overcome these security issues we have proposed a new encryption model for the outsourced data in the cloud. This model uses a trusted third party manager who acts as an intermediary between the data owner and the cloud service provider. The model used in this approach is called two-person integrity scheme. In this model the encryption key is managed by both the cloud service provider and the data manager. The proposed model follows two stage of encryption. In this first stage the key is derived from the data owner and data manager. In the second stage the key is determined by the data manager and the cloud service provider. The experimental results of the proposed system are better than the existing cloud security algorithms
Analysis of Multiple Toxicities Using ML Algorithms to Detect Toxic Comments

Toxic Comment Classification is a classification problem that needs to be addressed these days. People can expresstheir thoughts on the internet via social media platforms. Hence itis important to set up some guidelines, which address the kind of information that is allowed to be posted. Hence The study of comments and their classification is necessary. The main aim of the following project is to understand whether the followingcomment falls under the toxic or nontoxic category by using multiple machine learning techniques. The following study uses 6 different traits, with the help of &#x25A1; vectorization a dictionary will be created out of known vocabulary(Dataset) to train the ML model. Since Multiple Traits are presentthe ML model has to get trained multiple times against each trait.This helps us to identify, which algorithm performs best in identifying multiple types of toxicities. It was identified that the Random Forest algorithm performed well against all types of traitswhich gave us a good accuracy of 85&#x0025; with a precision of 91&#x0025;. During the preliminary research, it was concluded that most of theresearch which was revolving around the topic was limited to Demographic/local Languages. We tried identifying a classifier for the English language.
The Critical Understanding on the Emerging Threats and Defensive Aspects in Cryptocurrencies using Machine Learning Techniques

The universal blockchain consensus mechanism was then examined, consists of a review of its features, highlighting benefits and drawbacks. Following that, we offered a taxonomic taxonomy as well as a detailed evaluation of previous approaches and approaches that employ machine learning (ML) approaches to address common security issues and abnormal behaviours in Bitcoin systems and cryptocurrencies. Furthermore, researchers discussed several unanswered research questions and potential research areas, as well as some closing thoughts. This paper evaluates the present degree of awareness on the many types of cryptocurrency crime that persist today or may occur in the future, as well as full explanations of the scams found. It is unknown how useful cryptocurrencies will be in the long term as terrorist techniques and cryptocurrencies evolve. Unfortunately, some recent advancements in cryptocurrency will make it easier for the most skilled terrorist groups to utilise them to attack Developed democracies, and cryptocurrencies will be incredibly beneficial for people who currently participate in overseas fundraising and illegal operations. Machine learning mechanism is developed for detecting raising threats in cryptocurrency. The suggested approach comprises of a detection technique that is integrated into many Bitcoin entities. Prior to creating the initial analysers, the suggested method employs a capture mechanism to extract an antigen symbol from the activity. To collect data, survey or primary quantitative data is conducted.
Stochastic Self-Organizing Map and Proposed Enlarge C4.5 to Diagnose Breast Cancer

Timely and accurate Breast Cancer (BC) prediction allows healthcare providers and doctors to take suitable decisions to treat the patients. Thus, this study employed a strategy based on Deep Learning (DL) to diagnose BC. The study intends to cluster the BC data by the proposed Stochastic Self-Organizing Map (SOM) as it has the ability to process complex data. On the other hand, Enlarge C4.5 (E-C4.5) algorithm is introduced to predict the BC cases based on the clustered outcomes. The BC dataset is loaded and pre-processing is performed where dimensionality reduction is executed to select only the relevant features for clustering. This process eases the clustering. Then, clustering is undertaken by the proposed Stochastic SOM. Here, all the identical data are grouped as clusters which makes it easy for prediction. Followed by this, BC is predicted by the proposed E-C4.5 algorithm. The analytical outcomes explore that the proposed methods are effective than the conventional methods as the proposed method shows a high accuracy rate, precision rate, recall rate and F1-score rate. The misinterpretation rate is also found to be minimum on implementing the proposed method, which is confirmed through the confusion matrix. The proposed method also determines the malignant and benign counts.
Key Management using Lagrange Interpolation for Wireless Communications

Security is one of the major concerns that must be addressed with a variety of preventative methods. The fundamental goal of security is to transfer sensitive data in a secure, unreadable format that can only be accessible by authorized parties. A plethora of encrypting and decrypting algorithms are available; nevertheless, the challenge is to generate a secure key that is difficult to break. This paper proposed a polynomial-based key generating mechanism. Mathematically, whenever a polynomial is generated through the interpolation method, it is unique and is challenging to guess without known data points. In this paper, the data points are generated employing a random generator to provide more randomness to the algorithm. Furthermore, it compares the proposed algorithm with the existing one.
An Empirical Analysis of 3D Image Processing by using Machine Learning-Based Input Processing for Man-Machine Interaction

The “human-robot interface” or HRI provides multiple assistance services in a variety of real-time applications. In robotic devices, the notion of object classification by digital visualisation is predicated on the converging of a “three-dimensional (3D)” image into a plane-based representation. During the convergence process, the projectors in multiple planes are mistaken, resulting in identification mistakes. The information processing approach, which is based on the result showed, can lessen these misidentifications in object identification. The combining indexes are found by seeing and extending the input image in all conceivable directions. A machine learning technique is utilised to ways that improve processing precision and agility. This research paper aims to evaluate the detailed analysis of 3D image processing by using machine learning for man machine interaction. In this context, secondary analysis is to be done by taking information from different journals and articles. Google scholar, ProQuest databases are used to get relevant and proper journals related to topic.
Inverse Document Frequency &amp; KNN Machine Learning Approach based Novel Text Semantic Analysis

In the modern era each and every thing is digital. E- commerce takes the place of the physical market. People buy anything not going physically anywhere and they are used the E-commerce platform. When The people buy, initially read the reviews provided by the previous customer regarding the product and decide they buy or not. So, the reviews are most essential part of the customer as well as for the customer. This paper delineates the sentiment analysis (SEAN) of the cell amazon real data values initially, use the NLTK, Porter Stemmer and various processing for pre-process the data and get the clean and desired data. Secondly, use the term frequency inverse document frequency (TFIDF) method for extracting the feature and divide the data using the train and test split and last apply the K-nearest neighbor method to train the machine. The artificial model predicts the positive and negative reviews. The experiment outcome result shows the model accuracy, precision, recall of the novel developed algorithm on the real text set.
An Exploration into Artificial intelligence based advancement in education field

The improvisation of artificial intelligence inspired technologies like augment and virtual reality for implementation of blended learning in classrooms has created a buzz in the field of education. We conducted a research study to investigate the usage of virtual or augmented reality in teaching, as well as two separate theme analyses, to get a better overview of the challenges and expectations of the educators by adopting these technologies. The first analysis looked into the implementations and reported motives offered by instructors in academic literature for building virtual reality learning environments, whereas the latter looked into the issues that have been documented. According to these assessments, the majority of academics utilize virtual reality to improve students&#x0027; intrinsic motivation and build their interactions using a limited set of variables such as constructivist pedagogy, collaboration, and gamification. Similarly, the great majority of educational virtual reality deployments discovered in our research are in a small number of educational disciplines. Following that, we introduced and compared a variety of contemporary virtual reality technologies, highlighting their potential to address some of the issues raised in our studies. However, these tools are not without problems, therefore we end this study by proposing various innovative ways to potentially solve them, and prospective possibilities for future academics interested in using these developing innovations to learning.
A Framework for Big Data Analytics with Wireless Communication of Network, Internet of Things and Cyber Security

Nowadays, big data is being implemented in various fields due to its advantages in risk management, healthcare and other business fields. The conventional big data analytics system is not highly promising for implementation in every system. Therefore, the developers are integrating the Internet of Things (IoT), wireless communication and cyber security systems to strengthen the capability of big data analytics. The current research has explained the framework for big data analytics with IoT, wireless communication and cyber security. Initially, past literature was explained, and then, the research methodology has been described. Primary survey-based research has been conducted with 54 data analysis experts to understand the framework of big data, its applications and solutions for cyber security-based issues. Findings showed that a VPN system with a firewall is a great choice for preventing external attacks. Moreover, as the primary data suggested the use of encryption systems, the researchers used SHA-256 (“Secure Hashing Algorithm”) for protecting the collected big data. Internet of Things (IoT) devices is used for collecting customer and operational data. After that, the data is collected via a wireless network and transferred to the respective access points. Users can access the data from access points and can generate meaningful information for executing various purposes.
Review on the methods involved in Blockchain Technology

Blockchain is hailed as a technological breakthrough that has the potential to change social transactions and interaction methods. This is largely because it allows mutually distrustful organizations to exchange information without relying on the financial value of trusted third parties and interacting parties. In addition, the blockchain provides integrity-protected system storage and data distribution. We examine if blockchain is a good idea and the finest possible solution for a certain application situation in this study. We offer a structured technique for determining the optimal technological option for a particular application scenario. Applying our framework, we explore three usage cases in depth: Supply Chain Management, Interbank and International Payments, and Decentralized Autonomous Organizations, and conclude the essay with a look forward to vast prospects.
Rapid Computer-Aided Manufacturing Tools Including Computerized Motion Control

The models provided to perform dynamic analysis of structures uses of operating systems to run industrial equipment & accompanying equipment in the manufacture of work elements is known as computer-aided manufacturing (CAM). It is also referred to as computer-aided modeling or computer-aided machining.Robot behavior patterns nowadays are mostly reliant on programming material given by humans to conduct repetitive actions. The distinction between robots and today's mobile electronic devices, such as vehicles and aircraft, is whether they can function autonomously without human intervention. Due to the high requirement for repeated and regular motions in the sector of industrial manufacturing, this also serves as a great setting for the development of industrial robots.Motion control is among the most evidence-based therapeutic in the industrial automation environment. The greatest fault of humanity is that mistakes will occur, which in the case of industrial manufacturing lines will frequently result in small damage to the line and, in severe circumstances, harm to workers. Machines can eliminate a lot of human mistakes, but it must be assured that the computer can acquire the correct instructions or perform the intended actions, and these commands must still be delivered to the machine manually.
An Empirical Analysis in Measuring the Impact of Artificial Intelligence for Better Marketing Communication to the End-Users Effectively in the Digital Era

&#x201C;Artificial Intelligence or AI&#x201D; has allowed businesses to have a deeper understanding of their clients and address them more accurately with customized digital messaging. As a result, a growing number of financial service companies are incorporating AI into their operations. &#x201C;Artificial Intelligence Marketing (AIM)&#x201D; is a strategy for improving customer satisfaction by maximising the use of information and technology. &#x201C;Big Data Analytics&#x201D;, &#x201C;deep learning&#x201D;, and collecting intelligence about the functional analysis of clients are some of the approaches employed to achieve this goal. As a result of these actions, this period has been dubbed &#x201C;The AI Marketing Concept,&#x201D; which needs a fundamental transformation in the way marketers interact with their customers and develop strategies to achieve their objectives. Examining some of the ways that &#x201C;artificial intelligence (AI)&#x201D; can assist merchants to alter marketing techniques and achievements in the future. Based on the primary and secondary analysis, researchers have collected data regarding the impact of artificial intelligence for creating better communication to end users.
Image Description Generator: An Overview

In recent times, with the improvement of AI, picturedescription has continuously drawn in the consideration of numerous researchers in the field of AI and has turned into an intriguing and laborious task. Picture captioning, consequentlyproducing natural language descriptions as per the content shown in the picture, is a significant piece of scene understanding, which consolidates the knowledge of NLP and Computer Vision. The use of picture captioning is broad and huge, for instance, the insight of human-computer collaboration. The improvement of the image description structure may help the visually impaired individuals to &#x201C;see&#x201D; the world in the upcoming time. In recent times, it has drawn rising awareness and become one of the most significant subjects in computer vision.
A Comprehensive Analysis of Smart Home Applying Natural Language Processing Using Internet of Technologies

The Internet of Thigs is mainly considered as the key technology tools which enables in connecting many devices through the use of internet, this has enabled in overall exchange of data and information, support in receiving the instruction and enable in acting upon it in an effective manner. With the advent of IoT, many devices are connected to the internet which enable in assisting the individuals to operate the devise virtually, share data and program required actions. This study is focused in understanding the key determinants of creating smart homes by applying natural language processing (NLP) through IoT. The major determinants considered are Integrating voice understanding into devices; Ability to control the devices remotely and support in reducing the energy bills. The present study focuses in sourcing the data from both sources and information are collected through the usage of questionnaire and the information are quantitatively applied through 5-point Likert scale. The researchers use extensive data analysis tools using AMOS for understanding the path diagram using structural equation model.
Content Based Image Retrieval Using Data Mining Techniques

Image processing is a method of removing information from photographs. The agreement covers picture compression, noise removal, image recognition, thankfulness delineation, image retrieval, and image variation. Probing and obtaining images from a database of photos is used in a variety of industries, including medicine, research, engineering, and many others. The two most prevalent approaches for locating the photographs needed to start a database are text-based image retrieval and content-based image retrieval. The text-based image retrieval system, TBIR, retrieves the image from the database using annotations. Traditional methods of information recovery are becoming obsolete as a result of Internet users and the expansion of multimedia technologies. CBIR extracts images from a large degree database by using the visual components of an input image, often known as low level features or image features. This required image must be recovered from the database by extracting visual features and comparing them to the input image. The histogram, colour moment, colour correlogram, gabor filter, and wavelet transform are all CBIR approaches. These techniques can be used separately or in tandem to achieve better outcomes. An image retrieval strategy based on the haar transform, K-means, and Euclidian distance is presented in this article.
A Conceptual Analysis on the Impact of Internet of Things (IOT) Towards on Digital Marketing Transformation

The growth of digital technology presents organisations with both huge potential and significant obstacles. Given the growing awareness of “loT and Big Data”, the goal of this study was to lay out the present status of business digitizing and to add to existing theory. The “Internet of Things” (IoT), Big Data, and data analytics along with cloud platforms, all provide opportunities for industrial enterprises to use technology to transform their approaches, particularly in the implementation of “new service-oriented marketing strategies”. In other words, marketing managers can, in general, incorporate new gadgets into old processes or enhance the technical content of products or services. Businesses may gather and evaluate review information and data, allowing them to develop relevant marketing strategies. A collection of innovations constitutes the foundations of today's technology landscape, as well as the catalysts of the resulting business change. Among these technologies, the “Internet of Things” (IoT), particularly the “Industrial Internet of Things” (1IoT), is crucial in assisting businesses in increasing the utilization of their machines and in the creation of service-based products in manufacturing organisations. This research paper has considered survey or primary quantitative method for data collection based on impact of loT towards creating digital transformation. In this context, 55 random people are selected and collect their responses.