Convergence of Big Data, Machine Learning and the BlockChain Technology

2019 ◽  
Author(s):  
Ajit Singh
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Blockchain Technology

scholarly journals Blockchain Disrupting Fintech and the Banking System

Proceedings ◽  
2021 ◽  
Vol 74 (1) ◽  
pp. 24
Author(s):  
Eduard Alexandru Stoica ◽  
Daria Maria Sitea
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Financial Institutions ◽  
New World ◽  
Great Part ◽  
Banking System ◽  
Daily Activities ◽  
Blockchain Technology ◽  
Almost All

Nowadays society is profoundly changed by technology, velocity and productivity. While individuals are not yet prepared for holographic connection with banks or financial institutions, other innovative technologies have been adopted. Lately, a new world has been launched, personalized and adapted to reality. It has emerged and started to govern almost all daily activities due to the five key elements that are foundations of the technology: machine to machine (M2M), internet of things (IoT), big data, machine learning and artificial intelligence (AI). Competitive innovations are now on the market, helping with the connection between investors and borrowers—notably crowdfunding and peer-to-peer lending. Blockchain technology is now enjoying great popularity. Thus, a great part of the focus of this research paper is on Elrond. The outcomes highlight the relevance of technology in digital finance.

scholarly journals Blockchain Equity System Transaction Method and System Research Based on Machine Learning and Big Data Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Kanghua Peng
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Operating Efficiency ◽  
Analysis Method ◽  
Trading System ◽  
Single Node ◽  
Blockchain Technology ◽  
Equity Trading ◽  
Method Factor ◽  
Depth Study

With the development of machine learning and big data, traditional equity trading system methods can no longer meet the current trading needs, and there are still problems such as low operating efficiency and serious homogeneity. Blockchain technology has the characteristics of decentralization and can also complete transactions through smart contracts, innovating the way of equity system transactions. The purpose of this paper is to build an equity trading system in combination with blockchain in the context of machine learning and big data and provide innovative trading methods, so as to provide reference and reference significance for the construction of my country’s equity market. This article uses literature data method, comparative analysis method, factor analysis method, and other methods to carry out research, in-depth study of machine learning and big data, blockchain-related concepts, system composition, application situation, etc., and discusses the allocation of equity trading market The functions of resources, risk diversification, risk transfer, price determination, etc., have built a blockchain equity trading system, designed a consensus mechanism, block generation protocol, block verification, decentralization, and smart contract platform, and finally conducted a national equity transaction the background of the market is analyzed, and the experimental results, simulation indicators, transaction time, transmission consumption, and other content of the system constructed in this article are analyzed. In the single-node test, the CPU usage of the PoW consensus mechanism algorithm reached 100%, but the improved PBFT consensus mechanism was only 16%, which saved a lot of computing power and improved computing performance.

scholarly journals Big Data, Machine Learning and the BlockChain Technology: An Overview

2018 ◽  
Vol 180 (28) ◽  
pp. 1-4 ◽  
Author(s):  
Francisca Adoma
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Blockchain Technology

scholarly journals A Review of Artificial Intelligence, Big Data, and Blockchain Technology Applications in Medicine and Global Health

2021 ◽  
Vol 5 (3) ◽  
pp. 41
Author(s):  
Supriya M. ◽  
Vijay Kumar Chattu
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Global Health ◽  
Treatment Protocol ◽  
Diagnostic Procedures ◽  
Well Being ◽  
Medical Practitioners ◽  
Blockchain Technology ◽  
Technology Applications

Artificial intelligence (AI) programs are applied to methods such as diagnostic procedures, treatment protocol development, patient monitoring, drug development, personalized medicine in healthcare, and outbreak predictions in global health, as in the case of the current COVID-19 pandemic. Machine learning (ML) is a field of AI that allows computers to learn and improve without being explicitly programmed. ML algorithms can also analyze large amounts of data called Big data through electronic health records for disease prevention and diagnosis. Wearable medical devices are used to continuously monitor an individual’s health status and store it in cloud computing. In the context of a newly published study, the potential benefits of sophisticated data analytics and machine learning are discussed in this review. We have conducted a literature search in all the popular databases such as Web of Science, Scopus, MEDLINE/PubMed and Google Scholar search engines. This paper describes the utilization of concepts underlying ML, big data, blockchain technology and their importance in medicine, healthcare, public health surveillance, case estimations in COVID-19 pandemic and other epidemics. The review also goes through the possible consequences and difficulties for medical practitioners and health technologists in designing futuristic models to improve the quality and well-being of human lives.

Digital Farmers

2019 ◽  
pp. 221-238
Author(s):  
Gordon Conway ◽  
Ousmane Badiane ◽  
Katrin Glatzel
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Food Security ◽  
Digital Technologies ◽  
Soil Maps ◽  
Crop Selection ◽  
Blockchain Technology ◽  
Technology Applications ◽  
Sustainable Fashion ◽  
First Time

This chapter deals with digital technologies, both hardware and software, and how they can help increase agricultural production and food security in a sustainable fashion. Africa is going digital, enabling millions of Africans to connect for the first time. The effect is to revolutionize the lives of African farmers—by overcoming isolation, by speeding up change, and by taking success to scale. Digital connectivity has enormous implications for agriculture and nutrition. It is already being used to disseminate information on nutrition and health, providing timely information on everything from weather predictions, crop selection, and pest control to management and finance. Technologies include the analysis of big data, using machine learning and blockchain technology applications that help to produce and analyze digital soil maps, to provide sophisticated insurance and faster breeding cycles for traditional African crops.

Utilizing Blockchain Technology in Social Media Bot Identification

2020 ◽  
Author(s):  
Shreya Reddy ◽  
Lisa Ewen ◽  
Pankti Patel ◽  
Prerak Patel ◽  
Ankit Kundal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Gold Standard ◽  
The Internet ◽  
Learning Models ◽  
Current Time ◽  
Machine Learning Methods ◽  
Blockchain Technology ◽  
Modern Age ◽  
Machine Learning Models

<p>As bots become more prevalent and smarter in the modern age of the internet, it becomes ever more important that they be identified and removed. Recent research has dictated that machine learning methods are accurate and the gold standard of bot identification on social media. Unfortunately, machine learning models do not come without their negative aspects such as lengthy training times, difficult feature selection, and overwhelming pre-processing tasks. To overcome these difficulties, we are proposing a blockchain framework for bot identification. At the current time, it is unknown how this method will perform, but it serves to prove the existence of an overwhelming gap of research under this area.<i></i></p>

The Cross-Sectional Pricing of Corporate Bonds Using Big Data and Machine Learning

2020 ◽  
Author(s):  
Turan G. Bali ◽  
Amit Goyal ◽  
Dashan Huang ◽  
Fuwei Jiang ◽  
Quan Wen
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Corporate Bonds ◽  
Cross Sectional ◽  
The Cross
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