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Artificial Intelligence and Machine Learning
Published in Archana Mire, Vinayak Elangovan, Shailaja Patil, Advances in Deep Learning for Medical Image Analysis, 2022
Kaushik Dehingia, Mdi B. Jeelani, Anusmita Das
Artificial intelligence (AI) is a branch of computer science that was developed in the early twentieth century to solve complex problems using computing systems with advanced analytical or predictive capabilities. One of the most promising branches of AI is machine learning (ML), which can learn from past data and has the potential to create programming languages from that data. ML techniques forecast problem-specific outcomes and measurements based on learning ability [Kourou et al. 2015, Jiang et al. 2020]. ML can “learn” from data and recognize sophisticated patterns using a mathematical and statistical approach. When computing a complex dataset, ML processes go through two stages. The first is referred to as the “learning” phase, while the second is the “verification” phase. During the first phase’s implementation, a theoretical model is developed to clarify the task. ML algorithms check the first phase’s findings and details during the verification phase. ML algorithms are divided into three groups during the learning phase: supervised, unsupervised, and reinforcement learning [Thenault et al. 2020].
Distributed and Parallel Computing
Published in Sunilkumar Manvi, Gopal K. Shyam, Cloud Computing, 2021
Sunilkumar Manvi, Gopal K. Shyam
Cloud computing is the delivery of computing services: including servers, storage, databases, networking, software, analytics, and intelligence over the Internet (“the Cloud”) to offer faster innovation, flexible resources and economies of scale. We pay only for Cloud services we use, helping lower our operating costs, run our infrastructure more efficiently and scale as per our business needs.
AI-based comprehensive optimization technology for mining systems analysis
Published in Heping Xie, Yuehan Wang, Yaodong Jiang, Computer Applications in the Mineral Industries, 2020
Y.D. Zhang, R.X. Zhang, X.C. Li, W.L. Han
Artificial intelligence (AI) is an umbrella term for a wide range of computing methods that mimic various aspects of human intelligence [2]. AI method has its distinctive qualities for solution of multi-factor, multi-objective and non- linear large mining systems.
How the technologies underlying cyber-physical systems support the reconfigurability capability in manufacturing: a literature review
Published in International Journal of Production Research, 2023
Alessia Napoleone, Elisa Negri, Marco Macchi, Alessandro Pozzetti
Cloud computing, relying on internet-based big data analytics, is the enabling technology when data need to be collected from socialised and distributed resources and then, exploiting shared big data analytics, analysed to promptly react to disturbances and unexpected events (Ding and Jiang 2018). Cloud computing is the aggregation of computing as a utility and software as a service, where the applications are delivered as services over the Internet. Although cloud computing can support distributed engineering scenarios, intelligence and processing (e.g. decision-making) typically remain central, which means distributed clients depend on consistent and resilient connections with the cloud; therefore, these centralised services are not suited to the control architecture needed for decentralised and autonomous decision-making (O’Donovan et al. 2018). As explained below, acting on different layers, fog and edge computing complement cloud computing and overcome this limitation.
A Comprehensive Literature of Genetics Cryptographic Algorithms for Data Security in Cloud Computing
Published in Cybernetics and Systems, 2023
Ozgu Can, Fursan Thabit, Asia Othman Aljahdali, Sharaf Al-Homdy, Hoda A. Alkhzaimi
Cloud computing is a technology that enables the delivery of services through the Internet. The cloud functions as a data center. A consumer is charged for using cloud resources, storage, and other services. Cloud subscriptions for users are determined by the services they require, such as IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service) (Software as a service). As a result, Cloud Computing has arisen to provide processing power storage, resources, and applications to users as a “Utility” for meeting their needs. The availability of this cloud model is promoted. It has five distinguishing characteristics, three service models, and four deployment models. The five most important aspects are resource pooling, broad network access, on-demand self-service, rapid flexibility, and measurable service. There are three service models IaaS: Infrastructure as A Service, PaaS: Platform as a service, SaaS: software as a service, application as a service, and everything as a service. The four deployment models are public cloud, private cloud, hybrid cloud, and community cloud.