DevOps is a set of practices that deals with coordination between development and operation teams and ensures rapid and reliable new software releases that are essential in industry. DevOps education assumes the vital...
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(纸本)9798350322590
DevOps is a set of practices that deals with coordination between development and operation teams and ensures rapid and reliable new software releases that are essential in industry. DevOps education assumes the vital task of preparing new professionals in these practices using appropriate teaching methods. However, there are insufficient studies investigating teaching methods in DevOps. We performed an analysis based on interviews to identify teaching methods and their relationship with DevOps educational challenges. Our findings show that project-based learning and collaborative learning are emerging as the most relevant teaching methods.
The computational demands of training complex deep learning models have hindered the widespread adoption of this transformative technology. Parallel processing techniques have emerged as a promising approach to addres...
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This research study examines the ways in which AI-enabled edge computing (AIEC) models are being used across various industries to improve operational efficiency and enable faster decision-making. The study discusses ...
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The growing complexity of cyber-attacks has underlined the requirement of strong Intrusion Detection Systems (IDS) able to instantly recognize a variety of hazards. This work offers a strategy for improving Next-Gener...
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This paper presents an innovative approach to soil health analysis specifically tailored for farmers in a Pune division. We addressing the unique agricultural needs of this region by leveraging advanced machine learni...
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This study presents and assesses the Adaptive learning Reinforcement (ALR) approach, a new patient education strategy that improves illness prevention and treatment. Behavioral incentives and AI provide a dynamic and ...
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Focusing on the issues of students' low efficiency in learning real-time big data processing and analysis techniques, as well as their weakness in solving comprehensive real-time big data problems, this article, g...
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The life cycle of machine learning (ML) applications consists of two stages: model development and model deployment. However, traditional ML systems (e.g., training-specific or inference-specific systems) focus on one...
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In this paper, a self-organizing interval type-2 fuzzy neural network based on singular value decomposition and QR decomposition with column pivoting (SVD-QR)method is proposed to solve the identification problem of n...
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Human pose and action detection technology has significant applications in areas such as smart security, sports monitoring, and human-computer interaction. The development of deep learning has driven the demand for re...
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