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Titlebook: Emerging Technologies in Computing; 6th EAI Internationa Mahdi H. Miraz,Garfield Southall,Andrew Ware Conference proceedings 2024 ICST Inst

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楼主: affront
发表于 2025-3-25 06:22:05 | 显示全部楼层
Event-Based Data Pipelines in Recommender Systems: The Data Engineering Perspectives. Event-based data pipelines have emerged as a popular approach to handle the massive amount of data generated by modern applications. In this paper, we explore the impact of event-based data pipelines on recommendation systems. We discuss how these pipelines enable efficient data ingestion, real-time processing, and low-latency recommendations.
发表于 2025-3-25 10:25:12 | 显示全部楼层
1867-8211 cal sections covering AI, expert systems and big data analytics; information and network security; cloud, IoT and distributed computing..978-3-031-50214-9978-3-031-50215-6Series ISSN 1867-8211 Series E-ISSN 1867-822X
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https://doi.org/10.1007/978-4-431-67949-3hes such as image processing techniques and deep learning architectures are thus employed. The paper focuses on the survey of various detection, identification, and classification methods of malware and is an effort to put forward the best approach.
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Physiology and agronomy of , symbiosisuse they don’t know where the grass is actually grown. So, a lot of fuel or electricity is wasted during that process. We want to overcome those problems. Our proposed idea is that we will create an automation system that will detect field moisture, grass growth and it will report the field condition to a device.
发表于 2025-3-26 12:08:37 | 显示全部楼层
Academic Integrity in the Face of Generative Language Modelstices, as well as the challenges of identifying and combating academic dishonesty. Some measures universities and academics may employ in order to mitigate such risks are proposed, and several strategies and tools for detecting AI-generated content are discussed, along with their limitations.
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A Literature Review of Various Analysis Methods and Classification techniques of Malwarehes such as image processing techniques and deep learning architectures are thus employed. The paper focuses on the survey of various detection, identification, and classification methods of malware and is an effort to put forward the best approach.
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