Diabetes Mellitus, is a widespread endocrine illness that affects the entire world today. This is a necessity for an effective model that can predict diabetes and its variants with greater accuracy as early as possibl...
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Stream processing has become a critical component in the architecture of modern applications. With the exponential growth of data generation from sources such as the Internet of Things, business intelligence, and tele...
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ISBN:
(纸本)9798350343946
Stream processing has become a critical component in the architecture of modern applications. With the exponential growth of data generation from sources such as the Internet of Things, business intelligence, and telecommunications, real-time processing of unbounded data streams has become a necessity. DSP systems provide a solution to this challenge, offering high horizontal scalability, fault-tolerant execution, and the ability to process data streams from multiple sources in a single DSP job. Often enough though, data streams need to be enriched with extra information for correct processing, which introduces additional dependencies and potential bottlenecks. In this paper, we present an in-depth evaluation of data enrichment methods for DSP systems and identify the different use cases for stream processing in modern systems. Using a representative DSP system and conducting the evaluation in a realistic cloud environment, we found that outsourcing enrichment data to the DSP system can improve performance for specific use cases. However, this increased resource consumption highlights the need for stream processing solutions specifically designed for the performance-intensive workloads of cloud-based applications.
This research aims to provide an approach for analyzing the security of the e-health care system through the pre-processing of different deep learning models and the usage of federated learning. Infrastructural suppor...
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The rate of development in today's IT industry is unprecedented. Information is being stored and transformed at a faster and faster rate. Therefore, the importance of protecting sensitive data is growing. Everyone...
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Distributed optical fiber sensing technology can achieve distributed measurement of temperature and strain at any position of buried pipelines, but the post-dataprocessing process is quite cumbersome. In order to con...
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Underwater acoustic communication is the most reliable way of underwater long-distance communication. However, due to the harsh underwater environments, the battery capacity of underwater acoustic sensor nodes is limi...
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Quantum algorithms face practical difficulties and overheads in execution on realistic devices, potentially thwarting their theoretical advantages. A key practical challenge is efficiently encoding classical data, sin...
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In a medical problem, investigation of powerful new tools is involved in essential role of high-throughput sequencing technologies. Microarray data sequencers produced a large and complex sets of data for the advancem...
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The rise of the Internet of Things (IoT) has led to the development of smart cities, where various systems and devices are interconnected and constantly generating large amounts of data. Edge computing, which enables ...
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With the rapid growth of social media platforms, Twitter has emerged as a valuable source that provides real-time data on public opinion, sentiment, and trends through approximately 7500 tweets per second, enabling in...
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