A growing number of manufacturing businesses are becoming more concerned with energy efficiency because of rising energy costs and environmental consciousness. The enormous shift of an organization's resource requ...
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The food delivery market is spreading fast, so predicting delivery times, so that customers are happy and operations work efficiently, is possible. The research combines machine learning techniques with geospatial ana...
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The convolutional neural network (CNN) is widely utilized in computer vision due to its ability to effectively harness correlation information within data. However, when the data's dimensionality or the model'...
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Sketch education is an essential component of arts education. In recent years, with the development of society, the demand for sketch courses has been steadily increasing. However, the existing teaching resources are ...
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In this paper, we provide a detailed examination of energy consumption within specific sections of the Pecan Street Data Set. We employ two primary method-ologies: the Additive Factorial Approximate MAP (AFAMAP) algor...
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Quantum computing are breakthroughs aimed to revolutionize several sectors, although they also present considerable cybersecurity threats. Quantum computers can manage quite greater quantities of information than the ...
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Exponential growth of Internet and social media during the past few decades has helped the users to pass any information without even analyzing. Out of these many are fake information which has got no authenticity and...
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Cloud computing contains lots of processing power and storage. Cloud computing and machine learning (ML) techniques enable large-scale data processing. The enhanced ML-based categorization technique is established in ...
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Identifying the type of network traffic has several advantages, such as detecting and preventing applications that violate an organization's security policy or improving Quality of Service (QoS) and Quality of Exp...
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ISBN:
(纸本)9798350333398
Identifying the type of network traffic has several advantages, such as detecting and preventing applications that violate an organization's security policy or improving Quality of Service (QoS) and Quality of Experience (QoE) through traffic engineering. To enhance QoS support for Internet Service Providers (ISPs), a fine-grained classification scheme for network traffic is proposed in this paper. Statistical analysis of the throughput patterns of FTP, video conferencing, and video streaming traffic reveal that using new statistical features can be more effective at distinguishing the Internet traffic, especially from a QoS perspective, compared to the features commonly used in the literature, even for encrypted traffic. In this work, machine learning algorithms for classifying the low-latency traffic are trained using combinations of statistical features including the novel trend identification. Experiments are conducted to evaluate the proposed method using large-scale real network traffic data. Results show that our method can classify the particular type of traffic with accuracy of over 97%, and identify the low-latency traffic in the traffic mix with accuracy of 87%.
The term ''Web analytics'' pertains to the act of monitoring, analysing, and creating reports regarding the use of a website, such as its web pages, images, and videos. By utilising web analytics, busi...
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