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Techniques employed in distributed cognitive radio networks: a survey on routing intelligence
In order to meet the growing needs for wireless communication in dynamic and diverse circumstances, Cognitive Radio Networks (CRNs) have evolved as a...
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The Energy Data Space: The Path to a European Approach for Energy
Trusted data spaces supporting energy services and fostering collaboration between all stakeholders are a cornerstone of the decarbonization of the...
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Scaled gated networks
Gating transformation demonstrates great potential in recent deep convolutional neural networks design, enriching the feature representation and...
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Experience report: investigating bug fixes in machine learning frameworks/libraries
Machine learning (ML) techniques and algorithms have been successfully and widely used in various areas including software engineering tasks. Like...
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Techniques Used for the Prediction of Number of Faults
PredictionPrediction ofTechniques number of faultsFaults refers to the process of estimating/predicting a potential number of faults that can...
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A critical review on applications of artificial intelligence in manufacturing
The fourth industrial revolution, Industry 4.0, has brought internet, artificial intelligence (AI), and machine learning (ML) concepts into...
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FusFormer: global and detail feature fusion transformer for semantic segmentation of small objects
Improving the segmentation accuracy of small objects is essential for tasks such as autono-mous driving and remote sensing. However, the current main...
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Roadmap for digital technology to foster India’s MSME ecosystem—opportunities and challenges
Digital technology can significantly enable India’s MSME segment, provided the emerging infrastructure has joint buy-in from the government, solution...
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Visualizations for universal deep-feature representations: survey and taxonomy
In data science and content-based retrieval, we find many domain-specific techniques that employ a data processing pipeline with two fundamental...
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Big Data-Driven Industry 4.0 Service Engineering Large-Scale Trials: The Boost 4.0 Experience
In the last few years, the potential impact of big data on the manufacturing industry has received enormous attention. This chapter details two...
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Machine Learning Methods for BIM Data
This paper presents a survey of machine learning methods used in applications dedicated to building and construction industry. A BIM model being a...
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Measurement and Quantification
This chapter deals with the clinical task of measuring and quantifying cardiac morphology and function. The chapter opens with a clinical...
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Global vs. local models for cross-project defect prediction
Although researchers invested significant effort, the performance of defect prediction in a cross-project setting, i.e., with data that does not come...
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Web service recommendation for mashup creation based on graph network
In recent years, the world has witnessed the increased maturity of service-oriented computing. The mashup, as one of the typical service-based...
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AI and IoT in Manufacturing and Related Security Perspectives for Industry 4.0
The impact of artificial intelligence (AI) in the manufacturing sector gives a game changing environment in industries. Every manufacturer aims to...
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A feature selection approach based on a similarity measure for software defect prediction
Software defect prediction is aimed to find potential defects based on historical data and software features. Software features can reflect the...
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Resource scheduling techniques in cloud from a view of coordination: a holistic survey
Nowadays, the management of resource contention in shared cloud remains a pending problem. The evolution and deployment of new application paradigms...
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VaryMinions: leveraging RNNs to identify variants in variability-intensive systems’ logs
From business processes to course management, variability-intensive software systems (VIS) are now ubiquitous. One can configure these systems’...
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A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance....
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Discussion on a new paradigm of endogenous security towards 6G networks
The sixth-generation mobile communication (6G) networks will face more complex endogenous security problems, and it is urgent to propose new...