Computational Intelligence

The experimental dataset involves the interval values for the bed slope (m/m) measured with a theodolite, the river flow rate (m^3/s), and the average surface velocity (m/s) from the Ter River (Spain).
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There are no explicit labelled errors in FB15K. Considering the experience that most errors in real-world KG derive from the misunderstanding between similar entities, we consider the methods described in paper "DoesWilliamShakespeareREALLYWrite Hamlet? Knowledge Representation Learning with Confidence" to generate fake triples as negative examples automatically with less human annotation. Three kinds of fake triples may be constructed for each true triple: one by replacing head entity, one by replacing relationship, and one by replacing tail entity.
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The simplicity of deployment and perpetual operation of energy harvesting devices provides a compelling proposition for a new class of edge devices for the Internet of Things. In particular, Computational Radio Frequency Identification (CRFID) devices are an emerging class of battery-free, computational, sensing enhanced devices that harvest all of their energy for operation.
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The goal of the benchmark test library is to offer a set of tests which are wide in feature coverage, progressive and stable. It serves the purpose of evaluating the strength and weakness of matchers (by being progressive and wide coverage) and measuring the progress of matchers (by being stable and reusable over the years).
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test
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This is the code and data for IS-RNN validation and research
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Dataset used in paper "Machine Learning Cryptanalysis of a Quantum Random Number Generator" published at IEEE TIFS https://ieeexplore.ieee.org/document/8396276.
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This dataset contains user online reviews of two tourist places namely London' Parks and Art Museums.
London Parks Reviews
In this dataset, the top five most visited parks are selected, such as St. James' Park, Hyde Park, Regent's Park, Kensington Park and Greenwich Park. For each park, 600 reviews from Jan to Sep 2017 are present in CSV format.
London Art Museums
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Automatic classification of sensitive content in remote sensing images, such as drug crop sites, is a promising task as it can aid law-enforcement institutions fighting illegal drug dealers worldwide, while, at the same time, it can help monitoring legalized crops in countries that regulate them. However, existing art on detecting drug crops from remote sensing images is limited in some key factors not taking full advantage of the available hyperspectral info for analysis.
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Machine learning is becoming increasingly important for companies and the scientific community. It allows us to generate solutions for several problems faced by society. In this study, we perform a science mapping analysis on the machine learning research, in order to provide an overview of the scientific work during the last decade in this area and to show trends that could be the basis for future developments in the field of computer science. This study was carried out using the CiteSpace and SciMAT tools based on results from Scopus and Clarivate Web of Science.
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