Results 231 to 240 of about 293,978 (266)
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2001
After an introduction to self-similar deterministic and random measures, we introduce an algorithm which decides on the separation condition for given similarity mappings defining a self-similar set. We construct some new types of Sierpinski gasket and determine their exponent of interior distance.
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After an introduction to self-similar deterministic and random measures, we introduce an algorithm which decides on the separation condition for given similarity mappings defining a self-similar set. We construct some new types of Sierpinski gasket and determine their exponent of interior distance.
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Hypergraph Similarity Measures
IEEE Transactions on Network Science and Engineering, 2023Amit Surana, Can Chen, Indika Rajapakse
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Social determinants of health and US cancer screening interventions: A systematic review
Ca-A Cancer Journal for Clinicians, 2023Ariella R Korn
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Semantic Similarity Functions and Measures
2019Similarity is the process through which two or more objects are compared in order to identify to what extent they are alike. This is useful, for instance, when there is the need to identify common elements among a set of objects or when a new object has to be classified w.r.t. the others.
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Frailty and cancer: Implications for oncology surgery, medical oncology, and radiation oncology
Ca-A Cancer Journal for Clinicians, 2017Cecilia G Ethun +2 more
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Mesothelioma: Scientific clues for prevention, diagnosis, and therapy
Ca-A Cancer Journal for Clinicians, 2019Michele Carbone +2 more
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Who's still smoking? Disparities in adult cigarette smoking prevalence in the United States
Ca-A Cancer Journal for Clinicians, 2018Alex C Liber +2 more
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