AN η-INTUITIONISTIC FUZZY RINGS STRUCTURE

An η-Intuitionistic Fuzzy Rings Structure

In this article, we present the structure of η-intuitionistic fuzzy ring.An η-intuitionistic Gameboy Advance fuzzy ring is a structure which is built with combinating the definition of fuzzy ring, intuitionistic fuzzy set, and η-intuitionistic fuzzy set.The η-intuitionistic fuzzy set is characterized by any value η∈[0,1], where the degree of

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Reflections on the Intermediate Data Structure (IDS)

The Intermediate Data Structure (IDS) encourages sharing historical life course data by storing data in a Baby Crewneck Cardigan common format.To encompass the complexity of life histories, IDS relies on data structures that are unfamiliar to most social scientists.This article examines four features of IDS that make it flexible and expandable: the

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The role of socioeconomic and environmental factors on pediatric vehicular heatstroke (PVH) deaths and sentiment analysis: An investigation

Pediatric Vehicular Heatstroke (PVH) has been among the leading cause of non-traffic deaths among kids in the US.According to NHTSA, more than 900 children have died since 1998 because of being left in cars or accessing the cars without notice by adults.As of 2020, 40% of the 50 US states and Washington DC have policies on hot car deaths.This paper

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Pulse oximetry: fundamentals and technology update

Meir Nitzan,1 Ayal Romem,2 Robert Koppel31Department of Physics/Electro-Optics, Jerusalem College of Technology, Jerusalem, Israel; 2Pulmonary Institute, Shaare Zedek Medical Center, Jerusalem, Israel; 3Neonatal/Perinatal Medicine, Cohen Children's Medical Center of New York/North Shore-LIJ Health System, New Hyde Park, NY, United StatesAbstrac

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Integrating data science into the translational science research spectrum: A substance use disorder case study

The availability of large healthcare datasets offers the opportunity for researchers to navigate the traditional clinical and translational science research stages in a nonlinear manner.In particular, data scientists can harness the power of large healthcare datasets to bridge from preclinical discoveries (T0) directly to assessing population-level

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