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An accurate analysis of fluid–structure interaction (FSI) at compliant arteries via ultrasound (US) imaging and numerical modeling is a limitation of several studies. In this study, we propose a deep learning-based boundary detection and compensation (DL-BDC) technique that can segment vessel boundaries by harnessing the convolutional neural network and wall motion compensation in near-wall flow dynamics. The segmentation performance of the technique is evaluated through numerical simulations with synthetic US images and in vitro experiments.

This dataset contains the actual sensor and calculated process variables in a winder station in a paper mill. Several Process variables change in time with the change of the rewind diameter. I provided the process data for two sets, in future I will add more data. Advanced time series forcasting techniques can be used to estimate many process variables considering the rewind diameter as the time axis.

These tables provide proof of the authenticity and reliability of the article.

The database was created with records of psychosocial risk level colombian teachers school using physiological variables from May 2016 to December 2017 in five municipalities of a metropolitan area of city in Colombia. The application of physiological variables was made to the people who voluntarily participated in the study. The names and personal data were kept by the researcher.

10,000 rows of sample data in four formats (CSV, JSON, XML, XLSX) for testing. Fields are as follows: seq, first, last, age, street, city, state, zip, dollar, pick, date, latitude, longitude, birthday, ccnumber, dollar, ccnumber, phone, email, sentence, paragraph

Reliability paremeters for UHVDC

AIM: Population aging is a worldwide phenomenon leading to increased life expectancy without necessarily meaning more years of autonomous life. Frailty is characterized by diminished strength, resistance and physiological function that increase vulnerability leading to dependency and mortality. While frailty diagnoses requires a clinical assessment of the patients overall health including at least five different criteria, the relationship among them it is little explored.