scholarly journals A data‐driven approach for predicting nepheline crystallization in high‐level waste glasses

2020 ◽  
Vol 103 (9) ◽  
pp. 4913-4924
Author(s):  
Irmak Sargin ◽  
Charmayne E. Lonergan ◽  
John D. Vienna ◽  
John S. McCloy ◽  
Scott P. Beckman
Keyword(s):  
Data Driven ◽  
High Level Waste ◽  
Data Driven Approach ◽  
High Level

scholarly journals A data‐driven approach to stimulus selection reveals an image‐based representation of objects in high‐level visual areas

2019 ◽  
Vol 40 (16) ◽  
pp. 4716-4731 ◽  
Author(s):  
David D. Coggan ◽  
Afrodite Giannakopoulou ◽  
Sanah Ali ◽  
Burcu Goz ◽  
David M. Watson ◽  
...  
Keyword(s):  
Data Driven ◽  
Stimulus Selection ◽  
Visual Areas ◽  
Data Driven Approach ◽  
High Level

The Vanderbilt PICC Service: Program, Procedural, and Patient Outcomes Successes

2005 ◽  
Vol 10 (4) ◽  
pp. 183-192 ◽  
Author(s):  
Doug Burns
Keyword(s):  
Patient Outcomes ◽  
Medical Center ◽  
Nursing Program ◽  
Data Driven ◽  
Complication Rates ◽  
Advanced Practice ◽  
The Past ◽  
Data Driven Approach ◽  
High Level ◽  
Vanderbilt University

Abstract Since its inception in early 2000, Vanderbilt University's Peripherally Inserted Central Catheter (PICC) Service has experienced a high level of success as measured by high proficiency rates and increasing patient procedures each year, low complication rates during and after PICC placements, and an increasing scope of influence within the Vanderbilt University Medical Center and Children's Hospital, the surrounding community, and in the Southeastern United States. Primary drivers of the PICC Service's continuing success include consistent applications of technique and technology, a data-driven approach to assessing the program's progress, and appropriately managing customers' expectations and needs. Over the past five years, data were collected on more than 12,500 PICC placements performed in this specialized nursing program. Retrospective analyses of the data demonstrate an increasing rate of successful placements (from 87.2% to 92.4%) since the program's inception in 2000 to late 2004. Furthermore, the choice of PICC technology has had a significant impact on the odds for occlusion or infection. The Vanderbilt PICC Service provides a model by which other programs can be established, maintained, and expanded into advanced practice.

scholarly journals A Data-Driven Approach to the Development and Understanding of Chiroptical Sensors for Alcohols with Remote γ-Stereocenters

2021 ◽  
Author(s):  
Jordan Dotson ◽  
Eric Anslyn ◽  
Matthew Sigman
Keyword(s):  
Density Functional ◽  
Level Density ◽  
Enantiomeric Excess ◽  
Data Driven ◽  
Functional Theory ◽  
Dynamic Covalent Chemistry ◽  
Sensor Optimization ◽  
Data Driven Approach ◽  
High Level ◽  
Sensor Molecules

Dynamic covalent chemistry-based sensors have recently emerged as powerful tools to rapidly determine the enantiomeric excess of organic small molecules. While a bevy of sensors have been developed, those for flexible molecules with stereocenters remote to the functional group that binds the chiroptical sensor remain scarce. In this study, we develop an iterative, data-driven workflow to design and analyze a chiroptical sensor capable of assessing challenging acyclic γ-stereogenic alcohols. Fol-lowing sensor optimization, the mechanism of sensing was probed with a combination of computational parameterization of the sensor molecules, statistical modeling, and high-level density functional theory (DFT) calculations. These were used to elucidate the mechanism of stereochemical recognition and revealed that competing attractive non-covalent interactions (NCIs) determine the overall performance of the sensor. It is anticipated that the data-driven workflows developed herein will be generally applicable to the development and understanding of dynamic covalent and supramolecular sensors.

Designing And Optimizing Production In A High Variety / Low Volume Environment Through Data-Driven Simulation

2021 ◽  
Author(s):  
Virginia Fani ◽  
Bianca Bindi ◽  
Romeo Bandinelli
Keyword(s):  
Simulation Model ◽  
Production Systems ◽  
Discrete Event ◽  
Simulation Models ◽  
Product Variety ◽  
Data Driven ◽  
Business Decisions ◽  
Footwear Industry ◽  
Data Driven Approach ◽  
High Level

HVLV environments are characterized by high product variety and small lot production, pushing companies to recursively design and optimize their production systems in a very short time to reach high-level performance. To increase their competitiveness, companies belonging to these industries, often SMEs working as third parties, ask for decision-making tools to support them in a quick and reactive reconfiguration of their production lines. Traditional discrete event simulation models, widely studied in the literature to solve production-related issues, do not allow real-time support to business decisions in dynamic contexts, due to the time-consuming activities needed to re-align parameters to changing environments. Data-driven approach overcomes these limitations, giving the possibility to easily update input and quickly rebuild the model itself without any changes in the modeling code. The proposed data-driven simulation model has also been interfaced with a commonly-used BI tool to support companies in the iterative comparison of different scenarios to define the optimal resource allocation for the requested production plan. The simulation model has been implemented into a SME operating in the footwear industry, showing how this approach can be used by companies to increase their performance even without a specific knowledge in building and validating simulation models.

scholarly journals A data driven approach to understanding the organization of high-level visual cortex

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
David M. Watson ◽  
Timothy J. Andrews ◽  
Tom Hartley
Keyword(s):  
Visual Cortex ◽  
Data Driven ◽  
Data Driven Approach ◽  
High Level

scholarly journals Application of neural ordinary differential equations to the prediction of multi-agent systems

2021 ◽  
Author(s):  
Sebastian Herzog ◽  
Florentin Wörgötter
Keyword(s):  
Differential Equations ◽  
Dynamic Systems ◽  
Data Driven ◽  
Multi Agent System ◽  
Multi Agent Systems ◽  
Detailed Understanding ◽  
Agent Systems ◽  
Data Driven Approach ◽  
Multi Agent ◽  
High Level

AbstractDynamic systems are usually described by differential equations, but formulating these equations requires a high level of expertise and a detailed understanding of the observed system to be modelled. In this work, we present a data-driven approach, which tries to find a parameterization of neural differential equations system to describe the underlying dynamic of the observed data. The presented method is applied to a multi-agent system with thousand agents.

Data Driven Approach to Forecast Building Occupant Complaints

2020 ◽  
Author(s):  
Sena Assaf ◽  
Mohamad Awada ◽  
Issam Srour
Keyword(s):  
Data Driven ◽  
Data Driven Approach

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

2012 ◽  
Author(s):  
Michael Ghil ◽  
Mickael D. Chekroun ◽  
Dmitri Kondrashov ◽  
Michael K. Tippett ◽  
Andrew Robertson ◽  
...  
Keyword(s):  
Dynamic Models ◽  
Data Driven ◽  
Stochastic Dynamic ◽  
Extended Range ◽  
Data Driven Approach ◽  
Low Dimensional
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