scholarly journals The Ionic Liquid Property Explorer: An Extensive Library of Task-Specific Solvents

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 88
Author(s):  
Vishwesh Venkatraman ◽  
Sigvart Evjen ◽  
Kallidanthiyil Chellappan Lethesh
Keyword(s):  
Ionic Liquids ◽  
Statistical Models ◽  
Data Driven ◽  
Virtual Library ◽  
Equilibrium Thermodynamics ◽  
Data Set ◽  
Using Data ◽  
Liquid Property ◽  
Selection Of ◽  
Transition Heat

Ionic liquids have a broad spectrum of applications ranging from gas separation to sensors and pharmaceuticals. Rational selection of the constituent ions is key to achieving tailor-made materials with functional properties. To facilitate the discovery of new ionic liquids for sustainable applications, we have created a virtual library of over 8 million synthetically feasible ionic liquids. Each structure has been evaluated for their-task suitability using data-driven statistical models calculated for 12 highly relevant properties: melting point, thermal decomposition, glass transition, heat capacity, viscosity, density, cytotoxicity, CO 2 solubility, surface tension, and electrical and thermal conductivity. For comparison, values of six properties computed using quantum chemistry based equilibrium thermodynamics COSMO-RS methods are also provided. We believe the data set will be useful for future efforts directed towards targeted synthesis and optimization.

A Review and evaluation of Machine Translation methods for Lumasaaba

2020 ◽  
pp. 3-17
Author(s):  
Peter Nabende
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Machine Translation ◽  
Language Processing ◽  
Research Area ◽  
Data Driven ◽  
East African ◽  
Data Set ◽  
African Languages ◽  
Translation Methods

Natural Language Processing for under-resourced languages is now a mainstream research area. However, there are limited studies on Natural Language Processing applications for many indigenous East African languages. As a contribution to covering the current gap of knowledge, this paper focuses on evaluating the application of well-established machine translation methods for one heavily under-resourced indigenous East African language called Lumasaaba. Specifically, we review the most common machine translation methods in the context of Lumasaaba including both rule-based and data-driven methods. Then we apply a state of the art data-driven machine translation method to learn models for automating translation between Lumasaaba and English using a very limited data set of parallel sentences. Automatic evaluation results show that a transformer-based Neural Machine Translation model architecture leads to consistently better BLEU scores than the recurrent neural network-based models. Moreover, the automatically generated translations can be comprehended to a reasonable extent and are usually associated with the source language input.

Development of a Pediatric Early Warning System Using Data-Driven Vital Signs

PEDIATRICS ◽  
2016 ◽  
Vol 137 (Supplement 3) ◽  
pp. 256A-256A
Author(s):  
Catherine Ross ◽  
Iliana Harrysson ◽  
Lynda Knight ◽  
Veena Goel ◽  
Sarah Poole ◽  
...  
Keyword(s):  
Early Warning ◽  
Early Warning System ◽  
Vital Signs ◽  
Warning System ◽  
Data Driven ◽  
Using Data

K-MEANS CLUSTERING ALGORITHM FOR SERVICE DATA ANALYSIS BASED ON CUSTOMERS COMBINATION

2018 ◽  
Vol 3 (1) ◽  
pp. 001
Author(s):  
Zulhendra Zulhendra ◽  
Gunadi Widi Nurcahyo ◽  
Julius Santony
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Clustering Algorithm ◽  
Customer Complaints ◽  
Using Data ◽  
Clustering Data ◽  
Service Data ◽  
Selection Of

In this study using Data Mining, namely K-Means Clustering. Data Mining can be used in searching for a large enough data analysis that aims to enable Indocomputer to know and classify service data based on customer complaints using Weka Software. In this study using the algorithm K-Means Clustering to predict or classify complaints about hardware damage on Payakumbuh Indocomputer. And can find out the data of Laptop brands most do service on Indocomputer Payakumbuh as one of the recommendations to consumers for the selection of Laptops.

Application of experimental design for selection of optimal modes of electro-deformation cladding with a flexible tool

2020 ◽  
pp. 71-76
Author(s):  
M.A. Levantsevich ◽  
E.V. Pilipchuk ◽  
N.N Maksimchenko ◽  
L.S. Belevskiy ◽  
R.R. Dema
Keyword(s):  
Composite Material ◽  
Experimental Design ◽  
Statistical Models ◽  
Experiment Planning ◽  
Flexible Tool ◽  
Tool Coating ◽  
Coating Composite ◽  
Selection Of

Experimental-statistical models of the process of forming composite chromium coatings by electrodeformation cladding with a flexible tool are developed, which allow to determine the parameters of the regimes for obtaining coatings of the required thickness and roughness. Keywords electrodeformation cladding, flexible tool, coating, composite material, experiment planning, noncompositional plan, thickness, roughness. [email protected]

Founding Family Ownership and the Selection of Industry Specialist Auditors

2014 ◽  
Vol 28 (2) ◽  
pp. 261-276 ◽  
Author(s):  
Fei Kang
Keyword(s):  
Financial Reporting ◽  
Family Firms ◽  
Structure And Agency ◽  
Founding Family ◽  
Using Data ◽  
Dual Class Shares ◽  
Dual Class ◽  
Selection Of ◽  
Industry Specialist

SYNOPSIS This study examines how family firms' unique ownership structure and agency problems affect their selection of industry-specialist auditors. Using data from Standard & Poor's (S&P) 1500 firms, the results show that family firms are more likely to appoint industry-specialist auditors than non-family firms, which suggests that family firms have strong incentives to signal the quality of financial reporting. Additional analysis indicates that due to the potential entrenchment problems, family firms with family member CEOs or with dual-class shares have even a higher tendency to hire industry-specialist auditors to signal their disclosure quality.

Engagement Through the Diaspora Channel

2017 ◽  
Author(s):  
Michael S. Danielson
Keyword(s):  
Civil Society ◽  
Statistical Models ◽  
State Level ◽  
The State ◽  
Multivariate Statistical ◽  
Political Factors ◽  
Data Set ◽  
Level Data ◽  
Municipal Level

The first empirical task is to identify the characteristics of municipalities which US-based migrants have come together to support financially. Using a nationwide, municipal-level data set compiled by the author, the chapter estimates several multivariate statistical models to compare municipalities that did not benefit from the 3x1 Program for Migrants with those that did, and seeks to explain variation in the number and value of 3x1 projects. The analysis shows that migrants are more likely to contribute where migrant civil society has become more deeply institutionalized at the state level and in places with longer histories as migrant-sending places. Furthermore, the results suggest that political factors are at play, as projects have disproportionately benefited states and municipalities where the PAN had a stronger presence, with fewer occurring elsewhere.

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