Results 11 to 20 of about 34,112,328 (298)

Data analytics: building a data driven culture

, 2020
One of the main obstacles to instituting evidence-based practice can lie in implementing data findings. Hence, even with a critical appreciation of data, HR and global mobility professionals face communications and cultural challenges.
Shortland, S.
core   +6 more sources

Chapter 3. Exploration and Explanation in Data-Driven Storytelling

, 2018
This chapter will explore the differences between and integration of exploration and explanation in visual data-driven storytelling. Exploratory visualizations allow for a lot of freedom which can include changing the visual representation, the focus of ...
Thudt, Alice, Dykes, Jason, Stasko, John, Gschwandtner, Theresia, Walny, Jagoda   +4 more
core   +4 more sources

Data‐driven execution of fast multipole methods [PDF]

Concurrency and Computation: Practice and Experience, 2013
SUMMARYFast multipole methods (FMMs) havecomplexity, are compute bound, and require very little synchronization, which makes them a favorable algorithm on next‐generation supercomputers. Their most common application is to accelerateN‐body problems, but they can also be used to solve boundary integral equations.
Hatem Ltaief, Rio Yokota
openaire   +4 more sources

Energy Theft in Smart Grids: A Survey on Data-Driven Attack Strategies and Detection Methods

IEEE Access, 2021
The convergence of legacy power system components with advanced networking and communication facilities have led towards the development of smart grids.
Ahlam Althobaiti, Anish Jindal, Angelos K. Marnerides, Utz Roedig   +3 more
doaj   +1 more source

Evaluation of respondent-driven sampling [PDF]

, 2012
Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred.
Joseph Katongole, Hayes, Richard J., Janet Seeley, Natasha L. Lunel, Tarsh, Matilda N., Richard J. Hayes, Maher, Dermot, Sonnenberg, Pam, Tarsh, Matilda N, Johnston, Lisa G., Hayes, Richard J, White, Richard G, White, Richard G., Lunel, Natasha L, Richard Ndunguse, Copas, Andrew J, Matilda N. Tarsh, Frost, Simon DW, Richard G. White, Andrew J. Copas, Seeley, Janet, Fatima Jichi, McCreesh, Nicky, Nicky McCreesh, Simon D. W. Frost, Lunel, Natasha L., Copas, Andrew J., Jichi, Fatima, Pam Sonnenberg, Frost, Simon D. W., Ndunguse, Richard, Lisa G. Johnston, Johnston, Lisa G, Katongole, Joseph, Dermot Maher   +34 more
core   +1 more source

Application of Data Driven Methods for Condition Monitoring Maintenance

Chemical Engineering Transactions, 2013
Nowadays, there is an increasing demand for Condition Based Maintenance (CBM) activities as time-directed maintenance are observed to be inefficient in many situations.
I. Marton, A. Sanchez, S. Carlos, S. Martorell   +3 more
doaj   +1 more source

Data-Driven Control-oriented Modelling of Submerged Arc Furnaces [PDF]

, 2023
openThe present thesis focuses on the integration of chemophysical knowledge and data-driven insights to develop control-oriented models for submerged arc furnaces (SAF).
FORNASIER, PIERANGELO
core  

Fault Log Recovery Using an Incomplete-data-trained FDA Classifier for Failure Diagnosis of Engineered Systems

International Journal of Prognostics and Health Management, 2016
In the 2015 PHM Data Challenge Competition, the goal of the competition problem was to diagnose failure of industrial plant systems using incomplete data. The available data consisted of sensor measurements, control reference signals, and fault logs.
Hyunjae Kim, Jong Moon Ha, Jungho Park, Sunuwe Kim, Keunsu Kim, Beom Chan Jang, Hyunseok Oh, Byeng D. Youn   +7 more
doaj   +1 more source

Predictive Equations for Estimation of the Slump of Concrete Using GEP and MARS Methods [PDF]

Journal of Soft Computing in Civil Engineering
This paper developed two robust data-driven models, namely gene expression programming (GEP) and multivariate adaptive regression splines (MARS), for the estimation of the slump of concrete (SL). The main feature of the proposed data-driven methods is to
Ismail Husein, Ramaswamy Sivaraman, Sarwar Hasan Mohmmad, Forqan Ali Hussein Al-Khafaji, Sokaina Issa Kadhim, Yousof Rezakhani   +5 more
doaj   +1 more source

Data-Driven Machine-Learning Methods for Diabetes Risk Prediction

Sensors, 2022
Diabetes mellitus is a chronic condition characterized by a disturbance in the metabolism of carbohydrates, fats and proteins. The most characteristic disorder in all forms of diabetes is hyperglycemia, i.e., elevated blood sugar levels.
Elias Dritsas, Maria Trigka
doaj   +1 more source