An analytical model of condensed explosives under slow cook-off conditions was established based on the superposition principle and Sturm–Liouville method. The analytical model can quickly and ...
Coreless stator axial flux permanent magnet (CS-AFPM) machines have found many applications, such as electric vehicle and wind energy generation systems, due to their high power and torque density, ...
In explaining a data and analytics operating model, it is helpful to understand the business context. As the consumer experience becomes increasingly digitized, companies have access to massive troves ...
Founder and Managing Principal of DBP Institute. I consult companies on how to transform technology and data into a valuable business asset. There are many reasons for this poor success rate, one of ...
Inaccurate or overlooked alerts on manufacturing data can be reduced with proper data handling when developing and deploying predictive models. Data analytics, and specifically predictive analytics, ...
Rohit Amarnath is CTO of Vertica, a unified analytics platform that enables predictive business insights based on a scalable architecture. There’s no debate: Data is one of the most valuable assets ...
"Analytics as a discipline has changed dramatically in the last five to 10 years – and for sure in the past five," says Anne Snowdon, chief scientific research officer at HIMSS. "With the explosion of ...
Sparse data can impact the effectiveness of machine learning models. As students and experts alike experiment with diverse datasets, sparse data poses a challenge. The Leeds Master’s in Business ...
Introduction Economic evidence on community health worker (CHW) programmes is crucial for scaling these initiatives. Although decision-analytic models (DAMs) are essential for projecting long-term ...
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