Purpose: Integration of ICCT underlying technologies and big data technology to develop a
new kind of Business analytics that can be used to solve semi-structured and unstructured …

In the pandemic time, the monitoring of the progression of some diseases is affected and
rehabilitation is more complicated. Remote monitoring may help solve this problem using …

This research develops a regression-based Robust Optimization (RO) approach to efficiently
predict the number of patients with confirmed infection caused by the recent Coronavirus …

Customer churn is a complex challenge for burgeoning competitive organizations,
especially in telecommunication. It refers to customers that swiftly leave a company for a …

Being able to predict the churn rate is the key to success for the telecommunication industry.
It is also important for the telecommunication industry to obtain a high profit. Thus, the …

Air pollution is becoming a rising and serious environmental problem, especially in urban
areas affected by an increasing migration rate. The large availability of sensor data enables …

Companies in a wide variety of industries use the customer churn prediction (CCP) process
to keep their current clientele happy. Insurance companies need to be able to forecast churn …

Large-scale labeled datasets are generally necessary for successfully training a deep
neural network in the computer vision domain. In order to avoid the costly and tedious work …

To model the data and functions in various computer science applications, the researcher
uses a Data Flow Diagram (DFD). DFD has been constructed using [open-source software …

One type of data-driven innovations in management is data-driven decision making.
Confronted with a big amount of data external and internal to their organization's managers …