Data-driven customer acceptance for attended home delivery.

Home delivery services require the attendance of the customer during delivery. Hence, retailers and customers mutually agree on a delivery time window in the booking process. However, when a customer requests a time window, it is not clear how much accepting the ongoing request significantly reduces the availability of time windows for future customers.

Assessment of transportation system disruption and accessibility to critical amenities during flooding: Iowa case study.

Natural disasters, such as flooding, can cause severe social, environmental, and economic damage to a community. Transportation infrastructure plays an essential role in flood response and recovery efforts. However, flooding may disturb road functionality and generate direct and indirect adverse impacts, including the loss of access to essential services.

Prediction of ultrasound-mediated disruption of cell membranes using machine learning techniques and statistical analysis of acoustic spectra.

Although biological effects of ultrasound must be avoided for safe diagnostic applications, ultrasound's ability to disrupt cell membranes has attracted interest as a method to facilitate drug and gene delivery. This paper seeks to develop "prediction rules" for predicting the degree of cell membrane disruption based on specified ultrasound parameters and measured acoustic signals. Three techniques for generating prediction rules (regression analysis, classification trees and discriminant analysis) are applied to data obtained from a sequence of experiments on bovine red blood cells.