Energy budgets’ formation based on incomplete data

Ensemble-based Top-k Recommender System Considering Incomplete Data

Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ratings to make robust predictions and suggesting qualified recommendations are two si...

Power Management for Wireless Sensor Networks Based on Energy Budgets

This paper proposes and assesses analytical tools for largescale monitoring applications with wireless sensor networks powered by energy-harvesting supplies. We introduce the concept of an energy budget, the amount of energy available to a sensor node for a given period of time. The presented tools can be utilized to realize distributed algorithms that determine a schedule to perform the monito...

Image Reconstruction from Incomplete Data

Image Reconstruction from Incomplete Data

Average Life Prediction Based on Incomplete Data

The two-parameter exponential distribution can often be used to describe the lifetime of products for example, electronic components, engines and so on. This paper considers a prediction problem arising in the life test of key parts in high speed trains. Employing the Bayes method, a joint prior is used to describe the variability of the parameters but the form of the prior is not specified and...