This paper is developed based on machine vision system and data mining techniques to
identify the cotton leaf spot diseases. The leaves are most probably affected by the fungi …

It could be seen that almost survival analysis in biomedical and healthcare are focusing on
survival time; related to how long individuals with disease will survive or dying. While most …

Feature selection carries significance in the outcome of any classification or regression task.
Exercising evolutionary computation algorithms in feature selection has led to the …

Investments made on the stock market depend on timely and credible information being
made available to investors. Such information can be sourced from online news articles …

Feature selection is an essential preprocessing step for classifiers with high dimensional
training sets. In pattern recognition, feature selection improves the performance of …

A mechanism for detecting Open Space Steganography (OSS) is described founded on the
observation that the length of white space segments increases in the presence of OSS. The …

Abstract Analysis and predictive modeling of massive datasets is an extremely significant
problem that arises in many practical applications. The task of predictive modeling becomes …

This PhD thesis explores and offers new ways for the profitable application of low-cost
spectral technologies in an industrial research context. The aim of this PhD is to develop …

Particle swarm optimization (PSO) algorithms have been successfully applied to discrete-
valued optimization problems. However, in many cases the algorithms have been tailored …

Data Quality and Data Preprocessing on an IoT-based Ecosystem for Smart Maintenance in the
Manufacturing Industry Page 1 Data Quality and Data Preprocessing on an IoT-based …