BIG DATA IN CHEMICAL ENGINEERING

Algorithm Engineering for Big Data

Perhaps the most fundamental challenge implied by advanced applications of big data sets is how to perform the vast amount of required computations sufficiently efficiently. Efficient algorithms are at the heart of this question. But how can we obtain innovative algorithmic solutions for demanding application problems with exploding input sizes using complex modern hardware and advanced algorit...

EVALUATING EFFICIENCY OF BIG-BANG BIG-CRUNCH ALGORITHM IN BENCHMARK ENGINEERING OPTIMIZATION PROBLEMS

Engineering optimization needs easy-to-use and efficient optimization tools that can be employed for practical purposes. In this context, stochastic search techniques have good reputation and wide acceptability as being powerful tools for solving complex engineering optimization problems. However, increased complexity of some metaheuristic algorithms sometimes makes it difficult for engineers t...

A Privacy Engineering Framework for Big Data

In the Big Data era, the collection and mining of high-dimensional user data has become a fast growing and common practice by a large number of private and public institutions. In some cases, these institutions share data with third parties without an anonymity preferring user’s consent or awareness, thereby risking his privacy. In other cases, data is released voluntarily by a user not necessa...

Software Engineering for Big Data Systems

Privacy and Security of Big Data in THE Cloud

Big data has been arising a growing interest in both scien- tific and industrial fields for its potential value. However, before employing big data technology into massive appli- cations, a basic but also principle topic should be investigated: security and privacy. One of the biggest concerns of big data is privacy. However, the study on big data privacy is still at a very early stage. Many or...