Vol. 25, No. 1

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Now showing 1 - 5 of 23

Spiral Extrusion Die Design using Modified Differential Evolution Algorithm
(Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24) Pluhacek, Michal; Hrdy, Michal; Viktorin, Adam; Kadavy, Tomas; Senkerik, Roman
In this work, a spiral extrusion die for industrial production of plastic foil has been designed using a modified differential evolution algorithm. The proposed method managed to provide a die design that was compliant with all demands of the foil manufacturer and lowered the production cost. Third-Party software is used to compute the die characteristics from the geometry designed by modified differential evolution.
Predicting the Spread of Malware Outbreaks Using Autoencoder Based Neutral Networks
(Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24) Gopika, Bhardwaj; Rashi, Yadav
Malware Outbreaks are pervasive in today's digital world. However, there is a lack of awareness on part of general public on how to safeguard against such attacks and a need for increased cooperation between various national and international research as well as governmental organizations to combat the threat. On the positive side, cyber security websites, blogs and newsletters post articles outlining the working and spread of a malware outbreak and steps to recover from the same as well. In this project, an effective approach to predicting the spread of malware outbreaks is presented. The scope of the project is 15 Malware Outbreaks and the approach involves collecting these cyber aware articles from the web, assigning them to the 15 Malware Outbreaks using Topic Modeling and Similarity Analysis and along with Spread information of the Malware Outbreaks, this is input to auto encoder neural network for learning latent space representations which are further used to predict the spread of malware outbreak as either high or low spread outbreak, achieving a prediction accuracy of 75.56. This work can be used to process large amount of cyber aware content for effective and accurate prediction in the era of much-needed cyber security.
InterRC: An Inter-Resources Collaboration Heuristic for Scheduling Independent Tasks on Heterogeneous Distributed Environments
(Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24) Khiat, Abdelhamid; Tari, Abdelkamel
The independent task scheduling problem in distributed computing environments with makespan optimization as an objective is an NP-Hard problem. Consequently, an important number of approaches looking to approximate the optimal makespan in reasonable time have been proposed in the literature. In this paper, a new independent task scheduling heuristic called InterRC is presented. The proposed InterRC solution is an evolutionary approach, which starts with an initial solution, then executes a set of iterations, for the purpose of improving the initial solution and close the optimal makespan as soon as possible. Experiments show that InterRC obtains a better makespan compared to the other efficient algorithms.
Efficient Computation of Fitness Function for Evolutionary Clustering
(Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24) Muravyov, Sergey; Antipov, Denis; Buzdalova, Arina; Filchenkov, Andrey
Evolutionary algorithms (EAs) are random search heuristics which can solve various optimization problems. There are plenty of papers describing different approaches developed to apply evolutionary algorithms to the clustering problem, although none of them addressed the problem of fitness function computation. In clustering, many clustering validity indices exist that are designed to evaluate quality of resulting points partition. It is hard to use them as a fitness function due to their computational complexity. In this paper, we propose an efficient method for iterative computation of clustering validity indices which makes application of the EAs to this problem much more appropriate than it was before.
Ant Colony Optimisation for Performing Computational Task in Cellular Automata
(Institute of Automation and Computer Science, Brno University of Technology, 2019-06-24) Bidlo, Michal; Korgo, Jakub
A method is presented for the design of cellular automata rules by means of ant algorithms. In particular, Elitist Ant System and a~modified MAX-MIN Ant System are applied to search for transition functions of 1D cellular automata that are able to calculate squares of given input values. It will be shown that the proposed MAX-MIN Ant System can perform significantly better than the standard variant of Elitist Ant System. In particular, in the most advanced case study, the ant algorithm showed an ability to design a~complete set of elementary cellular automata rules that fulfil the required square calculations. Some selected results will be presented and their features discussed.

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