Category: Research

Members of our EuroCC Montenegro team will be presenting the paper titled “Combined adaptive load balancing algorithm for parallel applications”, authored by L. Filipovic, B. Krstajic, and T. Popovic, at the upcoming IcETRAN 2021 conference. The conference will be taking place on Sep 8-10, 2021. More info on the conference is available at the following link.

ABSTRACT – Development and improvement of efficient techniques for parallel task scheduling on multiple cores processors is one of the key issues encountered in parallel and distributed computer systems. The purpose of process distribution improvement in parallel applications is in increased system performance, reduced application execution time, reduced losses and increased resource utilization.

This paper presents combined adaptive load balancing algorithm based on domain decomposition and master-slave
algorithms and its core scheduling adaptive mechanism that handles load redistribution according obtained and analyzed data. Selection of distribution algorithm, based on collected parameters and previously defined conditions, proved to deliver increased performances and reduced imbalance. Results of simulations confirm better performance of proposed algorithms compared to the standard algorithms reviewed in this paper.

A paper titled “Pneumonia Detection Using Deep Learning Based on Convolutional Neural Network” authored by L. Racic, T. Popovic. S. Cakic, S. Sandi was presented at the 25th IEEE Conference on Information Technology. The paper is available in the IEEE Xplore repository at the following link.

ABSTRACT – Artificial intelligence has found its use in various fields during the course of its development, especially in recent years with the enormous increase in available data. Its main task is to assist making better, faster and more reliable decisions. Artificial intelligence and machine learning are increasingly finding their application in medicine. This is especially true for medical fields that utilize various types of biomedical images and where diagnostic procedures rely on collecting and processing a large number of digital images. The application of machine learning in processing of medical images helps with consistency and boosts accuracy in reporting. This paper describes the use of machine learning algorithms to process chest X-ray images in order to support the decision- making process in determining the correct diagnosis. Specifically, the research is focused on the use of deep learning algorithm based on convolutional neural network in order to build a processing model. This model has the task to help with a classification problem that is detecting whether a chest X-ray shows changes consistent with pneumonia or not, and classifying the X-ray images in two groups depending on the detection results.

A paper titled “Applying natural language processing to analyze customer satisfaction” authored by A. Alibasic and T. Popovic was presented at the 25th IEEE conference on Information Technology. More about the conference cab be found at the following link.

ABSTRACT – The aim of this paper is to analyze customer satisfaction by applying natural language processing (NLP). We have collected over 50,000 airline reviews from TripAdvisor data in the period from 2016 until 2019. This analysis demonstrates the capability of discovering the pain points of the customers by using data science techniques related to NLP. Our study shows that in today`s world, data-driven decisions must be taken quickly in order to maintain customer satisfaction and prevent customer churn. The paper is available at the following link.