Volume 14 - 2022
Functional reactive programming
This paper presents the basic concepts of functional and reactive programming. At the end of the paper, an application for a student survey is presented, which applies the concepts of functional and reactive programming. The application allows students to enter grades for subjects, professors and student service, students enter a grade from 1 to 5 for each question, after the grades are entered the table is updated in real-time showing how many students gave a certain grade, how many grades are there and average grade for the corresponding question.
The technologies used to create this application are Node.js and Express.js on the backend, MySQL database, Angular with the RxJS library on the frontend.
Self-supervised learning using a rotation pseudo task on specially designed deep neural architecture
Large amounts of labeled data are required to train deep neural networks to achieve good performance in the case of learning visual characteristics from images or videos in computer vision applications. To avoid the cost of collecting and labeling large datasets, a subset of unsupervised learning methods called self-supervised learning methods can be deployed. They manage to learn general visual characteristics of images and videos from unlabeled datasets. The paper implements a convolutional neural network that has the pseudo-task of recognizing which geometric transformation was applied to the image from the input, specifically - rotation. After training, using transfer learning techniques network was trained on a small subset of labeled data, for the task of image classification. On the STL10 dataset, an accuracy of 76% is achieved on the image classification downstream task.
Automated unmapped forest path navigation of mobile rover using neural networks
In this paper, a system for autonomous navigation of unmapped forest paths in a simulation, along with a new simulator for testing and training it is presented. For navigation, it uses a combination of path planning and deep neural networks trained with imitation learning.
The Use of Azure Synapse Analytics Serverless Pool Technology in Data Analytics
The development of information systems and technologies has enabled experts to intensively use remote computing resources according to the concept of cloud computing. Among other things, there is a development of cloud databases, as well as a transfer of data warehouses to the cloud. Microsoft's Azure is one of the leading cloud computing systems; it has support for many databases, and one of the platforms available on it is Azure Synapse Analytics.
This paper provides a brief critical overview of Azure Synapse Analytics, with an emphasis on its distributed data processing system, serverless SQL pool. This system allows data engineers, data architects, data analysts, business analysts and scientists to create virtual data warehouses, explore the big data available in the Azure Data Lakes, perform complex queries and create business reports.
Through this paper, we want to acquaint the reader with the basics of using the presented technologies. With this goal in mind, many examples have been developed, and the advantages and disadvantages of the presented technologies have been discussed.
Design and development of a public procurement information system
The subject of this paper is the design and development of a public procurement information system. A special attention is paid to the public procurement information system in the Republic of Serbia and to its possible improvements. The first part of the paper deals with the public procurement information system and its significance, while the second part deals with the modeling of the public procurement processes. As an original contribution to the paper, the two schematic representations are provided, which can help in the development of the information system - the scheme of electronic public procurement process and the scheme of necessary functions that e-procurement software should have in order for the information system to function successfully. The final result of this research is a critical presentation of a software solution that enables efficient public procurements.