Volume 10 - 2018

The Comparative Analysis of Model-Driven Service Orchestration Solutions


Contrary to the monolithic systems which are aware of their internal structure and component organisation, when considering orchestration in the service-oriented architecture (SOA), there is no knowledge of how services are implemented which makes it rather challenging to form the right foundation for their collaboration. One of the approaches for modelling orchestration in distributed systems is to introduce a middleware which would be responsible not only for gathering the services but also for composing them. Of course, the orchestration itself can be considered either static or dynamic, where the dynamic approach stands for the middleware's ability to change the patterns of composition at run-time based on the given context. The aim of this paper is to analyse model-driven solutions for service composition proposed so far and to set grounds for developing a meta-model that would enable modelling contextaware middleware solutions in SOA.

Keywords: сервисно-оријентисана архитектура, оркестрација сервиса, контекст-зависна оркестрација, моделом- управљан развој сервисних архитектура
Published on website: 19.12.2019

Planning a radio network


Planning a radio network is a very complex process involving planning capacity, coverage and frequency. Each of these planning processes requires first of all to look at the needs of the users. Such as the speed of voice transmission and data in wireless and mobile communications, the coverage of the scope of operation. All these processes and methods that are necessary for the planning of radio networks are described in detail in this work. All these processes and methods that are necessary for the planning of radio networks are described in detail in this work. In addition, the possibilities for using the WinProp program are described.

Keywords: Планирање радио мрежа, планирање капацитета, планирање покривености, планирање расподеле фреквенције, WинПроп.
Published on website: 16.7.2018



This paper presents the analysis of techniques for microscopic images in order to find a primary tumor based on the of bone metastases. Was done alg orithmic classification into three groups, kidney, lung and breast. In order to speed up the treatment of the patient and easier for doctors and therefore reduce room for human error. Digital microscope images of bone metastases were analyzed, for which it is known that the primary tumor is in one of the three human organs: kidney, lung or breast. We tested several solutions for classification, were tested two methods of image analysis. Multifractal analysis and convolutional neural network. Both methods were tested with and without preprocessing image. Results of multifractal analysis were then classified using different algorithms. Images were processed using CLAHE and k-means algorithm. At the end, the results obtained using a variety of techniques are presented.

Keywords: Класификација канцера, микроскопске слике, препроцесирање слика, мултифрактална анализа, алгоритми класификације
Published on website: 22.4.2018



Artificial Neural Networks enables solving many problems in which classical computing is not up to task. Neural Networks and Deep Learning currently provide the best solutions to problems in image recognition, speech recognition and natural language processing. In this paper a Neural Network, more specific - Convolutional Neural Network solution for the purpose of recognizing and classifying road traffic signs is proposed. Such solution could be used in autonomous vehicle production, and also similar solutions could easily be implemented in any other application that requires image object recognition.

Keywords: Неуралне мреже, конволуционе неуралне мреже, класификација, саобраћајни знакови.
Published on website: 16.7.2018