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Book: ICIST 2020 Proceedings

About the book

Subtitle	Proceedings of the 10th International Conference on Information Society and Technology
Book edition	ISOS Conference Proceedings Series
ISBN	978-86-85525-24-7
ISSN (Online)	2738-1447
Publisher	Information Society of Serbia - ISOS
Publisher location	Belgrade, Serbia
Copyright holder	Information Society of Serbia - ISOS
Published	2020
Conference	ICIST 2020 - 10th International Conference on Information Society and Technology
Copyright year	2020

Full book not yet accessible

Book editors

Zdravković, Milan

Faculty of Mechanical Engineering, University of Niš

Konjović, Zora

Singidunum University

Faculty of Technical Sciences, University of Novi Sad

Trajanović, Miroslav

Faculty of Mechanical Engineering, University of Niš

Basic Metrics

Number of book views	2083
Number of book downloads	0
Number of papers in the book	56
Number of countries	13
Number of cities	21
Number of institutions	44
Number of book shares	Facebook: 460 Twitter: 469 Google Plus: 479 Linkedin: 459

Countries

Serbia (119), Republic of Macedonia (8), Slovenia (8), Brasil (5), USA (5), Ireland (4), Portugal (4), Austria (2), France (1), Germany (1), India (1), Italy (1), RS (1)

Cities

Belgrade (38), Novi Sad (38), Niš (34), Ljubljana (8), Kragujevac (7), Skopje (7), Curitiba (5), Dublin (4), Caparica (4), Blacksburg (4), Vienna (2), Ispra (1), Kattankulathur (1), Kosovska Mitrovica (1), (1), Millbrae (1), Prokuplje (1), Siegen (1), Bitola (1), Troyes (1), Zrenjanin (1)

Institutions

Faculty of Technical Sciences, University of Novi Sad (31)
Faculty of Mechanical Engineering, University of Niš (15)
Faculty of Electrical Engineering, University of Niš (14)
University of Belgrade, Institute Mihailo Pupin (11)
Faculty of Electrical Engineering, University of Ljubljana, Slovenia (7)
School of Electrical Engineering, University of Belgrade (6)
Pontifical Catholic University of Parana – PUCPR / PPGEPS (5)
Faculty of Information Technology, Metropolitan University (5)
Faculty of Engineering, University of Kragujevac (5)
IRITEL a.d. (5)
Mind Music Machine Lab, Department of Industrial and Systems Engineering, Virginia Tech (4)
Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University in Skopje (4)
Comtrade Digital Services (4)
CTS, Uninova, Dep. de Eng. Electrotécnica, Faculdade de Ciências e Tecnologia, FCT , Universidade Nova de Lisboa (4)
University of Defence, Belgrade (3)
Faculty of Electrical Engineering and Information Technologies, Ss Cyril and Methodius University in Skopje (3)
University of Novi Sad, Faculty of Sciences, Department of Mathematics and Informatics (3)
Institute of Information Technologies Kragujevac, University of Kragujevac (2)
Faculty of Civil Engineering and Architecture, University of Niš (2)
Faculty of Technical Sciences, Computing and Control Department, University of Novi Sad (2)
Singidunum University (2)
TU Wien, Vienna University of Technology (2)
Telekom Srbija AD (1)
University St.Kliment Ohridski/Informatics and Computer Sciences Department (1)
University of Novi Sad, Technical Faculty “Mihajlo Pupin” (1)
University of Priština, Faculty of Technical Sciences in Kosovska Mitrovica (1)
Université de Technologie de Troyes (1)
Zucchabar, Inc (1)
Pharmacy „Oaza zdravlja“ (1)
Neven Farma (1)
NIS a.d. (1)
MOBI GAS d.o.o. (1)
General Staff of the Serbian Armed Forces, GARDA (1)
Faculty of Science and Mathematics, University of Niš (1)
Faculty of Organizational Sciences, University of Belgrade (1)
Faculty of Computer and Information Science, University of Ljubljana (1)
European Commission, DG Joint Research Centre, Ispra (1)
Department of Telecommunications and Information Science, University of Defence, Military Academy (1)
Department of Pharmacy, University of Niš (1)
Department of ECE, SRM Institute of Science and Technology, Kattankulathur (1)
Credit Agricole Bank, Novi Sad (1)
Centre for Applied Mathematics and Electronics, Serbian Armed Forces (1)
Academy South Serbia/Computer Science (1)
Universität Siegen (1)

ICIST 2020 Proceedings - Paper index

ICIST 2020 Proceedings Part I

1. Case study: univariate time series analysis and forecasting of pharmaceutical products’ sales data at small scale

Pages 1-4

Zdravković Milan, Đorđević Jasmina, Catić-Đorđević Aleksandra, Pavlović Sonja, Ivković Miodrag

Abstract: The objective of the research behind the paper was to validate different methods and approaches related to sales time series data preparation, analysis and forecasting, with aim to facilitate recommending sales and marketing strategies based on trend/seasonality effects and forecasting sales of eight different groups of pharmaceutical products with diverse characteristics, such as stationarity, seasonality, amount of residuals and sales data variance. All these analyses and forecasts are made on a small scale, for a single distributor, pharmacy chain or even individual pharmacy. Paper presents only research work related to univariate time series analysis, while potential candidates for explanatory input variables were also identified and shortly elaborated. Effectiveness of three forecasting methods, namely ARIMA, Facebook’s Prophet and Long-Short Term Memory (LSTM) neural networks was investigated. Each of the method is complemented with two optimization and validation approaches, relevant for short-term (so called rolling forecast scenario) and long-term forecasting.

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2. Novel Educational Methodology for Personalized Massive Open Online Courses

Pages 5-9

Vitković Nikola, Mišić Dragan, Simonović Miloš, Banić Milan, Miltenović Aleksandar, Mitić Jelena, Milovanović Jelena

Abstract: In today’s higher education, various learning concepts are applied, and in general, two approaches exist in designing web-based education systems with Massive Open Online Courses (MOOC): adaptive education systems and intelligent tutoring systems. For their success, it is important to actively include student(s) and to properly analyze theirs answers. These approaches enable creation of general topic courses, with content described by using only one teaching style or methodology, and main shortcomings are: missing or inadequate feedback from the students, system adaptation not focused on learning context, and course presentation and learning material limited to one teaching style. The main idea of this research is to develop Novel Educational Methodology (NEM), which will combine traditional and eLearning concepts into one new eLearning platform tailored to the needs or requirements of the student, student group, and teacher, thus, enabling creation and implementation of personalized MOOC(s), applicable in education, research and industry.

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3. Automation of FEM Analysis Report Generation using Visual Basic FEMAP API

Pages 10-15

Vulović Snežana, Bojović Milan, Topalović Marko

Abstract: Finite Element Method (FEM) is the most popular numerical method used for a wide range of problems, from the aerospace industry to biomechanical engineering and many more diverse applications in between. In this paper, we will not focus on the method itself, nor its applications, but we will address one tedious commonality that all engineers face, no matter what kind of analysis they perform, and that is writing a report. In the most cases, the contract requires a detailed Word document featuring description of all load cases, filled with the images of Finite Element mesh, colored by the equivalent stress or strain, which must emphasize the most critical areas of the structure. There are many commercial FEM softwares, and every one of them has a special pre and post-processing modules, which all in some way or another have certain limitations. FEMAP is a program developed by Siemens PLM, and it is specifically designed for FEM pre and post-processing. FEMAP can generate input files for all relevant commercial FEM programs, and read results from their output files. One of the most powerful features of FEMAP is its customization using an Application Programming Interface (API). In this paper, we will show how to use this API for connecting FEMAP with MS Word, and generating images for the analysis report. The key sections of the developed Visual Basic script are explained, as well as the most important methods and properties of FEMAP Application Object, which are used to access the analysis model. Although presented method does not influence the numerical procedure, or construction changes made by engineers, it significantly speeds up design iterations during development of a new product, because for every new proposed version, a full set of FEM analysis must be performed, and reports for them created.

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4. Methods for Drone Detection and Jamming

Pages 16-21

Matić Vladimir, Kosjer Vladimir, Lebl Aleksandar, Pavić Branislav, Radivojević Jovan

Abstract: This paper presents methods for drones’ detection and for jamming. Implementation of drones in malicious activities highly increases in the last years and the methods implemented for drone detection are numerous. The characteristics of the most detector types: radar, radiofrequency, acoustic, optical and thermal are emphasized in the paper. The goal of this analysis is to give the guidelines in choosing which techniques to use and combine for drone detection. The paper emphasizes the guidelines for drone successful jamming while presenting IRITEL solutions implementation for drones malicious function prevention and drones role in jamming efficiency improvement.

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5. Edge Computing for Fault Detection in Smart Systems

Pages 22-26

Stankovski Stevan, Ostojić Gordana, Nićin Miroslav, Baranovski Igor, Tarjan Laslo

Abstract: Increasing the performance of all computing components enables the development of new architectures and platforms for data processing, sharing, distribution and storage of data. Speed, security and reliability of data transmission are essential parameters in industrial automation and therefore only those architectures/concepts that successfully meet these parameters have a chance to succeed in an industrial environment. The general need for data sharing has made that the amount of data, which are generated and recorded significantly, are increased and therefore new approaches are needed to address to these facts, especially in industrial automation. One approach in industrial automation is using Edge computing. Edge computing brings new power in data processing in industrial automation and opportunities in data processing of big data in real-time. This characteristic is essential for the prediction of fault detections and represents one of the landmarks of smart systems. In this paper are described basics of Edge computing and its possibility for fault detection in smart manufacturing systems.

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6. Assessment of Human Neuromuscular System State Using Standard Human-Computer Interaction

Pages 27-31

Mišić Dragan, Trajanović Miroslav, Korunović Nikola, Vitković Nikola

Abstract: The paper describes an application for assessing the state of human neuromuscular system based on the data obtained from standard human-computer interaction. The application features several tests, which the users perform online. Test results are recorded in the database, which enables data analysis, based on which the human condition is evaluated. Based on these results, it can be assessed whether the recovery is going in the right direction or whether a therapy is appropriate. Monitoring the neuromuscular system state in this way can results in timesaving for both the doctor and the patient, as it can reduce the number of patient check-ups. At the same time, in the case of unfavourable results, a timely response from physicians could be provided, which without this system would be delayed until the next check-up.

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7. Use of spatial sound notifications for takeover requests in semi-autonomous vehicles - a cross-cultural study

Pages 32-35

Stojmenova Kristina, Sanghavi Harsh, Nadri Chihab, Ko Sangjin, Tomažič Sašo, Sodnik Jaka, Jeon Myounghoon

Abstract: To investigate the full potential of non-speech sounds, this study explored the use of spatial sound displays for takeover requests in semi-automated vehicles. The study was conducted in a motion-based driving simulator with 72 participants in two locations – Slovenia and Virginia. All participants were engaged in four 9-minute driving tasks in level-3 automated vehicle. Each driving session contained three hazardous events with takeover request (in total 12 requests per user). The results showed shorter reaction times to the directional sound displays compared to the non-directional sound display. Regardless of the sound display, the participants in Slovenia had statistically significantly shorter reaction times compared to participants in Virginia. While in Slovenia in 77% of the trials the participants’ first reaction was braking and 23 steering, all of the Virginia participants’ first reaction was braking.

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8. Usability Factors in e-Learning Acceptance Models

Pages 36-41

Dimitrijevic Sonja, Devedžić Vladan

Abstract: Usability is an important factor that influences learners’ and teachers’ attitudes towards the use of an e-learning system. The objective of this paper is to summarize and critically evaluate how usability has been addressed in e-learning acceptance models based on Technology Acceptance Model (TAM). A relatively recent systematic literature review has served as a starting point for the selection of papers. In addition, more-recent papers have been searched and selected. The results of the review have shown tendencies in tackling usability in the given context. Among different usability-related constructs that have been introduced, the most prominent ones are user satisfaction, perceived user interface design and perceived interactivity. The statistically significant influence of usability factors in the reviewed models has been confirmed in most of the studies. Future research may benefit from including neglected objective usability measures. Collecting these measures in innovative, less demanding ways should be considered. Moreover, including subjective measures based on standardized usability questionnaires may be quite beneficial considering their multidimensionality, validity and reliability.

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9. FPGA Design of IP Packet Filter based on SNORT rules

Pages 42-45

Efnusheva Danijela, Cholakoska Ana, Kalendar Marija

Abstract: Contemporary technology advances increase the pace of rapid expansion of the number of computers and devices connected to the Internet on а daily basis. Therefore, one of the highest priority issues that need to be considered in this enormous network is the network security. The greater the number of connected users and devices, the attempts to invade privacy and data of connected users becomes more and more tempting to hostile users. Thus, Network Intrusion Detection Systems (NIDS) become more and more necessary in any network device connected to the Internet, and are taking the lead in the battle against intruders. This paper addresses the network security issues by implementing NIDS style hardware implementation network packet filter intended to provide fast packet processing and filtering. The hardware is based on several NIDS rules that can be programmed in the system's memory, thus enabling modularity and flexibility. The designed hardware unit is described in VHDL and implemented in a Virtex7 VC709 FPGA board. The simulation timing diagrams and FPGA synthesis (implementation) reports are discussed and analyzed in this paper.

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10. CRDTs as replication strategy in large-scale edge distributed system: An overview

Pages 46-50

Simić Miloš, Stojkov Milan, Sladić Goran, Milosavljević Branko

Abstract: Replication is one of the most important parts of any distributed system. It is mainly used to provide fault-tolerant and robust systems. Data is copied on a few different machines, and often in several regions to ensure that loss of a single machine, cluster or even region does not affect the overall quality of the service given to users. Over several decades both academia and the industry developed few techniques on how to manage these tasks. These techniques usually involve some sort of expensive synchronization or consensus to ensure replication is done properly. Conflict free replicated data types or CRDTs, do not use consensus, but a set of strong mathematical rules and they are guaranteed to converge eventually if all concurrent updates are commutative. Expensive synchronization or consensus might be a problem with resource-limited devices. In this paper, we present a review of CRDTs, it’s benefits and shortcomings in the domain of the large scale edge computing systems with constant data flow with processing on the very edge of the network. We provide answers to questions is this technique applicable as a data replication strategy in systems with limited hardware capabilities, and could we retain or improve availability and reduce the latency of the system, but at the same time avoid expensive synchronization and consensus-based approach, which could be problematic due to the nature of edge computing.

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11. Traditional and Blockchain-based access control models in IoT: A review

Pages 51-55

Stojkov Milan, Simić Miloš, Sladić Goran, Milosavljević Branko

Abstract: Internet of Things gained popularity in recent years and the number of devices that are being interconnected is increased every day. These devices can exchange all kinds of information which is beneficial but also this introduces some concerns in terms of security and privacy. Conventional security approaches have shown as modestly applicable for IoT primarily due to the decentralized and lightweight nature of the devices. Access control is one of the concerns that have to be addressed. Traditional models are widespread in IoT systems as a starting point solution, but their shortcomings can be overcome with emerging technologies such as Blockchain that is a base for various cryptocurrencies that have recently gained popularity to provide security and privacy in peer-to-peer networks with similar topologies to IoT. In this paper, an analysis and comparison of different traditional and Blockchain-based solutions are conducted to see if and how IoT specific challenges can be tackled with these new technologies.

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12. Applying Blockchain Technology to Oil and Gas Industry

Pages 56-59

Marjanović Jelena, Dejanović Stefan, Smirnov Vadim, Miljković Petar, Lendak Imre

Abstract: Bitcoin, the first decentralized cryptocurrency, maybe getting less attention than earlier, but the technology behind it, blockchain, is searching for its place in various fields each day. Blockchain has been shown to work in finance, the Internet of Things, healthcare, and many more industries. The oil and gas industry still needs to tackle this technology. Our work shows how blockchain can be used in tracking gas levels on various gas stations.

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13. How to Establish a Project Management Education Process in a Software Company: from Defining a Roadmap to Effective Implementation

Pages 60-63

Janković Vera, Atanasijević Srdjan, Atanasijević Tatjana, Zahar Monika

Abstract: Comtrade PMO (Project Management Office) established an expert group for PMO Education, having a vision about improving company efficiency by extending a set of PM’s (Project Manager) skills, applying new processes and standards while embracing new learning habits of PM professionals. Education of project managers in the software industry should take into consideration not only market changes and demands but also employees’ needs as well as internally recognized areas for improvements. It must be flexible to provide proper aligning with frequent market changes while affecting corporate efficiency in a measurable manner. Due to changed learners, habits, different content, and communication channels must be established to provide equally important self-paced learning and productive collaboration. This paper shows the whole process flow from initial roadmap to implementation, state of PMO Education, problem-solving framework as well as actionable KPIs (Key Performance Indicator), which unambiguously show significant achievements in the excellence of Comtrade PM Experts.

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14. Extraction of Geometric Attributes Based on GAN for Anatomic Prosthesis Modeling

Pages 64-67

Schitz da Rocha Luiz Gustavo, Lefko Rudek João Victor, Rudek Marcelo

Abstract: This research addresses the anatomic prosthesis modeling problem based on contour reconstruction from Computed Tomography images. The new neural network techniques permit predicting the geometric attributes of bone failures that cannot be obtained by symmetry. This paper presents a method based on Generative Adversarial Network (GAN) applied to build anatomic 3D geometric models of a skull prosthesis. The method performs the calculation of geometric descriptors as parameters to fit a curve on each Computed Tomography slice. These features can be estimated by the network who will be trained with a database of descriptors. The curve descriptors are formed by the fixed points around the edge that better represent a geometry, and a curve section can be described using the Cubic Splines method in order to complete the missing information on an open edge. The curve that fits a missing region to each CT slice can be superimposed to define the stack of images to build a 3D virtual CAD model. A prototype software system was implemented in Python in order to calculate the edge parameters and generate the computational model to printing. The results evaluate the similarity measured between the estimated and real coordinates and demonstrate the feasibility of the proposed method.

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15. Multi-Agent Distributed Calibration of Large Sensor Networks

Pages 68-73

Stanković Maja, Antić Dragan

Abstract: This paper is devoted to the problem of distributed multi-agent blind macro calibration of large Wireless Sensor Networks (WSN). The paper starts with establishing strong connections between Cyber-Physical Systems (CPS) and WSN. General considerations of the problem of WSN calibration are provided. The central point of the paper is presentation of an original algorithm for multi-agent recursive blind macro calibration based on consensus, including an exact proof of convergence. Simulation results are presented as an illustration of the properties of the algorithm.

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16. Software Vulnerability Management System

Pages 74-78

Kovačević Marija, Sladić Goran, Luburić Nikola, Zarić Miroslav

Abstract: This paper presents an implementation of the Software Vulnerability Management System. The main goal of this system is to analyze data flow diagrams in order to discover potential security exploits. The security experts put great effort to discover vulnerabilities in different systems and to successfully prevent all possible attacks. They spend many working hours analyzing diagrams and targeting possible vulnerabilities because targeting them on time reduces the overall cost and time spent on the later phases of the software design. This system uses a knowledge base to find exploits on the different data flow diagrams and searches the National Vulnerability Database (NVD) to discover publicly known vulnerabilities that are associated with the diagram elements. This system brings a new type of element, that could be used on the diagram with the processes, external entities, and data stores. That element is called a complex process and it contains a new data flow diagram. This proposed system automates the analyzing process, simplifies threat modeling, and provides a readable report with the list of all found potential security exploits. It was designed as a website with a modest user interface that is easy to use, even by non-experts.

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17. Application of combinatorial methods in web application security testing

Pages 79-83

Preradov Katarina, Medić Mina, Sladić Goran, Milosavljević Branko

Abstract: Web applications are one of the most vulnerable systems nowadays. Everybody uses them in everyday life and most often they handle sensitive information from users, which makes them very tempting to malicious users for crashing them or steal their data. Testing web applications against various cybersecurity attacks can lower the risk of malicious user to perform some action that can harm the system itself or its users. Adequate test data can reveal these vulnerabilities, but traditional testing methods can not determine which test sets are appropriate. It is not uncommon that testing comes down to brute force testing. Also, these techniques do not take care of the correlation between different parameters which, under certain conditions, affect the reliability of the system. In this paper, we apply the idea of a combinatorial testing technique to generate adequate test data sets for testing web applications against known cybersecurity vulnerabilities. We used ACTS for automatic test set generation. The results show that these test sets are effective and can reveal security issues. Also, the number of necessary test cases is reduced, which directly affects the time and money needed to adequately test the software. Keywords software testing, combinatorial testing, web security.

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18. Multi-Agent based HEMS framework

Pages 84-88

Aleksić Aleksandra, Vidaković Milan, Slivka Jelena, Milosavljević Branko, Kaplar Aleksandar

Abstract: Nowadays, smart homes have the goal of providing an easier and more comfortable lifestyle. For that purpose, smart homes contain a vast number of electronic appliances and consume electricity from the electricity grid or renewable energy sources such as solar panels. Smart scheduling of these electrical appliances to lower the consumed energy while keeping the residents satisfied is a complex problem. One solution would be the implementation of an intelligent Home Energy Management System (HEMS) that automatically determines the best schedule. The focus of this paper is the implementation of a framework that could facilitate the training of a smart HEMS, using Siebog a Multi-Agent based system. To ensure resident satisfaction, we propose a system that enables residents to define their priorities in a narrative form, e.g. “The dishes should be washed till 7 AM”. Additionally, to provide smart and optimal energy consumption, as a part of the proposed system, we have implemented a cost function metric for machine-learning-based optimization that combines the two goals of resident satisfaction and lowering electricity consumption.

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19. Energy user benchmarking using clustering approach

Pages 89-93

Pujić Dea, Jelić Marko, Batić Marko, Tomašević Nikola

Abstract: Achieving energy efficiency is crucial in order to improve environment and life quality. Therefore, within the residential sector, research efforts on advanced approaches to steer end users to save the energy and adapt their consumption are widely spread. One of recent approaches being used is creating a competitive environment which would stimulate the users to improve their habits. The main idea of this paper is proposing a data-driven machine learning clustering approach for ranking users depending on their consumption measurements and other relevant data collected from a real-world pilot in France. Within this paper, exploited data, implementation details and results will be presented.

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20. Comparison between different ML approaches for PV and STC production forecasting using real world data

Pages 94-98

Pujić Dea, Jelić Marko, Tomašević Nikola

Abstract: With the aim of improving ecological interest, the share of renewable energy sources (RES) in the energy production is to be increased. Nonetheless, that growth adversely influences the grid’s instability, as a result of the dependency between the RES production and weather conditions. Therefore, with the aim of providing a stable energy system, it is necessary to plan the consumption in advance with respect to the availability of RES production. This paper is focused on comparing current SoA approaches for two different renewable energy sources, photovoltaic panels and solar thermal collector, using real world data from Denmark and Spain.

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21. Correlation between IoT sensor measurements and total electricity consumption in smart homes

Pages 99-103

Jelić Marko, Pujić Dea, Batić Marko

Abstract: With the IoT industry rapidly growing and evolving, smart home concepts powered by distributed IoT sensors are becoming more and more popular amongst residential users. This transformation has created an opportunity for novel energy management solutions with the main goal of improving energy efficiency. A key element in this process is being able to predict energy consumption with this paper aiming to extend the current state of the art by analyzing real measurements obtained from smart sensors through their distribution, statistical characteristics and suitability as predictors in a forecasting algorithm.

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22. OPTIMIZATION OF HEALTH SERVICE SCHEDULE

Pages 104-108

Đorđević Anđelija, Milenković Aleksandar, Janković Dragan, Stamenković Lazar

Abstract: It is a frequent case of cancellation or absence of patients on scheduled medical care. This behavior results in additional costs and unnecessarily long waiting times for patients arriving on scheduled appointments. This paper attempts to minimize the consequences of the problem by predicting patients' cancellations and absences by applying logistic regression, enabling employees at healthcare institutions to optimize their existing schedules and reduce the number of empty appointments. Prediction is made using a model that is trained on actual data collected in several health institutions in Serbia from 2010 to 2019.

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23. Distortion Optimized Spherical Cube Mapping for Discrete Global Grid Systems

Pages 109-113

Dimitrijević Aleksandar, Strobl Peter, Lambers Martin, Milosavljević Aleksandar, Rančić Dejan

Abstract: The amount of geospatial data generated globally, together with the necessity for increased interoperability of these data, call for innovative solutions for global geospatial reference frames. Discrete Global Grid Systems are a class of spatial reference systems that use hierarchical tessellation of cells to partition and address the globe without gaps or overlaps. The specific properties of DGGS make them important candidates for future standard geospatial reference frames and fuel further efforts to investigate their potential for organization, exchange and processing such data. In this paper, we focus on DGGSs based on the so-called spherical cube mapping technique and present some first results of how these can be optimized to serve as global reference frames for large volumes of gridded geospatial data.

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24. Cloud platform for biomechanical applications in sport and rehabilitation

Pages 114-118

Hribernik Matevž, Tomažič Sašo, Umek Anton, Kos Anton

Abstract: Sport and rehabilitation are two very important research areas where biomechanical systems and applications are used. The use of sensors and smart equipment enables the measurement of motion parameters that were previously unknown or not available. Sensors can produce large amounts of data that need to be stored for later processing and analysis. It is also important that the cloud platform architecture is structured yet flexible enough to allow different types of experiments and applications to use a single cloud platform to some extent. This paper presents a universal solution that addresses these issues. We present the architecture for the proposed cloud platform that can accommodate all types of sensors, support different applications and measurements, track users through different tests, and produce standardized output types and reports.

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25. Ontology Enabled Internet of Things System for Smart Buildings

Pages 119-122

Popadić Dušan, Berbakov Lazar, Jelić Marko, Batić Marko

Abstract: Irrational energy consumption and waste of energy are two of the main problems that we face today. A lot of the energy is wasted by people in their homes or offices because they are not paying much attention to their energy consumption. In order to increase energy efficiency of the general population and to raise general awareness, a system based on Internet of Things (IoT) is developed to influence users to be more energy efficient. Because of the great number of different entities in the buildings and their complex relationships, a semantic ontology is used to store contextual knowledge about spatial arrangements of the rooms, devices and sensors in the buildings.

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26. A Meta-Model and Code Generator for Evolving Software Product Lines

Pages 123-128

Lalošević Tijana, Vuković Željko, Milosavljević Gordana

Abstract: Software Product Line (SPL) engineering is a paradigm which allows reducing development time, effort, and costs for development of products with the same core features and some variations needed for every client that purchases the product. Instead of writing the variations code from scratch, we can follow the Model-Driven development approach, which aims to generate software from design models automatically. Incorporating Model-Driven Software development in an existing large scale software product line (SPL) can be challenging and full of obstacles due to constant development and changes in the SPL core and product architecture. The introduction of the Model-Driven approach to such solutions often must be done in an iterative and incremental manner to embrace the changes. In order to achieve this goal, it is necessary to fulfill two preconditions: the existence of the domain-specific modeling language and transformation programs for automatic code generation from a model. This paper presents a meta-model and a code generator that enables rapid development and customization of the SPL applications. Our solution enables the core product line to be automatically expanded in any segment (e.g. method, data structure, etc.).

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27. SORA vs. Euler angles: Computational Efficiency in the Context of Gyroscope Measurements

Pages 129-132

Stančin Sara, Tomažič Sašo

Abstract: We investigate the computational complexity of tracking 3D orientation (3DO) using gyroscope angular velocity measurements around its three sensitivity axes. These three rotations, obtained at every measurement step, are simultaneous and, due to rotation non-commutativity, interpreting them as sequential, i.e., Euler rotations, yields a systematic error in the estimated 3DO. As this error grows with the angle of rotation, an efficient approach for its reduction is to shorten the measurement interval, demanding a larger number of measurement and hence computational steps. We show that from the computational complexity point of view, for similar levels of result accuracy, the simultaneous interpretation of gyroscope measurements is superior to the sequential. Experimental results obtained using a dedicated microcontroller and relying on a specially developed, computationally optimized implementation, show that for the largest rotation angle considered, i.e., 3.67°, execution time for the simultaneous interpretation is 12 times shorter than for the sequential. Aiming to achieve computational efficiency and relevant comparison of both interpretations, rotation matrices were used when calculating 3DO after each measurement step and the rotation quaternions were used when combining multiple consecutive measurements in a single rotation composite.

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28. Self-Adaptive Agent for Reliable RESTful Messaging

Pages 133-136

Baylov Krasimir

Abstract: Service Oriented Architecture (SOA) is the most popular and widely adopted architectural style for implementing and integrating large-scale heterogeneous systems. While it has a lot of forms, microservices were established as the preferred way of building distributed SOA applications. Such architectures tend to have a lot of asynchronous REST communication. Their distributed nature, however, often results in complex design decisions that address the issue of reliable messaging. In this work, we present a self-adaptive agent that guarantees reliable RESTful messaging. The agent can be integrated into existing services, thus reduce the overall complexity of the entire infrastructure.

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29. A performance study of the UWB positioning system for the player tracking in tennis

Pages 137-140

Umek Anton, Kos Anton

Abstract: Precise tracking of the tennis player’s location gives important information for the tennis game analysis. We designed a prototype system that uses an ultra-wideband (UWB) positioning technology for players tracking on the tennis court and wireless inertial sensors for detecting the ball impacts. We verified the accuracy of the UWB positioning technology in the tennis court by the high-precision optical tracking system. The results of the field tests confirmed that UWB technology is useful for player tracking in tennis coaching applications.

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30. Sensor system for agility assessment: T-test case study

Pages 141-145

Keš Erik, Hribernik Matevž, Umek Anton, Kos Anton

Abstract: Measurement of the relevant basic and sport specific physical abilities of athletes is one of the most important elements in the system of sport. Agility, i.e. the ability to rapidly change direction is one of these abilities and various agility tests are regularly included in sport test batteries. This paper presents a state-of-the-art approach to measuring agility using infrared and kinematic sensors. The combination of precise timing, position detection and motion recording enables the acquisition of previously inaccessible kinematic and temporal variables. The evaluation of the athletes' agility can be more objective and acquired with much greater certainty than it would be possible with current equipment and methods. The presented sensor system can be used in different sport settings and types of tests, including the frequently used T-test, which serves as our case study. Keywordsagility, photocell, IMU, sensor system, synchronization, sensor fusion, T-test

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31. A mechanism for mitigation of branch prediction calculation latency

Pages 146-149

Radenković Uroš, Mićović Marko, Radivojević Zaharije

Abstract: Branch predictors are one of the most significant components in the contemporary pipelined processors. They are used to predict which instruction should be executed right after a branch instruction. Prediction itself must be made before completion of the branch instruction. This requirement makes an accuracy the main characteristic of a branch predictor. Accuracy of a branch predictor naturally must be very high to avoid wasted processor cycles while executing instructions which are not part of the correct execution path. Additionally, in case of a misprediction processor must engage recovery procedure in order to return back to the correct execution path which reduces performance of the processor. Branch predictors use various algorithms and structures to calculate a prediction consuming certain time in the process. This time is called a branch predictor latency. There are two types of branch predictor latency. First type is time needed for prediction calculation itself and second type is time needed to update internal state of branch predictors. This paper focuses on time needed for prediction calculation and ways this type of branch predictor latency could be mitigated. There is a proposition of a mechanism that initiates prediction calculation in advance i.e. before branch instruction has even been fetched for execution by the processor. Proposed mechanism consists of two different branch predictors and internal structures for information buffering. First branch predictor is slow in terms of time needed for prediction calculation and has very high accuracy whilst second branch predictor is fast but less accurate. Depending on the execution traces used for testing proposed mechanism achieves accuracy from 76 to 99 percent. Index terms: branch predictor, prediction calculation latency, pipelined processor

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32. Big Data Architecture for Cryptocurrency Real-time Data Processing

Pages 150-155

Horvat Nebojsa, Ivković Vladimir, Todorović Nikola, Ivančević Vladimir, Gajić Dušan, Luković Ivan

Abstract: The role of cryptocurrencies in the alternative world economy has been steadily increasing since they emerged in 2009. However, understanding their actual influence and performance can be a difficult task. In this paper, we present an architecture for real-time cryptocurrency data processing and analysis based on the Lambda architectural approach. The proposed architecture offers both batch and stream data processing of cryptocurrency transactions and blocks, as well as analyzing various sorts of trends in a blockchain network and an exchange market. The proposed architecture is modular and thus easies the implementation of loosely coupled components and also provides several benefits for cryptocurrency analysis: real-time monitoring of blockchain events and mining statistics, cryptocurrency buying and selling trends, as well as social media events related to cryptocurrency reputation.

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33. Secure Horizontal Integration in Industry 4.0: Automatically Generated Smart Contracts Deployed on a Private Blockchain Network

Pages 156-160

Todorović Nikola, Todorović Nenad, Ivković Vladimir, Dimitrieski Vladimir, Luković Ivan

Abstract: In recent years, Industry 4.0 has promoted enhanced integration of value chain participants and their production processes, aiming to improve their efficiency and effectiveness. In this paper, we address transparency and data privacy issues that occur with the introduction of a high level horizontal integration. We propose a use of private, permissioned Distributed Ledger Technology (DLT) systems for overcoming these issues and facilitating the integration of business processes with end-to-end engineering spanning across the entire value chain. We also present a tool for the automatic generation of smart contracts based on the production process specification. Generated smart contracts are used for transparent, secure and scalable monitoring of the production process executions.

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34. Conceptual Method of a systems to support the process dental implant

Pages 161-164

Tinfer Sabrina, Canciglieri Jr. Osiris, Szejka Anderson Luis, Rudek Marcelo

Abstract: In recent years there has been a technological evolution that has provided the integration between different areas of knowledge, an example of this is the integration between Dentistry and Engineering in order to find new solutions to improve the surgical process of dental implants. This work proposes a conceptual method of reasoning to determine the type of dental implant based on the tomographic image where it will support the surgeon in determining the best dental implant options, depending on the characteristics of each patient. This system will analyse tomographic images through the bone structure, density and the load that implant will support, identifying the most appropriate models for the patient. The system creates a three-dimensional model of the dental arch and interacts with the dentist, leaving him free to choose among the selected ones the most appropriate implant. This system is a planning tool that assists the dentist during the preoperative period and in his / her decision making. Main contributions of the article are: i) design and development of a computational reasoning tool that supports the dental implant process; ii) interactivity in the development of surgical planning.

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35. Geolocation Solver of IoT Devices for Active and Assisted Living

Pages 165-169

Rodrigues Rafael, Calado Jorge, Sarraipa Joao, Jardim-Goncalves Ricardo

Abstract: Latest enhancements in IoT devices and in communication technologies, has brought new ideas that are capable of providing advanced sensing of the surrounding environment. On the other hand, average life expectancy has grown, resulting in a considerable increase in the number of elderly people. Consequently, there is a constant search for new solutions, to support an Active and Assisted Living (AAL) of these people. This paper aims to propose a solution to help in knowing the location of IoT devices that could be helping these people. The proposed solution takes into consideration the risk factors of the target persons, at any given time and as well as the technical constraints of the device, such as available power and communications. Thus, a proﬁle-based decision is taken autonomously either by the device or its integrated system to ensure the use of the best geolocation technology in each situation.

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36. Time-series entropy data clustering for effective anomaly detection

Pages 170-175

Timčenko Valentina, Gajin Slavko

Abstract: In this paper, the focus of the research is on the comprehensive flow-based anomaly detection architecture which is based on the joint use of the entropy calculation and machine learning algorithms, and its enhancement with time-series techniques. The proposed solution is evaluated with the modified CTU-13 dataset, which includes instances of normal, background and botnet traffic. The analysis encompasses a range of unsupervised machine learning algorithms, time-series and entropy threshold analysis with different configuration parameters.

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37. Assuring immutability of public e-government documents using blockchain infrastructure

Pages 176-180

Davidović Nikola, Veljković Nataša, Stoimenov Leonid

Abstract: After a decade from its advent in 2008, the blockchain technology has dived deeply into mainstream research. The success of Bitcoin, used for storing transactions in blocks and thus maintaining a distributed ledger of who owns how many units of cryptocurrency, created high expectations for the possible usage of blockchain technology in the industry and the public sector. In order to step out from its limited use for finance sector and digital money, a new type of blockchains are emerging. The so-called smart contracts cast a light on possible usages of this technology in e-government, with the purpose to bring more transparency in e-government processes. Using the available features and data structures of the Smart contract it is possible to develop a solution for checking validity and assuring immutability of public documents.

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38. Big streaming data visualization and visual analytics

Pages 181-186

Stojnev Ilić Aleksandra, Stojanović Dragan

Abstract: Big streaming data visualization has an important role in data exploration and mining, information retrieval and data analysis as it assists humans in analyzing and comprehending large volumes of streaming data. Systems for big stream data visualization must be able to handle massive amounts of data in a timely manner and provide an interactive and comprehensive graphical presentation. This paper describes a unified architecture for big streaming data visualization and lists the most popular libraries and platforms for its implementation. The described architecture supports all of the key characteristics of big streaming data: their volume, velocity, veracity and variety. Furthermore, we create a set of applications to demonstrate the viability of the described architecture, and to test some of the listed technologies.

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39. A new IoT solution for control of the entry and routing the vehicle

Pages 187-192

Bogićević Dusan, Stoimenov Leonid, Tot Ivan, Prodanović Radomir, Vulić Ivan

Abstract: Vehicle tracking has become a common practice for commercial and traffic monitoring purposes. The problem of tracking the vehicle arises in the situation when there are more than one vehicle in the same place and the order of movement is important. Also, the problem is in places where there is a high frequency of vehicles such as parking spaces or public transport stations. The authors solve the problem through the application of different wireless technologies in monitoring the position of vehicles and their distance from the station, by automating the entry and referral of vehicles to the appropriate platform. This paper proposes an Internet of Things solution for controlling the entry and routing of a vehicle through reliability, security, and low cost. The authors applies a solution based on sensors, microcontrollers and wireless access control using radio communication, which is paired with infrared technology.

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40. Predicting Purchase Day in B2B: From Statistical Methods towards LSTM Neural Networks

Pages 193-197

Ćirić Milica, Predić Bratislav

Abstract: Predicting when will a customer buy some product is a valuable information for any vendor. This information can be used for direct advertisement to customer or production/procurement planning. In this paper we focused on predicting whether there will be a purchase in the following seven days for a specific customer-product pair using LSTM neural networks. Considering that the data used are purchase records from a medical supply company, this research pertains to a B2B purchase scenario which has different characteristic than B2C purchases. Due to the irregular nature of purchase data, some data transformation was necessary before training the LSTM networks. Trained networks were evaluated on multiple datasets differing on the lowest number of purchases per customer-product pair. Results were compared to purchase prediction results from an earlier research based on the same dataset, but using ARIMA, a statistical method. Compared to ARIMA, LSTM networks’ predictions have lower precision, but significantly higher recall. Additionally, both precision and recall consistently rise when the dataset has a higher number of purchases per customer-product pair.

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41. Intelligent Heat Demand prediction for Advanced District Heat Plant Control

Pages 198-201

Ćirić Ivan, Ignjatović Marko, Stojiljković Mirko, Stojiljković Dušan, Gocić Milan, Ćirić Milica

Abstract: In urban areas the most efficient, environment friendly and cost-effective method for supplying heat to buildings is by district heating systems (DHS). However, by optimizing the production of heating energy in DHS further improvement of the efficiency, operation cost reduction and raise of the profitability can be achieved. This goal cannot be met without a detailed analysis and adjustment of the heat supply according to the user demands. Accurate heat demand (especially peak load) is very hard to predict and Artificial Intelligence techniques like LSTM neural networks and DNN are most commonly used for development of Data Driven Models (DDM) for this prediction. In this paper various methods for heat load prediction applicable in District Heating System of Faculty of Mechanical Engineering in Nis (FMEDH) will be considered where Knowledge Based Models (KBM) and DDM for heat demand prediction will be analyzed while the goal that goes beyond State of the Art is development of Hybrid KBM/DDM model. Prediction models can further be used by the operators as a support for District Heat Plant Control as well as by the consumers as a decision making support for heat cost reduction if several heating sources are available (e.g. DHS, Solar energy, Heat pump, Air conditioning system etc.)

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42. Reconstruction of the missing part in the human mandible

Pages 202-205

Mitić Jelena, Vitković Nikola, Manić Miodrag, Trajanović Miroslav

Abstract: The reconstruction of the missing part of the human mandible is a significant challenge in orthodontics and surgery, especially when the shape of the missing part is not known prior to operation. Creation of geometrical model of specific patient is being become an expected treatment. The one of the greatest challenges within this procedure is related to efficient designing the geometry and anatomy of a particular human bone. In this paper, method of the reconstruction of missing part the human mandible is presented. The reconstruction was performed by using the parametric model based on Method of Anatomical Features (MAF). The 3D parametric model is defined as point cloud, where coordinates of points are described by parametric functions, whose components are morphometric parameters (dimensions which are read on medical images). The main benefit of this model is ability to adapt model to the specific patient, by applying patient specific values of morphometric parameters. The resulted model may be used for preoperative planning and for surgical simulation. The main idea of the research was to present patient-specific reconstruction method which will provide the surgeon more control over the treatment, decreases the risk of surgical errors and reduces the operating time.

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43. Model for authenticating the Internet of Military Things and Internet of Battlefield

Pages 206-210

Vulić Ivan, Prodanović Radomir, Tot Ivan, Bogićević Dusan

Abstract: The Internet of Military Things and the Internet of Battlefield Things (IoMT/IoBT) perform more different activities such as data collection, communication, data processing, command execution, data transmission. It is essential that subsequent activity is based on a decision made on the basis of authentic source data from a dynamic and unpredictable military environment. For that purpose, the authors proposed an authentication scheme based on PKI, digital signature and asymmetric cryptography. The proposed scheme does not require the establishment of an authentication channel for the authentication of the parties in the communication. Authentication is conducted on the IoMT/IoBT side after receiving the data. In addition to authentication, the schema provides data integrity and non-repudiation parties in transaction.

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44. Implementing Blockchain Technology for Data Protection in Health-IoT and Diagnostic Devices: Overview, Potential, and Issues

Pages 211-215

Zdravković Nemanja, Damnjanović Marina, Domazet Dragan, Ponnusamy Vijayakumar, Trajanović Miroslav

Abstract: In recent years, we have witnessed an increase in interconnected devices which collect and process data, and are used in a plethora of situations, giving rise to the Internet of Things (IoT). The measurements collected from these sensing devices - which in general may come from different manufacturers - must be aggregated, formatted, and processed together in order to provide integrated data management, and still presents a challenge to academia and industry alike. One of the critical applications of IoT is in healthcare management, where a strong motivation in government regulation should exist to secure protected health data transmission. A promising solution is integrating IoT with the still novel Blockchain technology, which is based on overcoming the lack of trust with its immutability and transparency properties. In this paper, we analyze state-of-the-art healthcarerelated Blockchain solutions with IoT (scientific papers, startup whitepapers, and readily available commercial solutions), identifying their similarities and differences, as well as possible bottlenecks. We hence provide an extended Blockchain/IoT healthcare model, based on multiple usecases which incorporates previously identified shortcomings, in order to build a basis for a trusted, reliable and secure Blockchain- and IoT-based healthcare system

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45. Usage of Blockchain Technology for Sensitive Data Protection - Medical records Use Case

Pages 216-221

Grković Veljko, Jović Jovana, Zdravković Nemanja, Trajanović Miroslav, Domazet Dragan, Ponnusamy Vijayakumar

Abstract: In recent years, we have witnessed the lack of control over our personal identities e.g. our birth dates, home addresses, and other personal data, that can be now easily accessed through search engines. Concerns also exist about more sensitive personal data, such as social security numbers, bank account information or health related data. One cannot be sure anymore which of one’s personal data is being shared through social networks or institutional systems, or even being modified without their knowledge. With all the different technologies that are in use, data often ends up being shared, modified or misplaced far more than one can realize. The aim of this work is to investigate how Blockchain technology can improve current, centralized data security solutions, with emphasis on medical records. In addition, we investigate how Blockchain can help keep data safe and in our control, following the regulations of various standards such as GDPR or, for medical records, HIPAA in the USA.

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ICIST 2020 Proceedings Part II

46. Parallel Differentially Private K-Means Implementation Using COMPSs Framework

Pages 222-225

Sukpisit Sukgamon, Škrbić Srđan, Jakovetić Dušan

Abstract: K-means is one of the most important clustering algorithms, but it does introduce a risk of privacy disclosure in the clustering process. One approach to solving this problem is by applying differential privacy to K-means clustering algorithm to effectively prevent privacy disclosure. Increasing amounts of information generated in big data processing scenarios make clustering a challenging task. In order to deal with the problem, various approaches to the parallelization of clustering algorithms have been attempted. This paper presents an implementation of a differentially private k-means clustering algorithm that uses -differential privacy, based on the COMPSs framework for parallel computing. The experimental results show that the proposed implementation scales well and can be used to efficiently process large datasets using high-performance computing equipment.

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47. Redesign of PAK’s interfaces to fit OSICE and CloudiFacturing requirements

Pages 226-229

Vulović Snežana, Dunić Vladimir, Živković Miroslav, Milovanović Vladimir, Živković Jelena

Abstract: Simulation-based optimization integrates optimization techniques into a simulation analysis. Because of the complexity of the simulation, the objective function becomes difficult and expensive for an evaluation. In our example, the simulation considers structural analysis using the finite element method (FEM), the estimation of the welds number, the costs associated with the welding process, and the simplicity of the assembly process. To overcome the computing complexity, we are using OSICE, a comprehensive, cost-effective, and easy-to-use HPC/Grid and Cloud-based optimization service for solving large-scale optimization problems using parallel evolutionary algorithms. For this particular Application Experiment, after the initial definition of technical requirements, PAK input/output interfaces were redesigned to fit OSICE and CloudiFacturing requirements.

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48. Combination of Bash and Python in Development of Wrappers used for Automation of Finite Element Analysis

Pages 230-235

Topalović Marko, Vulović Snežana, Živković Miroslav, Bojović Milan

Abstract: This paper presents developing wrapper scripts for automating Finite Element Method (FEM) analysis on GNU/Linux servers. The purpose of these scripts is to edit data in ASCII files that are inputs for FEM solver and to call FEM solver which performs the analysis. Input files consist of geometry model, material parameters, loads, constraints, time step definitions and other data. After the long-lasting calculations, based on the stress results, material parameters in input files are updated and the analysis is restarted. This loop is repeated until the analysis predicts structure failure and for each pass safety factor is calculated. These scripts are also used to extract certain element groups, combine file sections and adjust output file for post-processing. Although Bash is very versatile when it comes to text manipulation it was necessary to augment it with Python programing language in order to achieve required functionality, primarily for fitting material parameters needed for next calculation. Repetitive, tedious work that an engineer needs to perform is greatly reduced, utilization of server time is improved, and this solution can be used for further development, for example, an inclusion of optimization, on which will focus in the future work.

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49. Improvement of business intelligence system by application of R program package

Pages 236-239

Atanasijević Jordan, Atanasijević Nevena, Lazović Danilo

Abstract: The basic tenet of the paper is related to the improvement of the implementation of business intelligence systems, which are important for deciding on a particular problem, and in order to achieve the highest level decision-making benefits. The improvement must be appropriate to the development of the BI system under conditions where there is already prior knowledge of the problem. The results obtained should show that the business intelligence system, enhanced by the application of R software package, can improve decision support.

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50. Network Coding based on quasigroups

Pages 240-243

Mechkaroska Daniela, Popovska-Mitrovikj Aleksandra, Bakeva Verica, Dimitrova Vesna

Abstract: Network coding is a promising technique that improves network throughput and provides high reliability. In this paper we propose an application of quasigroups in network coding and give several advantages of proposed algorithm over linear network coding.

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51. My Baby - System proposal

Pages 244-249

Stojnev Ilić Aleksandra, Ilić Miloš, Spalević Petar, Hamid Abdullah Majid, Eferjani Seni Shanta Abubaker

Abstract: The problem that we tried to solve was creating a system designed for young parents to provide information and assistance during the raising a newborn. Overcoming the obstacles and responsibilities of parenting is especially difficult for first-born parents. The large number of different often-contradictory information received from the environment, as well as the lack of adequate answers to many questions, is a constant problem. The amount of information available on the web can put an additional burden on parents. Currently available applications, as well as web portals, provide a wealth of information in textual form, which leads parents to read loads of text that very often makes no meaningful point. The available applications and web portals do not offer any interactivity that would allow parents to have a retrospective of the meal, the examinations performed, nor the ability to monitor the development of the infant and get suggestions from the system based on a review of all available infant parameters. The system proposal includes applications for monitoring the development of a child from birth onwards. The benefits of such a system are the ability to input relevant data from parents. Based on these data, system can analyze and inform parents when it is time for a meal, how many meals a baby should have, to suggest introducing a certain type of food based on what has already been introduced, to monitor child development, completed and future vaccination as well as exercises for proper development.

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52. Comparison: Angular vs. React vs. Vue. Which framework is the best choice?

Pages 250-255

Cincović Jelica, Punt Marija

Abstract: JavaScript is now one of the most popular programming languages in the software development industry, and as it is growing, a lot of new JavaScript frameworks have entered the market. JavaScript frameworks enable easier and faster front-end development, but with a wide variety of frameworks available, developers can often find themselves in a dilemma choosing which framework is the best for them. This paper focuses on the three most prominent frameworks (Angular, React and Vue) and performs a detailed comparison based on specific applications that were made and a survey that was conducted. The parameters by which the comparison was made are: popularity, performance, community support, learning curve, migrations and flexibility. As a result of this comparison, a manual was created to help both beginners as well as experienced developers, to choose the right JavaScript framework, depending on their needs and abilities.

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53. An approach for processing data from NASDAQ stock exchange database

Pages 256-259

Radojičić Dragana, Kredatus Simeon

Abstract: This research is based on a data set that replicates the entire NASDAQ stock exchange, which is the second-largest stock market (measured by market capitalization of shares traded). Since there is a huge number of stock market events in each trading day which caused the update of the shape of the Limit Order Book, the data produced by the stock market is huge and demanding for processing. In order to do research with a huge data set, we propose a framework for data processing.

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54. Assessment of websites

Pages 260-265

Paroški Milan, Dragutinović Branislava

Abstract: In this paper, on the basis of the criteria from the Guidelines for Web site development, state administration bodies, territorial autonomy bodies and local self-government units, web sites were evaluated and recommendations for their improvement were given. A statistical analysis was made and further recommendations for the survey were outlined.

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55. Lexicographical Index Decision Variable in Pulse-Doppler Radar Pulse Burst Waveform Optimization

Pages 266-270

Jevtić Miloš, Zogović Nikola, Graovac Stevica

Abstract: In pulse-Doppler radar pulse burst waveform optimization problem, the combination of pulse repetition intervals can be substituted with the lexicographical index (LI), thus simplifying the decision space without losing any degree of freedom. This approach relies on an algorithm that generates a combination from its LI. We benchmark such an algorithm, ACM Algorithm 515 (A515), on a modern computer. We estimate that A515 would negligibly slow down the evolutionary algorithm previously used as a solver, thus making a strong case for the LI decision variable approach within the subject problem. INTRODUCTION

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56. Application of a Generalized Fuzzy Model in PKI Architecture Determination

Pages 271-276

Prodanović Radomir, Vulić Ivan, Bogićević Dusan

Abstract: It is difficult to decide what the best PKI architecture is to be applied due to unspecified determination parameters. The PKI architecture content and a comparative analysis of advantages and disadvantages are not sufficient for the appropriate determination of PKI as it is founded on subjective criteria. Subjectivity in interpretation of the PKI quality contributes to non-specificity of input data. The objective of the research is to obtain an efficient working framework for the application of the natural linguistic in determination of PKI architecture by using the fuzzy logic. In order to reduce the subjectivity in determining the appropriate PKI architecture, the authors propose the working framework based on selected parameters and fuzzy logic. For PKI architecture determination purposes, the authors use the value of a global limitation fulfillment for each architecture obtained by the Generalized Prioritized Fuzzy Constraint Satisfaction Problem.

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