Abstract: The paper presents modeling of Computer Science curriculum based on ontologies. The main concept of the proposed ontological model is the competence defined by IEEE RCD standard. Mapping of the IEEE RCD data model to ontological model is described in detail. ACM Computing classification is used for domain knowledge modeling. Protégé tool is used for designing ontologies.

Abstract: This paper describes the implementation of the native mobile application for Android operating system. Realized application is the aid for learning and testing process of the users in the integrated learning system. Components of this eco system are presented with an emphasis on mobile application. Plans for future development are given.

Abstract: The current trend in education is towards flexible and creative institutions that are capable of sustained change and development. E-learning plays an important role in the process of accessing, collecting, analyzing and transforming information and knowledge. The greatest contribution has to do with bettering both the teaching staff and the students and raising the process of education to a higher level. The quality of teaching and the system for managing the process of learning is likewise improved. The primary aim of E-learning is to enhance the quality of contribution to a particular organization, i.e. an educational institution. The research testifies to the importance of E-learning, as well as the quality of instructional content, and the results have been obtained by means of a survey conducted among students who use the learning management system. The teaching materials which are posted on the learning management system, as well as the activities through which students acquire knowledge, have been clearly outlined in the paper. A suggestion as to how to improve certain materials in order to enhance the quality of knowledge has also been offered on the basis of the results obtained in the survey.

Abstract: Modern society is a fast-moving, achievement-oriented, very competitive and lead to many stressful situations, which individuals cannot handle always. The consequence of that state is burnout effect. We propose usage of system dynamics methodology in exploration of burnout effect. Several experiments have been conducted and presented which indicate increase and collapse behaviour in case of burnout experience by the individual.

Abstract: This paper will describe the potential of computerized adaptive testing, as a part of E-learning, within a corporate context. The success of any organization today is more and more dependent on the quality of the people they are able to attract, recruit and retain and employee value is essential for competitive market environment. Adaptive tests are designed to maximize measurement efficiency, or the precision of test scores in relation to test length. Therefore, the potential of computerized adaptive testing in determining employees knowledge and skills development, which are vital in any organization, is going to be presented and analyzed

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.