The article is devoted to researching the prospects and possibilities of implementing the concept of a smart city in order to restore the industrial sector of Ukraine. The authors systematically analyze the key aspects of modern smart cities, in particular the use of advanced technologies of the Internet of Things, data analysis, and automation of production processes. The article highlights the potential benefits of implementing a smart grid in Ukrainian industry, such as increasing the efficiency of production processes, optimizing resource use, and creating environmentally friendly technological solutions. In particular, the possibilities of using smart technologies in production, logistics and management, as well as their impact on increasing the competitiveness of enterprises, are considered. The study is based on the study of the experience of implementing a smart grid in other countries and takes into account the specifics of the Ukrainian industrial sector. Thanks to this analysis, the authors provide specific recommendations for the implementation of a smart grid in Ukraine in order to increase its competitiveness and create sustainable economic growth.
AI technology presents new challenges in digital development which necessitates the creation of a regulatory framework for implementation of AI technological solutions. Public discussion in European public institutions, the scientific and professional community additionally contributes to this demand. According to the areas of AI Technology application, the regulation of AI solutions should be focused on specific problems related to implementation in certain parts of digital society. A special part of implementation is regulation of AI technology in public administration. The focus of this paper will be on the implementation ability of the general principle of AI technology regulation in specific solutions in public administration, according to EU AI Act and EU Digital Strategy. The first part is implementation of AI in central government services, the second part is implementation in local government services, and the third one is implementation in interactive communication between government authorities and citizens.
Patent analysis is the process of analyzing patent documents and other information throughout the patent lifecycle to uncover innovation insights and patterns in a particular area or technology field. It provides data-driven, evidence-based insights that allow organizations to make better strategic decisions in areas such as research and development, innovation policies, licensing, and research collaboration. Patent analysis is often carried out in several steps, such as data collection and extraction, analysis and finding patterns, and reporting results. Various methods have been used to analyze patent data in many technological fields. The goal of this paper is twofold: (i) to describe basic concepts and terminology of patent analysis, and (ii) to perform a systematic literature analysis to detect the most common methodology used for conducting patent analysis and to identify the technological fields that have been the focus of patent analyses in the last twenty years. The research is carried out in three steps: first, querying scientific databases; second, analyzing relevant articles within the patent analysis research area; and third, summarizing and reporting the state-of-the-art methodology and technological fields prevalent in patent analysis for the last twenty years.
Artificial intelligence is a global topic that holds significant importance in recent years. It sparks debates about its usage, but despite the contradictions that arise, there are many benefits to applying it in various areas. In this paper, the authors investigate the possibilities of implementing machine learning algorithms to help optimize crop management for precision agriculture. Meeting current food demands becomes an increasingly challenging task as the population grows. Applying machine learning using IoT data analytics in the agricultural sector will bring forth additional advantages, increasing not only the quantity but also the quality of production from crop fields to meet the rising food demands. The main objective of the paper is to employ various machine learning algorithms for predictive modeling and subsequently develop a robust model capable of making accurate predictions on unseen agricultural data. The research methodology involves preprocessing the acquired dataset, including data cleaning and feature engineering to enhance model performance. The authors systematically apply a range of machine learning algorithms, such as Logistic regression, Decision trees, Naïve Bayes, and k-nearest Neighbor, to identify the most effective approach for crop yield prediction. For better model performance, boosting techniques of machine learning are also implemented. Cross-validation and performance metrics such as accuracy, confusion matrix, precision, recall and F1 score, are included to evaluate the accuracy of the models, aiming to highlight the strengths and weaknesses of each algorithm in the context of precision agriculture.
Teaching methodology for high school students is in many ways different from teaching at the university level. This paper presents an approach to teaching introductory digital system design to high school students of ages 17-18. Students learn the basics of the functionality of digital system components with the goal of understanding the architecture of a simple hypothetical processor. This topic goes beyond the general high school curriculum in Serbia and is targeted at students in classes with a special curriculum for mathematics and computer science subjects. The class covered the following main topics: 1) fundamentals of combinational and sequential circuit design and 2) architecture and design of a simple processor. Practical sessions were performed using a simulator, such that each student designed their own instance of a processor with a simple set of instructions. The classes were evaluated using the exit surveys which showed that students widely accepted the simulator and learning material and were excited to experience and complete the design of a processor. This teaching experience provided additional motivation for the development of more learning materials in computer science and engineering for pre-university education.
Engineering programmes typically include a capstone project completed by individual students carrying specific requirements from a technical and accreditation perspective. To ensure that all proposed projects can be considered equally suited to address these requirements is a complex task. This creates a quality control problem since all projects must therefore comply with technical, curriculum, and accreditation requirements. In many cases, the quality assurance process is handled by a single project coordinator. However technically skilled, this is an unrealistic expectation when the number of projects increases. Peer-reviewing is a method to address this problem but manually assigning reviewers to project definitions only partially addresses the problem. A web-based tool was developed that guides individual project proposers through the requirements of a project, requires a self-review, and provides a peer-review process that rewards early active participation in the peer-reviewing process. Results indicate that the automated reviewing process is faster than using a single reviewer and that a more balanced set of feedback and outcomes is provided. This significantly improves the overall quality of the projects. The collective responsibility has improved the overall quality of the projects and also increased awareness of the various aspects to which each project should comply.
This study investigates the usability and applicability of High-Performance Computing (HPC) in photogrammetry for the creation of high-resolution 3D models for the preservation of cultural heritage. The study addresses the challenges posed by the large datasets generated for high-resolution photogrammetry and argues in favour of the potential of HPC to speed up processing time. By comparing different computer systems, from standard laptops to HPC, this study evaluates their potential on the basis of processing power and management. Case studies illustrate the practical applications at different heritage sites and underpin the study’s approach to technology selection. The paper concludes with insights into the benefits and future directions of integrating photogrammetry and HPC in cultural heritage conservation.
We live in a digital society and use a variety of tools and technologies to extend and enhance our everyday, working or learning experience. Education is one of the areas where ICT has already brought and can still bring major changes and improvements. Awareness about learning in a virtual environment came into focus, especially during the pandemic. ICT and virtual learning environment enabled the continuation of the educational process when everyone was facing lockdown. The University of Zagreb University Computing Centre SRCE maintains and develops the virtual learning environment for higher education. One of the significant segments of the virtual learning environment (VLE) is the Learning Management System (LMS) - Student Management System (SMS) connection that enables a seamless studying experience on the university level as well as across a virtual campus in an alliance (European University Alliances). Communication and exchange of information between the LMS and SMS using the European Student Identifier and eduGAIN for identification is crucial. In this paper, we will further elaborate on how they are working and why they are important.
In the dynamic landscape of communication technologies, the imminent arrival of 6G networks promises a transformative change that requires a proactive strategy to strengthen the underlying infrastructure. This research is driven by the mission to ensure the security, trustworthiness, and resilience of 6G networks by introducing innovative, intelligent controls at the physical layer. This involves integrating adaptive systems that dynamically adjust to evolving network conditions while alerting to and remediating security risks in real-time. This study aims to provide a robust foundation for 6G networks by eliminating vulnerabilities that could be exploited by malicious entities, with a focus on the physical layer. The proposed intelligent controls utilise advanced machine learning and adaptive algorithms to assess and improve the network’s security posture continuously. Based on a theoretical analysis, this research aims to contribute to the conceptual development of 6G networks that drive technological innovation and embody a secure and resilient architecture essential for the upcoming era of wireless communications. It will explore how intelligent physical layer controls, adaptive algorithms, and machine learning have improved the security of 6G networks.
A new algorithm for processing of quasiquadrature interferometric signals in optical sensors of incus vibration, based on a 3x3 single-mode fiber optical coupler and low current VCSEL, is presented. This sensor serves as a microphone in the totally implantable hearing aid device. The amplitude of incus vibration spans over a large dynamic range, from a few picometers to a few nanometers, corresponding to sound pressure levels of 30-120 dB, superimposed on slow and hundreds micron large movement of the incus, which is induced by atmospheric pressure changes and the patient physiological activities. Instead of the usual interferometric phase demodulation based on arctangent function, which is processor time and power-consuming, we propose a simple, fast, but accurate technique. In this approach, the low-frequency components of the raw quasi-quadrature signals are used to determine the octant in which the photodetector signals are located and the audio-frequency component of one or another photodetector signal is forwarded to the output, after a simple processing. Two 16bit ADCs, a DC restoration circuit for each of the interferometric channels and one 16-bit DAC are employed. The sampling rate was 16 kS/s and an ultra-low power 16-bit fixed-point microcontroller performed the signal processing.
This paper presents a comparative study of two powerful tools, Tracker and Python, in analyzing high-speed camera footage for exploring subharmonic oscillations in physics education. By utilizing high-speed video capture, we delve into the nuanced study of these oscillations, capturing intricate details at frame rates unattainable by standard video. Our study emphasizes the comparative effectiveness of Tracker, an open-source video analysis and modeling tool, and Python, a versatile programming language with extensive libraries for data analysis and visualization, in extracting and interpreting the physical parameters of subharmonic oscillations.We explore the capabilities of each tool in processing high-speed footage, focusing on their strengths in enhancing students’ understanding of complex oscillatory behaviors, and evaluate the ease of use, accuracy of data extraction, and the depth of analysis provided by Tracker and Python. By presenting a side-by-side analysis, we aim to guide educators in selecting the appropriate tool for their pedagogical needs, enhancing the learning experience in physics classrooms. The comparative analysis not only illuminates the potential of integrating advanced technologies in education but also serves as a guide for educators to harness these tools effectively in physics education.
This paper explores the transformation of electrocardiogram (ECG) monitoring from traditional offline to Real-Time analysis, enabled by high-speed mobile networks and affordable data plans. The transition to live monitoring presents challenges in data streaming and processing and the necessity of balancing immediacy with accuracy. We optimize two critical aspects of cloud architecture and scalability under the broader umbrella of cloud efficiency by evaluating the architecture’s components and their contribution to overall efficiency. The focus is on accommodating over a thousand concurrent patients streaming ECG data while maintaining cost-effectiveness, constrained by Near Real-Time Round Trip Time (RTT) of $\leq 3$ seconds, achieving a throughput of $\geq 333.333($ msgs/s).
Daily increase in the number of mobile users and the demand for better services on the rise have obliged network and service operators to implement 5G networks. However, concerns have been raised regarding the exposure to electromagnetic field radiated by advanced communication technology. This issue is especially evident in countries where 5G will operate simultaneously with previous technologies, for a considerable time period. Because of this, network operators must carefully plan the implementation of such networks under EMF constrains while still satisfying users demands in terms of quality-of-service. In this work we have presented the trade-off analysis between EMF values and user data rate from 5G non-standalone networks, by analyzing around 50 thousand real-world samples, measured for a period of one month. Our analysis shows that most cellular users achieve satisfactory data rate under acceptable EMF levels below 1V/m, however there are situations in which we observe spikes of EMF values. Our analysis shows that a trade-off between EMF levels and data rates of individual users can be achieved with careful planning of future 5G infrastructure.
The rise of Edge Computing has brought Single Board Computing Clusters (SBCCs) back into the spotlight. With their efficient performance-to-power ratio, SBCs are becoming key players in Edge Computing infrastructure. Previous studies have explored the performance and power efficiency of SBCCs, yet often lack a systematic approach to benchmarking, especially for big.LITTLE ARM-based SBCs like the Odroid-MC1, Odroid$- \mathrm{N}2 +$, and ASUS’ Tinker Board 2 series. This study addresses the need for thorough benchmarking of such systems by employing the High Performance Linpack Benchmark (HPL). With precise tuning and improved cooling, we achieved up to 24% better performance on the same platforms using ATLAS and OpenBLAS, revealing more potential than initially anticipated and further improving their already notable performance-per-watt ratio.
Word-processing (WP) was and still is one of the ubiquitous applications for many computer users. After about a half of century of its existence, it is considered stable, and is widely taught on all educational levels. Many users find themselves quite proficient in creating documents. However, after examining a number of publicly available documents and document templates (mostly from public sector, universities and scientific publishing) we found that many template creators and users just grasp basic knowledge of WP concepts while some of not so advanced concepts are mostly not used at all. In some cases when users were forced to use some of these features, they reverted to manual and forcible (overriding style) formatting and insertion of a numbering manually. Here we present our findings in WP literacy and give some recommendations for creating document templates, for teaching WP, and propose some modifications of WP applications for better acceptance of the more advanced concepts. The development of WP applications is mostly stagnant and recent additions only address collaboration features while other WP concepts that are considered widely known are not changed at all but obviously not well emphasizes in WP applications.
Social entrepreneurship is a type of entrepreneurship whose primary goal is to achieve a social impact by solving or alleviating a social problem. While focusing on a social purpose, making profit is essential to ensure the financial sustainability of the ventures. In the last 20 years social entrepreneurship is gaining importance in Croatia, although the concept is still rather unfamiliar. The aim of the paper was three-fold: to identify the presence of Croatian social entrepreneurs in the most popular social networks and analyzing types of their activities and their reach, to identify social network profiles which promote the concept of social entrepreneurship and to identify the topics that dominate the published content. The results showed that Facebook is the most used social network among the social enterprises in Croatia followed by Instagram, while TikTok is almost not used at all. Most of the social enterprises’ posts are promoting their products and services. Social entrepreneurs also promote other social initiatives and sometimes combine those with the promotion of their own products. There is an opportunity for social entrepreneurship promotors in Croatia to generate the content for younger generations on TikTok presenting them the examples and the benefits of social entrepreneurship.
The rapid advancements in Industry 4.0 and 5.0, along with the increasing adoption of edge computing, have brought about a significant transformation in industrial landscapes. These advancements have ushered in a new era of interconnected devices, real-time data processing, and decentralized decision making, creating an unprecedented volume of digital data. This surge in data generation has also heightened the need for robust digital forensics capabilities to investigate and respond to cyberattacks, data breaches, and other security incidents. This paper provides an overview of digital forensics in the context of Industry 4.0, Industry 5.0, and edge computing. It discusses the challenges and opportunities associated with forensic investigations in these environments, highlighting the unique characteristics of these technologies and their impact on the collection, preservation, and analysis of digital evidence. The paper also explores the potential applications of digital forensics in these industries, including incident response, fraud detection, and regulatory compliance.
In this paper we present a proposal for STEAM activity for classroom use in which students, biology teacher and informatics teacher actively collaborate. We draw on a short survey in which we identified students’ preconceptions on the topic of evolution. Students solve a specific problem related to evolution, using programming tools to understand the basic concepts of evolution and natural selection. The activity shows students that relying on impressions does not always lead to the right conclusion. Based on the results of simulation using their own programmed model, students confirm or disconfirm their preconceptions while also developing their critical thinking skills. The results of activity provide a good starting point for deeper understanding of the curriculum of both subjects. Students can explore other aspects of evolution in the context of biology lessons. In informatics, students gain experience of usefulness of programming, and the model is a propaedeutic for genetic algorithms that can be used to solve a wide range of practical problems. The activity also has potential to be beneficial for teachers themselves. Biology teacher develops his/her digital competences, and in addition, it helps informatics teacher to motivate students for programming itself. The activity thus has a strong synergistic effect for the benefit of both biology and informatics teaching.
This paper addresses the need for innovative strategies in the e-commerce industry to meet rising customer expectations. With a focus on improving scalability and performance, the paper advocates microservices-based architectures in distributed web systems. This study examines the literature on e-commerce and microservices in detail. Microservices provide agility, fast development cycles, and fault isolation, ensuring that e-commerce companies can effectively adapt to market changes. The proposed microservices-based architecture consists of small, independent services that can work together to create a single, robust e commerce application. However, implementing this type of architecture presents several technical challenges. One of these is the robustness of the microservices implementation. This article proposes a series of practical steps to successfully build an e commerce store, emphasizing the importance of microservices and focusing on reliability and robustness without sacrificing the scalable approach. It also provides a concrete example of implementing a back-end application using the virtualization provided by containers and technologies such as Python programming language, Django framework, PostgreSQL database. Finally, this article not only provides a detailed analysis of the advantages of microservice-based architectures in distributed web systems, but also serves as a practical guide and analysis of the current e-commerce context.
