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Tomo Popovic

Bio: Tomo Popovic is an academic researcher from University of Donja Gorica. The author has contributed to research in topics: Protective relay & Computer science. The author has an hindex of 13, co-authored 40 publications receiving 537 citations. Previous affiliations of Tomo Popovic include University of Montenegro & Texas A&M University.


Papers
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Journal ArticleDOI
TL;DR: The requirements and architecture of the proposed platform have been derived so that the users of the platform, researchers, and developers on the project, can utilize it for prototyping solutions for these high level use cases.

159 citations

Journal ArticleDOI
TL;DR: An active machine learning technique for monitoring the voltage stability in transmission systems is presented and identifies operating points where machine learning predictions based on power system measurements contradict with actual system conditions.
Abstract: An active machine learning technique for monitoring the voltage stability in transmission systems is presented. It has been shown that machine learning algorithms may be used to supplement the traditional simulation approach, but they suffer from the difficulties of online machine learning model update and offline training data preparation. We propose an active learning solution to enhance existing machine learning applications by actively interacting with the online prediction and offline training process. The technique identifies operating points where machine learning predictions based on power system measurements contradict with actual system conditions. By creating the training set around the identified operating points, it is possible to improve the capability of machine learning tools to predict future power system states. The technique also accelerates the offline training process by reducing the amount of simulations on a detailed power system model around operating points where correct predictions are made. Experiments show a significant advantage in relation to the training time, prediction time, and number of measurements that need to be queried to achieve high prediction accuracy.

75 citations

Journal ArticleDOI
TL;DR: Lacunarity and fractal dimension together quantitatively characterize microvascular geometry in the retina with higher specificity than fractal analysis alone.

54 citations

Journal ArticleDOI
TL;DR: The study found that attendance of face-to-face lectures had a positive impact on academic performance and high frequency of Moodle use was not always associated with better academic performance, suggesting that the introduction of a new method of teaching was most likely equally accepted by low- and high-achieving students.
Abstract: This study evaluates the impact of web-based blended learning in the physiology course at the Faculty of Medicine, University of Montenegro. The two main goals of the study were: to determine the impact of e-learning on student success in mastering the course, and to assess user satisfaction after the introduction of e-learning. The study compared a group of students who attended the physiology course before, with a group of students who attended the physiology course after the Moodle platform was fully implemented as an educational tool. Formative and summative assessment scores were compared between these two groups. The impact of high vs. low Moodle use on the assessment scores was analyzed. The satisfaction among Moodle users was assessed by the survey. The study found that attendance of face-to-face lectures had a positive impact on academic performance. The introduction of Moodle in the presented model of teaching increased interest of students, attendance of face-to-face lectures, as well as formative and summative scores. High frequency of Moodle use was not always associated with better academic performance, suggesting that the introduction of a new method of teaching was most likely equally accepted by low- and high-achieving students. Most of the students agreed that Moodle was easy to use and it complemented traditional teaching very well, but it could not completely replace traditional face-to-face lectures. The study supports continuing the use of web-based learning in a form of blended learning for physiology, as well as for other courses in medical education.

39 citations

Journal ArticleDOI
TL;DR: In this article, a new iterative method for frequency estimation in the unbalanced three-phase power system is proposed, which is based on the transformation of unbalanced 3-phase voltage signal into a complex exponential by using the orthogonal constant modulus algorithm.
Abstract: A new iterative method for frequency estimation in the unbalanced three-phase power system is proposed. The proposed solution is based on the transformation of unbalanced three-phase voltage signal into a complex exponential by using the orthogonal constant modulus algorithm. In addition, based on the transformed signal, a simple adaptive algorithm for frequency estimation is proposed. Beside the proposed approach, any frequency estimator designed for a single-tone complex exponential can be used here, which is also the advantage of the proposed method. Simulation results confirm that the proposed algorithm exhibits better performance compared to the considered algorithms.

35 citations


Cited by
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Journal ArticleDOI
TL;DR: The article explains the major components of IoT based smart farming, including network architecture and layers, network topologies used, and protocols, and some open research issues and challenges in IoT agriculture field have been presented.
Abstract: Internet of things (IoT) is a promising technology which provides efficient and reliable solutions towards the modernization of several domains. IoT based solutions are being developed to automatically maintain and monitor agricultural farms with minimal human involvement. The article presents many aspects of technologies involved in the domain of IoT in agriculture. It explains the major components of IoT based smart farming. A rigorous discussion on network technologies used in IoT based agriculture has been presented, that involves network architecture and layers, network topologies used, and protocols. Furthermore, the connection of IoT based agriculture systems with relevant technologies including cloud computing, big data storage and analytics has also been presented. In addition, security issues in IoT agriculture have been highlighted. A list of smart phone based and sensor based applications developed for different aspects of farm management has also been presented. Lastly, the regulations and policies made by several countries to standardize IoT based agriculture have been presented along with few available success stories. In the end, some open research issues and challenges in IoT agriculture field have been presented.

400 citations

01 Jan 2016
TL;DR: The lectures and the group projects will cover all aspects of the software life cycle, from development team management, problem specification and analysis, system design techniques, implementation and documentation practices, testing, to maintenance and evaluation of the final product.
Abstract: Software engineering is concerned with the development and evolution of high-quality software systems in a systematic, controlled, and efficient manner. Software engineers are concerned with safety and reliability of the product as well as the cost and schedule of the development process. The lectures and the group projects will cover all aspects of the software life cycle, from development team management, problem specification and analysis, system design techniques, implementation and documentation practices, testing, to maintenance and evaluation of the final product.

357 citations

Journal ArticleDOI
11 Jan 2019-Sensors
TL;DR: Results show that it is able to provide adequate performance for the SWAMP pilots, but requires specially designed configurations and the re-engineering of some components to provide higher scalability using less computational resources.
Abstract: The smart management of freshwater for precision irrigation in agriculture is essential for increasing crop yield and decreasing costs, while contributing to environmental sustainability. The intense use of technologies offers a means for providing the exact amount of water needed by plants. The Internet of Things (IoT) is the natural choice for smart water management applications, even though the integration of different technologies required for making it work seamlessly in practice is still not fully accomplished. The SWAMP project develops an IoT-based smart water management platform for precision irrigation in agriculture with a hands-on approach based on four pilots in Brazil and Europe. This paper presents the SWAMP architecture, platform, and system deployments that highlight the replicability of the platform, and, as scalability is a major concern for IoT applications, it includes a performance analysis of FIWARE components used in the Platform. Results show that it is able to provide adequate performance for the SWAMP pilots, but requires specially designed configurations and the re-engineering of some components to provide higher scalability using less computational resources.

265 citations

Journal ArticleDOI
TL;DR: This paper systematically reviews the development and deployment of smart energy meters, including smart electricity meters, smart heat meters, and smart gas meters, to provide insights and guidelines regarding the future development of smart meters.
Abstract: The significant increase in energy consumption and the rapid development of renewable energy, such as solar power and wind power, have brought huge challenges to energy security and the environment, which, in the meantime, stimulate the development of energy networks toward a more intelligent direction. Smart meters are the most fundamental components in the intelligent energy networks (IENs). In addition to measuring energy flows, smart energy meters can exchange the information on energy consumption and the status of energy networks between utility companies and consumers. Furthermore, smart energy meters can also be used to monitor and control home appliances and other devices according to the individual consumer’s instruction. This paper systematically reviews the development and deployment of smart energy meters, including smart electricity meters, smart heat meters, and smart gas meters. By examining various functions and applications of smart energy meters, as well as associated benefits and costs, this paper provides insights and guidelines regarding the future development of smart meters.

236 citations

Journal ArticleDOI
TL;DR: A survey of recent security advances in smart grid, by a data driven approach around the security vulnerabilities and solutions within the entire lifecycle of smart grid data, which are systematically decomposed into four sequential stages.
Abstract: With the integration of advanced computing and communication technologies, smart grid is considered as the next-generation power system, which promises self healing, resilience, sustainability, and efficiency to the energy critical infrastructure. The smart grid innovation brings enormous challenges and initiatives across both industry and academia, in which the security issue emerges to be a critical concern. In this paper, we present a survey of recent security advances in smart grid, by a data driven approach. Compared with existing related works, our survey is centered around the security vulnerabilities and solutions within the entire lifecycle of smart grid data, which are systematically decomposed into four sequential stages: 1) data generation; 2) data acquisition; 3) data storage; and 4) data processing. Moreover, we further review the security analytics in smart grid, which employs data analytics to ensure smart grid security. Finally, an effort to shed light on potential future research concludes this paper.

210 citations