Guest from El Salvador delivered a lecture for the students of Faculty of Civil Engineering at VILNIUS TECH

Are you looking for eBooks for research and study? We invite you to use the VILNIUS TECH eBook platform ebooks.vilniustech.lt. VILNIUS TECH eBooks – More than 700 VILNIUS TECH eBooks published in a wide range of academic disciplines. You will be able to: Choose books based on your interests and relevant topics. Purchase an electronic version of a book for a week, a month or a semester. Purchase a printed copy of the VILNIUS TECH book. Are you a member of the VILNIUS TECH community? The VILNIUS TECH community members can access all eBooks on ebooks.vilniustech.lt free of charge while using the university network (e.g., at University) or working/studying remotely and using VPN. Where can you read eBooks? You can read eBooks on your PC (Windows, Mac), smartphone, and tablet. Where can you find your eBook subscription? Purchased or subscribed eBooks can be found in the Bookshelf tab. Where can you find all eBooks? All VILNIUS TECH eBooks can be found in the Catalogue tab. How do you search? You can search for the eBook by entering a title or keyword in the search box or using Advanced Search. You can select where to search for your keyword in the Advanced Search: Catalogue - will search for books in the catalogue; Description - will search for the keyword in full-text documents (PDF). If you select Phrase Match, you can search for the exact phrase you need. You can also narrow your search by author, eISBN, year, or category. How do you filter eBooks? You can filter eBooks by Publication date and Categories using the Filter by function. Printed books are available for purchase. It is important for the reader to make sure that a book contains all the information they need when planning to buy it. It is possible to search for the required information (words, phrases, or sentences) among all books available on ebooks.vilniustech.lt. In addition, before purchasing a book, it is possible to browse the table of contents and read excerpts. All VILNIUS TECH eBooks have an individual DOI provided in URL format. If you encounter such a link in another source of information (books, articles, websites, etc.), type it into your web browser, and you will be redirected to the specific eBook. If you have questions about eBook acquisition and subscriptions, please contact ebooks@vilniustech.lt. * The VILNIUS TECH community members can access the eBooks through the University's computer network and from home by connecting to the VILNIUS TECH network through a VPN. The VILNIUS TECH community can connect to an institutional account. To read eBooks offline, users need to download the Mon`k offline app by navigating to the home page and accessing the download section. To install the app on your phone, download the Mon`k app from the Google Play Store or Apple App Store.

VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Research and development of methods for detection and recognition of unmanned aerial vehicles“ prepared at VILNIUS TECH by Tomas Jačionis. The dissertation was prepared in 2018–2026. Scientific consultant – Prof. Dr Vytautas Urbanavičius. The dissertation was defended at the public meeting of the Dissertation Defence Council of the Scientific Field of Electrical and Electronic Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 10 a.m. on 16 September 2026. Unmanned Aerial Vehicle (UAV) detection has become a critical element of modern security systems. It is essential for safeguarding national security, maintaining airspace sovereignty, and protecting critical infrastructure, including power networks, military facilities, and fuel manufacturing and storage sites. As UAV technologies become more advanced and accessible, reliable detection methods are increasingly required to counter emerging threats. Artificial intelligence integrated into UAV flight-control systems is increasingly enabling UAVs to operate without emitting radio communication signals, which have traditionally been exploited for detection via electromagnetic (EM) spectrum analysis. This technological development creates substantial challenges for detecting UAVs, UAV swarms, kamikaze-type drones, and other electrically powered UAVs, particularly when they operate in complete radio silence. The dissertation proposes a novel method for detecting electrically powered multirotor UAVs by analysing and identifying the EM signatures radiated by their electric propulsion motor systems. An EM signature is the measurable pattern of the EM radiation spectrum produced by a UAV’s electric propulsion system due to time-varying electrical currents and voltages. It is characterised by distinct frequency, amplitude, and time features that enable the detection and identification of EM sources, including UAVs, through their propulsion-related EM emissions. These EM signatures vary dynamically with flight conditions, thereby providing a new detection modality even when conventional radio-frequency-based methods are ineffective. The dissertation proposes theoretical models of the EM radiation of a quadcopter UAV electric propulsion system and of the EM signature structure of UAV brushless direct current (BLDC) propulsion motors. The quadcopter UAV model enables assessment of radiation intensity and directivity. In contrast, the EM signature structure model reveals the dependence of the BLDC motor frequency spectrum on the pulse-width-modulated supply-current duty cycle and on the switching and phase-commutation frequencies. An experimental investigation was conducted to analyse the EM signatures radiated by the airborne UAV’s electric propulsion system. The findings include a detailed comparison of the EM signatures of various UAV models with those of similar electric motors used in domestic appliances. The results for the EM signatures of four serial-production UAVs are presented, including a case of a UAV swarm EM signature. The proposed mathematical model and experimental results demonstrate the feasibility of reliably recognising and classifying the EM signatures of an electrically powered multirotor UAV. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.