Multi-authored monograph

Unmanned aerial vehicles. Perspectives. Management. Power supply : Multi-authored monograph / V. V. Holovenskiy, T. F. Shmelova,Y. M. Shmelev and oth.; Science Editor DSc. (Engineering), T. F. Shmelova. – Warsaw, 2019. – 100 p. - ISBN 978-83-66216-10-5.У монографії аналізуються можливі варіанти енергопостачання та управління безпілотними літальними апаратами. Також розглядається питання прийняття рішення оператором безпілотного літального апарату при управлінні у надзвичайних ситуаціях. Рекомендується для фахівців, аспірантів і студентів за спеціальностями 141 - «Електроенергетика, електротехніка та електромеханіка», 173 - «Авіоніка» та інших суміжних спеціальностей.The monograph analyzes the possible options for energy supply and control of unmanned aerial vehicles. Also, the issue of decision-making by the operator of an unmanned aerial vehicle in the management of emergencies is considered.

NASA Tech Briefs, January 1992

Topics include: New Product Ideas; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery/Automation; Fabrication; Mathematics and Information Sciences; Life Sciences

NASA Tech Briefs, March 1992

Topics include: New Product Ideas; Electronic Components and Circuits; Electronic Systems; Physical Sciences; Materials; Computer Programs; Mechanics; Machinery; Fabrication Technology; Mathematics and Information Sciences; Life Sciences

Water pressure optimisation for leakage management using deep reinforcement learning

In this thesis, we introduce a novel approach to pressure management using deep reinforcement learning (DRL) algorithms. Exploiting DRL algorithms to optimise pressure management in water distribution networks (WDNs) provides a more computationally efficient and resilient method to reduce background and burst leakage. Using DRL to manage pressure has proven as a valuable method to reduce leakage and carbon emissions in two case studies based on a real and benchmark water network. A cohort of eight DRL algorithms of varying natures are implemented on a benchmark test network and real network model of varying sizes to prove their scalability. An investigation on their ability to reduce both background and burst leakage is conducted to highlight their abilities with regards to different leak sizes. The application of deep reinforcement learning algorithms to control leakage in WDNs builds on from two extensive reviews of leakage management and DRL applications in the urban water systems. Collating this literature pinpoints the novelty in applying deep reinforcement learning algorithms to control pressure in WDNs and provides context to the thesis. To develop DRL algorithms fit for WDN operations, a novel python-based environment is created that can communicate the hydraulic capabilities of EPANET to the DRL agent. This involved multiple design choices including action space and observation space selection as well as formulating a reward function suitable for the multiple objectives relating to leakage reduction. Regarding background leakage, the best performing DRL algorithm resulted in 65.2% reduction in leakage in the benchmark network. However, the investigation on the real water network provided by Northumbrian Water Living has proved the strong dependency between valve locations and pressure management hence resulting in a negligible background leakage reduction. The ability of the DRL algorithms to deal with uncertainty through randomised burst nodes was investigated in the second case study. DRL policies demonstrated resilience in comparison to the standard optimisation algorithms used (differential evolution, particle swarm optimisation, and nelder mead). The best performing DRL algorithm predicted a 58.46% leakage reduction and 5650kg of reduced CO2 emissions in the benchmark water network. On the other hand, the best DRL performance optimised the real water network by reducing the leakage by 5.79% and carbon emissions by 1999kg of CO2

Social work with airports passengers

Social work at the airport is in to offer to passengers social services. The main methodological position is that people are under stress, which characterized by a particular set of characteristics in appearance and behavior. In such circumstances passenger attracts in his actions some attention. Only person whom he trusts can help him with the documents or psychologically

Digital Transformation in Healthcare

This book presents a collection of papers revealing the impact of advanced computation and instrumentation on healthcare. It highlights the increasing global trend driving innovation for a new era of multifunctional technologies for personalized digital healthcare. Moreover, it highlights that contemporary research on healthcare is performed on a multidisciplinary basis comprising computational engineering, biomedicine, biomedical engineering, electronic engineering, and automation engineering, among other areas

Digital Interaction and Machine Intelligence

This book is open access, which means that you have free and unlimited access. This book presents the Proceedings of the 9th Machine Intelligence and Digital Interaction Conference. Significant progress in the development of artificial intelligence (AI) and its wider use in many interactive products are quickly transforming further areas of our life, which results in the emergence of various new social phenomena. Many countries have been making efforts to understand these phenomena and find answers on how to put the development of artificial intelligence on the right track to support the common good of people and societies. These attempts require interdisciplinary actions, covering not only science disciplines involved in the development of artificial intelligence and human-computer interaction but also close cooperation between researchers and practitioners. For this reason, the main goal of the MIDI conference held on 9-10.12.2021 as a virtual event is to integrate two, until recently, independent fields of research in computer science: broadly understood artificial intelligence and human-technology interaction

Understanding, assessing, and facilitating entrepreneurship competence in the digital age

Entrepreneurship and entrepreneurship education become mainstream inside and outside business schools after scholarships and educators from this field made efforts in the past two decades. Nutrition of entrepreneurship competence is an emergency task for the economy and society especially during economic shock and uncertainty. Digital entrepreneurship competence brings new possibilities for learners living in this digital world. This study facilitates digital entrepreneurship and digital entrepreneurship competence as 21st-century skills at the higher education level, experimenting in Chinese universities and colleges. In addition, this research will help stakeholders in Germany and other countries whose learners lack such knowledge and skills. I propose a methodology set consisting of three main ingredients. Initially, a systematic review was undertaken by the researcher in collaboration with two educators who specialized in entrepreneurship theories and practice to extract insights on the utilization of educational technologies in the context of entrepreneurship education. In response to the current trend of educational technology, a comprehensive examination was conducted to scrutinize the regulations and potential of AI within entrepreneurship learning and teaching. Secondly, the present study endeavored to assess the effectiveness of virtual team learning in online entrepreneurship education during the COVID-19 pandemic, taking into consideration the dimensions of teamwork, taskwork, and information and communication technology. In the final investigation, a digital entrepreneurship training program was administered through an online platform, with the aim of obtaining both quantitative and qualitative feedback regarding the program’s effectiveness and assessing the participants’ digital entrepreneurship competence. The following presents a summary of each study: Regarding the systematic review on the utilization of educational technologies in entrepreneurship education, Study 1 uncovered that social media, serious games, and digital platforms emerged as three prominent technological approaches. In light of extensive application of artificial intelligence in various educational domains, Study 2 delved into its utilization within the context of entrepreneurship education. The findings indicated the prevalence of machine learning, big data analysis, and adaptive learning systems in this field. Meanwhile, the investigation identified potential prospects for the integration of natural language processing and chatbots in entrepreneurship teaching and learning. I evaluated online entrepreneurship education courses, supported by virtual teams from existing freely available learning content and multimedia materials. Evaluation of the content and materials is whether they fit the needs of educators and learners with various demographic backgrounds. Specifically, we evaluated the influence of gender and other demographic backgrounds on virtual team learning and its impact on entrepreneurship competence. Furthermore, experiential learning in online settings was explored in the field of entrepreneurship, focusing on the evaluation of an online practical entrepreneurship training program using the digital entrepreneurship competence framework. The research showed that digital opportunity identification competence is apparently improved from a complete novice to a nascent entrepreneur who understands the theory and practice of digital entrepreneurship. However, the effectiveness of online practical learning is limited because of participants’ isolation. If possible, tutorials and project guides are conducted online whereas experiential learning is partly moved into face-to-face contexts. To analyze entrepreneurship competence in the digital age, this thesis construct and discuss theoretical frameworks, namely entrepreneurship education, educational technology, and digital entrepreneurship competence. The current studies seldom analyze entrepreneurship competence in online entrepreneurship education programs. Therefore, this research attempts to understand, assess, and facilitate entrepreneurship competence and digital entrepreneurship competence in the digital age. The thesis consists of two qualitative studies (Study 1 and 3) and two quantitative studies (Study 2 and 4). This research aims to offer valuable insights for developing countries engaging in entrepreneurship education with limited resources, enabling the younger generation to navigate the path of venture creation. It holds practical and theoretical implications, establishing a solid foundation for online entrepreneurship education and fostering digital entrepreneurship competence. It is hoped that this thesis will inspire scholars and policy-makers to actively contribute to this field and work collaboratively