Application of Python Programming Language in Analyzing the Operations of Silicon Valley Bank
Miloš ŽIVIĆ, Dejan NEMEC
The principal focus of this paper is an examination of the utilisation of the Python programming language, in conjunction with pertinent libraries (namely pandas, matplotlib, seaborn, etc.), for the purpose of analysing specific aspects of operations at Silicon Valley Bank (SVB). SVB was a financial institution with a lengthy history and notable presence in the technology sector. The bank’s primary activity was business with the economy, particularly with startups and venture capitalists. However, it ultimately failed in March 2023 due to its inability to adapt to the digital banking landscape. Its collapse had the potential to trigger a global financial crisis, but fortunately, this did not occur. This paper aims to analyze the bank’s operations and global events during this period using Python to determine whether the bankruptcy could have been avoided.
Wi-Fi 7 (IEEE 802.11be) Technology Features, Improvements It Brings and Expectations for Wi-Fi 8
Dejan NEMEC
IEEE 802.11be, is the latest standard in the IEEE 802.11 series. The Wi-Fi Alliance has named it Wi-Fi 7, since it follows Wi-Fi 6/6E. Over time, during 25 years, Wi-Fi wireless technology, from a speed of 1 Mbit/s, evolved to a technology that today allows a maximum of 46 Gbit/s. Such high speeds are possible by improving the technology that has been used so far and by introducing some new ones. The final IEEE 802.11be standard will be adopted in the coming months, while the Wi-Fi 7 certification process started on January 8, 2024. Although there are no specifications, the next Wi-Fi 8 is already announced, a generation that should bring new improvements. This paper lists the features, i.e. technologies related to Wi-Fi 7, a comparison with previous technologies and improvements that Wi-Fi 7 brings, as well as predictions of the basic features of Wi-Fi 8 are presented.
The Role of Applied Artificial Intelligence in Effective Natural Disaster Mitigation
Filip MARKOVIĆ, Žaklina SPALEVIĆ, Dejan RANČIĆ, Olivera PRONIĆ-RANČIĆ, Petar SPALEVIĆ
In recent years, advances in artificial intelligence have created new opportunities for more effective risk management and mitigation of natural disasters, which pose serious challenges to countries worldwide. Artificial intelligence techniques, including supervised learning, unsupervised learning, deep learning, reinforcement learning, and deep reinforcement learning, as presented in this paper, can be applied to disaster data analysis, early detection, decision-making, and intervention planning. In a global context, we face diverse natural disasters, and analyzing their distribution and frequency is essential for developing effective risk management strategies. Using data from the International Disaster Database Center (EM-DAT), this paper provides an overview of key disaster categories — geophysical, meteorological, and hydrological — in both the Republic of Serbia and worldwide from 2010 to 2023, highlighting the potential applications of artificial intelligence, which can play a pivotal role in all phases of disaster management.
Transformation of Learning in Higher Education based on AI-tools
Gordana OSTOJIĆ, Stevan STANKOVSKI, Goran ŠINIKOVIĆ
Innovation is a key indicator of a society’s development, reflecting its ability to create and implement new ideas within its environment. While often linked to the industrial era, innovation dates back millions of years, beginning with the first tools our ancestors used for hunting and food preparation. Today, advancements in artificial intelligence (AI) have introduced tools that significantly enhance the innovation process. However, leveraging these AI-based tools effectively requires a transformation in higher education, aligning learning methods with AI’s current and future capabilities. This thesis explores an approach to reshaping knowledge delivery in higher education, fostering innovation critical to business success.