On the 20th of October 2023, Dr. Jaka Vodeb gave a lecture on the topic of quantum computing to the students of the University of Donja Gorica (UDG) and NCC Montenegro academic and industry partners.
Twinning between NCC germany and NCC Montenegro – Lecture on Quantum Computing
During the lecture, Dr. Vodeb addressed several key aspects of quantum computing, including its historical development, early stages, and the motivating factors behind its advancement. Additionally, he provided insights into the current state of quantum hardware and various quantum algorithms. At the end, he presented success stories where quantum computing demonstrated superior performance compared to conventional computing methods. Quantum computing lecture was organized as a fruitful collaboration between NCC Germany and NCC Montenegro. There was around 70 attendees at the lecture.
Over 70 attendees were presenet at the lectureStudents got an assignment to further research and write an essay on quantum computing
NCC Montenegro is organizing online introductory lecture about quantum computing and its applications.
Quantum computing is a cutting-edge field of computer science that leverages the principles of quantum mechanics to perform complex calculations at speeds far beyond what classical computers can achieve. Instead of using classical bits, quantum computers use quantum bits or qubits, which can exist in multiple states simultaneously due to superposition. This enables them to solve certain problems, such as factoring large numbers or simulating quantum systems, much faster than traditional computers. Quantum computing has the potential to revolutionize fields like AI/ML applications, cryptography, bioinformatics, digital manufacturing, optimization of traffic systems…
We are privileged to have Dr. Jaka Vodeb as our speaker. Dr. Vodeb is a postdoctoral researcher at the Jozef Stefan Institute and Fz Juelich (NCC Germany). His extensive expertise in quantum computing and quantum simulator ensures inspirational lectures.
Dr. Vodeb will give an overview of the quantum computing landscape, existing quantum hardware, quantum algorithms, quantum error correction and the quantum internet.
At the University of Donja Gorica, the Faculty of Information Systems and Technologies has commenced the implementation of the project “Application of Computer Vision and Deep Learning in Agriculture and Food Production, Medicine, and Energy (AI4S3).” The project is funded within the program to promote the development of an innovation culture and organize education in the fields of smart specialization in Montenegro by the Innovation Fund (https://fondzainovacije.me/).
Implementation of AI4S3 training started
On September 28th, as part of the 9th Festival of Science and Innovation, we had the opportunity to present our plans for the project’s implementation. The key idea of the project is to bring the application of artificial intelligence closer to the S3 sectors, which represent one of the key strategies for digitization in agriculture and supply chain, medicine, tourism, and energy sectors.
Over 65 candidates enrolled in the training
As previously announced, on September 30th, we organized an entrance test and questionnaire for all applicants. More than 65 candidates took the entrance test and questionnaire, and after analyzing the results, we selected more than 40 of them who will undergo training over the next 2 months.
The training is supported by the Innovation fund of Montenegro
Additionally, on October 7th, we began conducting lectures, starting with Python programming language, which forms the foundation for further training and the development of artificial intelligence models through upcoming modules. This training is a continuation of previous NCC Montenegro and Open Mind Academy efforts.
Congratulations to everyone, and we look forward to collaborating with all our participants.
The thesis underscores the effectiveness of artificial intelligence in combating phishing attacks and underscores the importance of continued research and innovation to safeguard users and their data in the digital realm. Beyond technical aspects, the paper provides a theoretical framework on cyber security, phishing attacks, and the role of artificial intelligence in modern cyber defense. It emphasizes the ongoing need for research and improvement in this area due to the evolving nature of cyber threats. This BSc theis work was done by Mr Ivan Novakovic under the menthorship of prof. Armin Alibasic.
Mr Novakovic defended his BSc thesis on AI in cybersecurity
ABSTRACT – This thesis addresses the critical issue of detecting phishing URLs, a prevalent cyber threat, using advanced artificial intelligence techniques. It examines three models—Logistic Regression, Random Forest, and LightGBM—through rigorous analysis and real data testing to assess their effectiveness in identifying malicious URLs. The results demonstrate that these models, when properly trained and calibrated, can achieve high accuracy in predicting the maliciousness of URLs.
The widespread use of ChatGPT has reshaped the labor market, offering both opportunities and challenges for companies and employees across various industries. This thesis has highlighted that the most positive impacts are likely to be seen in fields like medicine, trade, and education, while sectors such as customer support, media, and administration face significant challenges. ChatGPT should be viewed as a valuable ally for enhancing daily business tasks and boosting productivity. Ths BSc theis was done by Marko Raicevic under the mentorship of prof. Armin Alibasic.
Mr Marko Raicevic defending his BSc thesis on ChatGPT and AI in business
While the current version of this technology excels in certain areas like automation, information processing speed, and knowledge base, it is not poised to replace the majority of employees in the labor market. The future of businesses hinges on how we harness and deploy ChatGPT; it can either be a chance or a threat, depending on our development and utilization of this technology.
ABSTRACT – This thesis examines the groundbreaking impact of OpenAI’s ChatGPT, a revolutionary conversational AI, on the field of natural language processing. ChatGPT’s exceptional performance and capabilities have led to widespread adoption for daily business tasks, setting new trends in the job market. The paper explores ChatGPT’s role in various branches of artificial intelligence and its implications for diverse industries, considering its potential, limitations, and ethical concerns. The research draws on relevant literature to highlight the opportunities and challenges this technology presents. While routine tasks may be automated, ChatGPT is seen as a tool to enhance productivity, emphasizing that workers will not be replaced but augmented by its usage.
Mr Anel Gredic defended his BSc thesis titled “Time series and their application in meteorology” under mentorship of prof. Luka Filipovic. Thesis discusses the significance of time series analysis in meteorology. Time series, which are continuous records of meteorological data like temperature, precipitation, humidity, and wind speed, play a vital role in meteorological science. They are collected by specialized weather stations and satellites and are essential for meteorologists and climate researchers. Time series analysis involves using statistical methods and models to understand the variability of weather conditions over time. It helps identify seasonal patterns, trends, and extreme events, which in turn aids in weather forecasting and climate change monitoring. The application of time series analysis extends beyond meteorology, impacting various aspects of everyday life. This research has profound implications for society and various industries, improving safety, sustainability, and efficiency.
ABSTRACT – Time series are continuous sequences of meteorological data, such as temperature, precipitation, humidity, wind speed, etc., recorded over time at the same location. These data sets are often collected by specialized weather stations and satellites, and are an invaluable resource for meteorologists and climate researchers. Time series analysis is a fundamental component of meteorological science. Through the use of statistical methods, models and techniques, meteorologists can better understand the variability of weather conditions over time. This analysis enables the identification of seasonal patterns, trends and extreme events. It also helps develop models for weather forecasting and climate change monitoring. The application of time series extends to various aspects of our everyday life. Analysis of time series and their application in meteorology are crucial for understanding and predicting weather phenomena, climate change and protection against extreme weather events. This research has a profound and far-reaching impact on our society and various industries, contributing to the improvement of safety, sustainability and efficiency.
Mr Filip Radinovic defended his BSc thesis “A system for analyzing identification documents by leveraging Computer vision and Deep Learning” under co-mentorhsip of mr Stevan Cakic and prof. Tomo Popovic. The thesis focuses on the importance of identity in our digital world and how it impacts the security measures used by organizations. The main goal of the thesis is to use artificial intelligence to verify a person’s identity online. The researchers trained a model using various datasets and images, teaching it to spot even the smallest inconsistencies. The most significant discovery they made is that this model is very accurate, with a precision rate of around 90%. Additionally, the model is very efficient, taking only 3 to 4 seconds to process data, which is much faster than manual methods. Overall, the thesis highlights the potential of using AI for identity verification, making it both precise and time-saving.
The thesis focused on the use of computer vision and HPC/AI to develop tools for ID document analysis
ABSTRACT – Identity is one of the most sacred values and currencies in our digital era, affecting the working models of private and public institutions. This causes many strict security measures and protocols with a price of time, which is where this thesis’ goal arises. The approach of the thesis is leveraging artificial intelligence to accomplish identity verification over the web. The model was trained on a myriad of datasets and images, utilizing standard deep learning algorithms. By the end of training, it was able to detect the most subtle inconsistencies, making it quite precise. The biggest research finding is the potential that a model like this holds. Its precision varies around 90%, which is a good number by today’s standards and model’s testing conditions and hardware. The other aspect is time, in which the model excels. From the point when the model receives the data, the processing of it begins and it takes 3 to 4 seconds (on modest hardware). This implies superior efficiency than manual or alternative ways of accomplishing the same goal.
