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IMPACT OF DIGITAL TRANSFORMATION ON SME COMPETITIVENESS

Digital transformation is reshaping the way Small and Medium Enterprises (SMEs) operate and compete in today’s dynamic markets. By adopting technologies such as cloud computing, artificial intelligence, and data analytics, SMEs can improve efficiency, innovation, and customer engagement. Digital tools enable better decision-making, streamline operations, and open access to global markets. E-commerce platforms and digital marketing strategies help SMEs reach a broader customer base at lower costs. Moreover, automation and digital collaboration tools enhance productivity and adaptability. However, challenges such as limited digital skills, high implementation costs, and cybersecurity risks often slow adoption. Overcoming these barriers can significantly enhance SMEs’ competitiveness, enabling them to match or even outperform larger firms. Ultimately, digital transformation empowers SMEs to innovate, scale sustainably, and thrive in an increasingly digital economy.

Carbon capture utilization and technologies

Carbon Capture, Utilization, and Storage (CCUS) technologies are essential in addressing global climate change by capturing carbon dioxide (CO₂) emissions before they reach the atmosphere. The process involves three main stages — capturing CO₂ from industrial plants or directly from the air, transporting it through pipelines or ships, and then either storing it underground or utilizing it in useful products. Utilization includes converting CO₂ into fuels, building materials, or chemicals, promoting a circular carbon economy. These technologies help industries transition toward net-zero emissions without halting production. CCUS also supports cleaner energy systems by reducing emissions from fossil fuel use. However, challenges like high costs, energy requirements, and large-scale deployment remain. Continued innovation and global collaboration are key to making CCUS more efficient and accessible.

IMPROVEMENT OF SMART GRID STABILITY AT TIMES OF NETWORK ATTACKS USING ARTIFICIAL INTELLIGENCE

Smart grids, which are becoming increasingly vulnerable to cyber and network attacks as the digitalization of power systems increases, are highly efficient and reliable. Grid stability can be seriously compromised by malicious intrusions, denial-of-service attacks, and false data injection, which are all threats to energy security.

During such attacks, AI-driven strategies should be developed to enhance smart grid stability and resilience. With the aid of machine learning, deep learning, and reinforcement learning models, this study aims to detect intrusions in real-time, devise adaptive control mechanisms, and analyze faults in advance in order to mitigate disruptions. Also, the research will develop intelligent algorithms capable of identifying anomalous patterns, identifying threats, and restoring grid balance. Ultimately, the research aims to create a robust AI framework for smart grids that are safe, stable, and sustainable, as well as a way to ensure that critical infrastructure is protected against cyber attacks in the future.

DEPRESSION DETECTION BASED ON DEEP LEARNING

The stigma of depression, lack of awareness, and limited access to mental health professionals often prevent depression from being diagnosed. By analyzing diverse data sources, such as facial expressions, voice patterns, textual content, and physiological signals, deep learning offers promising solutions for early detection. The objective of this research is to develop and assess deep learning models that are highly accurate and reliable at identifying depression indicators.

In the study, multimodal data processing and feature extraction are integrated to enhance detection accuracy, facilitate timely interventions, and facilitate technology-driven mental health assessment. A system like this could be implemented in clinical settings, telehealth platforms, or even integrated into everyday digital interactions. As part of the research, ethical considerations such as ensuring privacy, informed consent, and responsible use of AI will also be addressed.