Backdoor attacks pose a critical and increasingly realistic security threat to deep neural networks (DNNs), enabling adversaries to implant hidden behaviors that remain dormant under normal conditions while preserving high performance on benign data. Although numerous defenses have been proposed, most works treat the interaction between attackers and defenders in isolation, without a principled...

The exponential growth of data traffic and user demand in modern communication systems has significantly increased the complexity of data streaming and management in Beyond Fifth Generation (B5G) networks. These networks face critical challenges such as network congestion, traffic load imbalance, latency, energy consumption, spectrum inefficiency, and limited storage capacity for real-time cont...

Unmanned Aerial Vehicle (UAV) path planning in unknown environments continues to pose a significant challenge, as Deep Reinforcement Learning (DRL) solutions are often severely hampered by slow convergence rates as well as unstable training dynamics. To address this gap, we introduce a Genetic Programming–seeded Soft Actor–Critic (GP+SAC) approach in which Genetic Programming produces high-qual...

Vehicular Ad hoc Networks (VANETs) face significant challenges in maintaining seamless connectivity due to frequent handovers caused by high vehicular mobility, fluctuating signal strength, and dynamic traffic conditions. Conventional static threshold‑based handover schemes are unable to adapt to these variations, often resulting in excessive latency, packet loss, handover failures, and poor re...

Understanding public opinion at scale is both a scientific challenge and a practical necessity in the digital era, as the proliferation of online communication platforms has created unprecedented opportunities to monitor attitudes in near real time. Early work in subjectivity detection and semantic orientation laid the methodological foundations for automated sentiment extraction, focusing on d...

The advancement of the Internet of Things (IoT) provides a set of new possibilities and challenges within the Industrial and Manufacturing environments, as well as into the Private Sector and the user daily life in our houses. In this context it is important to design and provide an IoT integrated system with a scalable architecture while maintaining a set of competitive costs and performance. ...

As an ultimate generalisation to several kinds of generalised entropy in the literature, a novel entropy measure, namely, Ismail’s entropy, or (IE), is presented. This article spotlights the significance of fractal dimension, through highlighting several possible applications of fractal dimension to structural engineering. In addition to several difficult open problems and the next step of inqu...

The use of artificial intelligence (AI) as a data science tool for education has enormous potential for increasing student performance and course outcomes. However, the growing concern about fairness, bias, and ethics in AI systems requires a careful examination of these issues in an educational context. Using AI and predictive modelling tools, this paper explores the aspects influencing studen...

The production of new apartments in Sweden has varied strongly during the period from 1975 to 2021. A new statistical function, which explains these production changes, has been developed. This function is designed, based on a set of hypotheses of how the production level should be affected by different explaining factors, such as the GNP, the size of the population, the growth of the populatio...

The current paper provides a cutting-edge information data length-theoretic approach to the transient M/M/∞ queueing system. This is the first investigation that unifies information data length and queueing theories. Notably, an exposition of a significant real-life application of the M/M/∞ queueing system was addressed, namely the computation of the common average time for unsaturated site vis...

This paper proposes a multi agent value decomposition network (VDN) based multi UAV collaborative reconnaissance and control method to address the issue of insufficient strategies for multi UAV collaborative reconnaissance and control. By designing corresponding algorithm networks and training processes, the goal of autonomy, collaboration, and intelligence among multiple unmanned aerial vehicl...

Nowadays, cybersecurity stands out as a prominent topic frequently discussed by companies aiming to safeguard their data from hacking attempts. The rise of cyberspace has fuelled the expansion of electronic systems, creating a virtual digital realm that links computers and smartphones within the Internet of Things framework. Thus, the purpose of this study is to present the progress made thus f...

The emergence of generative artificial intelligence (AI) technologies, such as large language models (LLMs) like ChatGPT, has precipitated a para...

This study proposes a marketing strategy framework tailored to address the challenges faced by small and medium-sized enterprises (SMEs) in Uzbekistan. Amidst a fiercely competitive business landscape, SMEs encounter obstacles in establishing brand awareness, attracting customers, and optimizing financial performance. To address these challenges and sustain growth, SMEs can leverage the extende...