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Abstract The rapid adoption of AI is transforming industrial wastewater treatment by enabling real-time monitoring, predictive control, and operational optimization. Publications on the subject accelerated sharply betwee...

ABSTRACT Background The COVID‐19 pandemic has caused massive devastation worldwide, and its effects still persist. Managing the early stages was difficult, but scientists worked tirelessly to control it. The emergence ...

Abstract Heritage crops are recognized for their genetic diversity and naturally elevated antioxidant profiles, including polyphenols, flavonoids, and carotenoids. However, their nutritional value is highly sensitive to ...

Cloud computing environments face persistent structural challenges in cost control, dynamic resource allocation, and security risk management, which traditional infrastructure approaches fail to address adequately. This ...

Abstract The Internet of Things (IoT) and emerging technologies have converged to drive the remarkable development of intelligent systems. The interconnection of physical objects, sensors, and tiny communication devices ...

Abstract Financial institutions continue to face a significant challenge with money laundering and need intelligent, scalable ways to detect illegal financial activity. This paper introduces a machine learning-driven pla...

Water security in the Gulf Cooperation Council (GCC) is under existential threat from aquifer depletion, intensifying climate extremes, and escalating demand. While satellite Earth observation (EO) provides unprecedented...

In recent years, generative artificial intelligence represented by large language models (LLMs) and multimodal large language models (MLLMs) has achieved remarkable progress. These ultra-large-scale and complex models im...

Digital Twin Networks (DTNs) are emerging as a key enabler for the robust optimization and lifecycle management of next-generation networks. However, current DTN approaches still rely heavily on manual design, implementa...

Abstract The growing importance of machine learning in geological data computing, as well as in the broader geoscience and energy sectors, makes it essential to evaluate the impact of data augmentation on model performan...

Abstract This paper seeks to investigate the use of Natural Language Processing techniques in analyzing the Bhagavad Gita, a fundamental text in Hindu philosophy that has stood the test of time and centuries of interpret...

Abstract In response to the dual challenges of complex static obstacles and frequent dynamic disturbances in the construction site environment, this paper proposes a hybrid path planning strategy that integrates global s...

Digital health increasingly relies on artificial intelligence for clinical decision-making, patient management, and distributed learning, yet two persistent challenges remain: the computational complexity of optimization...

Abstract Long-range dependency processing is the core challenge of sequence modeling, and traditional sequence modeling algorithms suffer from information decay and low parallel computing efficiency in ultra long sequenc...

Abstract Skin diseases affect a considerable part of the world population, but it is not easy to diagnose these diseases on time because of the limited availability of dermatologists and the similarity of lesions. This r...

The growing demand for intensive artificial intelligence applications, such as deep neural networks and Large Language Models (LLMs), has driven the creation of architecture extensions and accelerators for matrix multipl...