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Abstract Echo State Networks are recurrent neural networks that leverage a random reservoir’s dynamics, training only a simple readout layer. This approach is computationally efficient but limits network performance. B...

Abstract In the world of the Internet of Things (IoT), wireless sensor networks (WSNs) play a vital role in enabling seamless communication between connected devices. In a WSN data prediction system based, clustering and...

Thermoelectric generators offer a promising solution for sustainable, low-maintenance energy harvesting in smart agriculture, especially for powering off-grid sensor nodes and microgrid systems. However, their inherently...

Abstract Background Protein-protein interaction (PPI) network-based protein function prediction algorithms, which use the guilt-by-association principle, are widely applied in medical and human domains, but they are comp...

The prediction of suspended sediment concentration (SSC) is of critical importance for the management of aquatic ecosystems, flood control, and erosion assessments. However, the continuous measurement of SSC is technical...

Abstract Faculty hiring shapes the flow of ideas, resources, and opportunities in academia, influencing not only individual career trajectories but also broader patterns of institutional prestige and scientific progress....

Abstract Active power distribution networks are evolving with the integration of distributed energy resources (DERs) and advanced optimization techniques to enhance grid flexibility and efficiency. However, radial distri...

This paper addresses the challenge of packet-based information routing in large-scale communication networks. The problem is framed as a constrained statistical learning task, where each network node operates using only ...

The article examines current approaches to optimizing the operating modes of distributed technical systems based on automation and intelligent control technologies, using the example of 10 kV electric networks. The analy...

Abstract The rapid adoption of encrypted communication protocols has raised privacy levels but has also dealt a significant blow to traditional intrusion detection systems that rely on payload inspection for anomaly dete...

"Conventional network generation models exhibit limitations in capturing complex structural patterns influenced by nodal and link attributes. While recent models have partially addressed this issue, significant gaps pers...

Low-power and Lossy IoT Networks (LLNs) comprise physical sensors, processing capability, power, and other technologies to exchange information between systems and devices over the internet. However, these networks are s...

To address the challenges of voltage deviation and increased network losses arising from the high integration of photovoltaic (PV) systems in distribution networks, this paper proposes a bi-level optimisation model for c...

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...

Research background: innovation is a key factor in determining the growth of the creative industries sector. However, it also highlights the importance of the creative industries to the broader innovation process within ...

Although the mobility protocols have improved, Proxy Mobile IPv6 (PMIPv6)-Based Distributed Mobility Management (DMM) networks still have significant challenges to ensure a seamless user mobility. These problems include ...

Mobile genetic elements (MGEs) such as bacteriophages and plasmids profoundly shape microbial community structure and drive horizontal gene transfer across ecosystems. Wastewater treatment systems, with their high cell d...

For an integer [Formula: see text], consider a collection of numbers [Formula: see text] and a network [Formula: see text] with [Formula: see text] and [Formula: see text]. The challenge is to create a variety of network...

Abstract This paper presents a model for path-based growing network with preferential attachment motivated by the deployment of quantum key distribution networks. The model is based on a network constructed from path seg...

Abstract Genetic interaction and protein-protein interaction networks have proved among the most important tools for inference of gene function and genotype-phenotype relationship. It remains unclear, however, how these ...

Understanding how students form and maintain social networks in volunteer organizations is crucial for promoting collaboration, effective communication, and the flow of resources within these groups. While prior research...

Abstract Background Endothelial cells (ECs) orchestrate vascular homeostasis and resilience but can undergo reprogramming into a mesenchymal-like phenotype through an endothelial-to-mesenchymal transition (EndMT). Crucia...

Spiking neural networks (SNNs) offer a biologically inspired, energy-efficient alternative to conventional artificial neural networks (ANNs). However, deep SNNs struggle to process complex EEG signals because their spike...

Graph-based text classification has become an effective paradigm for modeling corpus-level structure, particularly under limited supervision. However, most existing approaches rely on document–word representations...