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Underwater sensor networks are becoming an important field of re- search, because of its everyday increasing application scope. Examples of their application areas are environmental and pollution monitoring (mainly oil s...

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...

Abstract In an elastic network paradigm, where the transceiver is able to control several characteristics of the transmitted signal according to the optical link quality and capacity demand, receivers able to automatical...

Abstract The physical topology design (PTD) of optical networks is frequently accomplished by combining several solutions in an iterative way, especially if meta-heuristics are deployed for this purpose. Suitable operato...

A high efficiency hardware integration of neural networks benefits from realizing nonlinearity, network connectivity and learning fully in a physical substrate. Multiple systems have recently implemented some or all of t...

The communication of Corporate Social Responsibility (CSR) of a sample of eight restaurant and fast food companies is analyzed. An exploratory and descriptive method, based on the content analysis technique, is used to a...

The growth of transnational organised crime has been widely perceived as a major national and international security threat. The growth has been facilitated by globalisation, in which people, money, information and goods...

The construction of a network capturing the topological structure linked to the interactions among species and the analysis of its properties constitutes a clarifying way to understand the functioning of an ecosystem at ...

Mobile Ad-Hoc Networks (MANET) is a type of ad-hoc networks which use less infrastructure, that means the nodes in this network forward the massages without the need of infrastructure such as routers, switches etc. One o...

Loratadine (LOR) and pseudoephedrine sulfate (PES) were determined in pharmaceutical samples by using non-linear second-order data generated by a pH-gradient flow injection analysis (FIA) system with diode-array detectio...

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...

Multi-domain traffic engineering is a very challenging problem area and crankback signaling offers a very promising solutions framework herein. Although some initial crankback studies have been done, there is still signi...

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....

Nowadays, optical amplifiers designs are induced by new requirements generated by optical networks. The introduction of WDM reconfigurable networks with increasing rate from 10-40 Gb/s to 100 Gb/s and beyond, demand new ...

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 ...

Abstract The study of multi classification of data has become one of the important issues which geographical studies focus on especially those which take their data from satellites. Two ways of classification has been ta...

Functionalizacion of epoxy-based networks by the preferential surface enrichment of perfluorinated tails to achieve hydrophobic surface is described. The selected fluorinated epoxies (FE) were: 2,2,3,3,4,4,5,5,6,6,7,7,8,...

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; howev...

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...

We study the structural properties of networks formed by random sets of bit strings—namely the ordered arrays of binary variables representing, for instance, genetic information or cultural profiles. Two bit strings ar...