Results 51 to 60 of about 2,991 (173)

Numerical examination of concentration-dependent wastewater sludge ejected into a drinking water source

Scientific Reports, 2023
One of the significant water-related health challenges globally is due to pollutant fate. Contaminants endanger the lives of humans, animals, and even plants.
S. O. Adesanya, T. A. Adeosun, T. A. Yusuf, A. A. Adeyemi, J. S. Bamigboye, A. Ogunlaja, R. S. Lebelo, E. I. Unuabonah   +7 more
doaj   +1 more source

Pickin' up good vibrations: a systematic review of footfall detection and analysis in the realm of wildlife surveying

Wildlife Biology, EarlyView.
Exploration of new wildlife surveying methodologies that leverage advances in sensor technology and machine learning has led to tentative research into the application of seismology techniques. This, most commonly, involves the deployment of a footfall trap – a seismic sensor and data logger customised for wildlife footfall.
Benjamin J. Blackledge, Luigi La Spada, Robert A. Briers, Niamh M. McHugh, Patrick J. C. White   +4 more
wiley   +1 more source

New Analytical Solutions for Time-Fractional Kolmogorov-Petrovsky-Piskunov Equation with Variety of Initial Boundary Conditions

Mathematics, 2019
The generalized time fractional Kolmogorov-Petrovsky-Piskunov equation (FKPP), D t α ω ( x , t ) = a ( x , t ) D x x ω ( x , t ) + F ( ω ( x , t ) ) , which plays an important role in engineering ...
Thanon Korkiatsakul, Sanoe Koonprasert, Khomsan Neamprem   +2 more
doaj   +1 more source

Evolution and interpolation of double parton distributions using Chebyshev grids

European Physical Journal C: Particles and Fields, 2023
Double parton distributions are the nonperturbative ingredients needed for computing double parton scattering processes in hadron–hadron collisions. They describe a variety of correlations between two partons in a hadron and depend on a large number of ...
Markus Diehl, Riccardo Nagar, Peter Plößl, Frank J. Tackmann   +3 more
doaj   +1 more source

Image and video analysis using graph neural network for Internet of Medical Things and computer vision applications

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Graph neural networks (GNNs) have revolutionised the processing of information by facilitating the transmission of messages between graph nodes. Graph neural networks operate on graph‐structured data, which makes them suitable for a wide variety of computer vision problems, such as link prediction, node classification, and graph classification.
Amit Sharma, Ashutosh Sharma, Alexey Tselykh, Alexander Bozhenyuk, Byung‐Gyu Kim   +4 more
wiley   +1 more source

ANPGT: Towards Adaptive Node Property Extraction and Integration

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Graph transformers (GTs) with elaborate positional/structural encodings (PEs/SEs) have excelled in graph representation learning, especially in graph‐level tasks. However, their potential in large‐scale node classification remains untapped for several reasons: (i) Current PEs/SEs are insufficient in modelling large‐scale real‐world graphs ...
Qin Chen, Yuanyi Ren, Guojie Song, Liang Wang, Bo Zheng   +4 more
wiley   +1 more source

An efficient spectral algorithm for non-linear astrophysical Lane–Emden problem using pseudo-Chebyshev wavelets with error analysis

Franklin Open
Mother wavelets play a crucial role in wavelet analysis, leading to the development of several well-known families such as Haar, Morlet, Legendre, and Chebyshev wavelets.
Susheel Kumar, Satish Kumar, Sudhir Kumar Mishra, Shyam Lal   +3 more
doaj   +1 more source

Achieving Fair Spectrum Allocation and Reduced Spectrum Handoff in Wireless Sensor Networks: Modeling via Biobjective Optimization

Modelling and Simulation in Engineering, 2014
This paper considers the problem of centralized spectrum allocations in wireless sensor networks towards the following goals: (1) maximizing fairness, (2) reflecting the priority among sensor data, and (3) avoiding unnecessary spectrum handoff.
Sang-Seon Byun, Kimmo Kansanen, Ilangko Balasingham, Joon-Min Gil   +3 more
doaj   +1 more source

A Dynamic Correlation‐Information‐Fusion‐Based Spatiotemporal Network for Traffic Flow Forecasting

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Traffic Flow Forecasting (TFF) is a foundational task in the development of Intelligent Transport Systems (ITSs). The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network, unveiling the long‐term evolutionary traffic trends.
Dawen Xia, Zhan Lin, Xingyan Wang, Ruixi Huang, Jinhui Hu, Yang Hu, Huaqing Li   +6 more
wiley   +1 more source

Representation by several orthogonal polynomials for sums of finite products of Chebyshev polynomials of the first, third and fourth kinds

Advances in Difference Equations, 2019
The classical linearization problem concerns with determining the coefficients in the expansion of the product of two polynomials in terms of any given sequence of polynomials.
Taekyun Kim, Dae San Kim, Dmitry V. Dolgy, Dojin Kim   +3 more
doaj   +1 more source