Results 121 to 130 of about 145,155 (289)

Empowering smart cities: Leveraging advanced forecasting models for proactive rainfall prediction and resilient urban planning

AIP Advances
This study highlights the pivotal role of rainfall prediction within the dynamic landscape of smart cities. Accurate rainfall forecasts in such urban environments are foundational for bolstering infrastructure resilience, optimizing resource allocation ...
Abdulnoor A. J. Ghanim, Ahmad Shaf, Muhammad Irfan, Fawaz Alzabari, Muawia Abdelkafi Magzoub Mohamed Ali   +4 more
doaj   +1 more source

Trend and prediction of daily incidence of hand, foot, and mouth disease in Shenzhen, 2011 - 2023 with projections to 2024: a Prophet model approach

Zhongguo gonggong weisheng
ObjectiveTo evaluate the performance of the Prophet model in predicting the daily incidence of hand, foot, and mouth disease (HFMD) in Shenzhen city, to analyze the impact of the COVID-19 pandemic, public holidays, and school vacations (summer/winter) on
Wenhai LU, Lixia SONG, Huawei XIONG, Zhigao CHEN, Yan LU, Yanpeng CHENG, Zhen ZHANG   +6 more
doaj   +1 more source

Examining the Impact of Row Planting on Labor Use for Sustainable Food Production Among Maize Farmers in Rural Ghana

Agribusiness, EarlyView.
ABSTRACT Smallholder farmers are reverting to traditional production methods due to the high opportunity costs and unintended consequences of new technologies. This study focuses on row planting technology, which is labor‐intensive and slow without mechanized operations.
Emmanuel Tetteh Jumpah, Habtamu Alem, Abdulai Adams, Tomáš Ratinger, Miroslava Bavorová   +4 more
wiley   +1 more source

New constant modulus algorithm suitable for nonconstant modulus signals

Tongxin xuebao, 2011
The steady-state mean square error（MSE） of constant modulus algorithm（CMA） can not converge to zero for nonconstant modulus signals.By changing the multimodulus of nonconstant modulus source to single modulus,a new cost function was defined.And the new ...
RAO Wei1, SUN Hui1, GUO Ye-cai2, DENG Cheng-zhi1, WANG Sheng-qian1, TIAN Wei1   +5 more
doaj   +2 more sources

Enhancing Sustainability Label Effectiveness Through Logo Design Modification: An Analysis of the EU Green Leaf Logo

Agribusiness, EarlyView.
ABSTRACT Sustainability labels can help support consumers select more socially and environmentally friendly options, thereby enhancing returns for conscientious producers and promoting the transition to a more sustainable food system. However, consumer confusion regarding labels' meaning undermines their effectiveness.
Monika Hartmann, Ching‐Hua Yeh, Matthew Gorton, Barbara Tocco, Áron Török   +4 more
wiley   +1 more source

Domain‐Aware Implicit Network for Arbitrary‐Scale Remote Sensing Image Super‐Resolution

Advanced Intelligent Discovery, EarlyView.
Although existing arbitrary‐scale image super‐resolution methods are flexible to reconstruct images with arbitrary scales, the characteristic of training distribution is neglected that there exists domain shift between samples of various scales. In this work, a Domain‐Aware Implicit Network (DAIN) is proposed to handle it from the perspective of domain
Xiaoxuan Ren, Qian Jiang, Xin Jin, Puming Wang, Xing Chu, Shaowen Yao, Shengfa Miao   +6 more
wiley   +1 more source

Decoding Tattoo and Permanent Makeup Pigments: Linking Physicochemical Properties to Absorption, Distribution, Metabolism, and Elimination Profiles Using Quantitative Structure–Activity Relationship (QSAR)‐Based New Approach Methodologies (NAMs)

Advanced Intelligent Discovery, EarlyView.
This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod, Ajay Vikram Singh, Preeti Bhardwaj, Tulika Rai, Sweta Vijay Nakhale, Amruta Shelar, Rajendra Patil, Peter Laux, Andreas Luch, Christopher J. Osgood, Michael W. Stacey   +10 more
wiley   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Deep Learning Prediction of Surface Roughness in Multi‐Stage Microneedle Fabrication: A Long Short‐Term Memory‐Recurrent Neural Network Approach

Advanced Intelligent Discovery, EarlyView.
A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour, Sara Soltanabadi Farshi, Tuanna Ozcan, Amir Mohammad Ketabchi, Alper Kiraz, Savas Tasoglu   +5 more
wiley   +1 more source

A Weighted Soft-Max PNLMS Algorithm for Sparse System Identification

International Journal of Information and Communication Technology Research, 2016
This paper presents a new Proportionate Normalized Least Mean Square (PNLMS) adaptive algorithm using a soft maximum operator for sparse system identification.
Mehdi Bekrani, Hadi Zayyani
doaj