Results 111 to 120 of about 145,710 (264)

Sampling Strategy: An Overlooked Factor Affecting Artificial Intelligence Prediction Accuracy of Peptides’ Physicochemical Properties

Advanced Intelligent Discovery, EarlyView.
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan, Ankeer Abuduhebaier, Haojin Zhou, Jiaqi Wang   +3 more
wiley   +1 more source

Adaptive Least Error Rate Algorithm for Neural Network Classifiers

, 2001
We consider sample-by-sample adaptive training of two-class neural network classifiers. Specific applications that we have in mind are communication channel equalization and code-division multiple-access (CDMA) multiuser detection. Typically, training of
Chen, S., Hanzo, L., Mulgrew, B.
core   +1 more source

Advancing Efficient Error Reduction in DNA Data Storage Systems with Deep Learning‐Based Denoising Models

Advanced Intelligent Discovery, EarlyView.
Deep learning‐based denoising models are applied to DNA data storage systems to enhance error reduction and data fidelity. By integrating DnCNN with DNA sequence encoding methods, the study demonstrates significant improvements in image quality and correction of substitution errors, revealing a promising path toward robust and efficient DNA‐based ...
Seongjun Seo, Anshula Tandon, Nguyen Kim Uyen, Quoc Nam Le, Jee‐Hyong Lee, Sung Ha Park   +5 more
wiley   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Constructing a new estimator for estimating population mean utilizing auxiliary information in probability proportional to size sampling

Alexandria Engineering Journal
In some instances, the size of the target population might exhibit significant variation. In the medical investigation, the number of individuals troubled with a certain infection and the scale of the medical facilities may differ.
Safar M. Alghamdi, Sohaib Ahmad, Sanaa Mohammed Almarzouki, Badr Aloraini, Majdah Mohammed Badr, M.A. Abdelkawy   +5 more
doaj   +1 more source

Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering

Advanced Intelligent Discovery, EarlyView.
Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley   +1 more source

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

Analysis of Steganography on PNG Image using Least Significant Bit (LSB), Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) [PDF]

Journal of Engineering and Applied Sciences, 2019
Priyandanu Filzasavitra, Tito Waluyo Purboyo, Randy Erfa Saputra   +2 more
openaire   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

Advanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang, Min Zhu, Wei Xiong, Si‐Wei Liu, Lu Lu   +4 more
wiley   +1 more source