Results 111 to 120 of about 76,641 (279)

Effects of Computer Assistive Technology on the Mathematics Achievement of Pupils with Visual Impairment in Otana Integrated School Jos, Plateau State

Journal of African Innovation and Advanced Studies
This research study was conducted to investigate the effects of computer assistive technology on mathematics achievement of pupils with visual impairment in Otana Integrated School Jos, Plateau State. This researcher study adopts the pre-test post-test experimental research design.
null Nankling Pankyes Tanko, null Pirman Nimmak   +1 more
openaire   +1 more source

Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials

Advanced Intelligent Discovery, EarlyView.
In this study we employed support vector regressor and quantum support vector regressor to predict the hydrogen storage capacity of metal–organic frameworks using structural and physicochemical descriptors. This study presents a comparative analysis of classical support vector regression (SVR) and quantum support vector regression (QSVR) in predicting ...
Chandra Chowdhury
wiley   +1 more source

Analysis of Transmission Dynamics and Control of Strongyloides Stercoralis using Mathematical Modeling in Pankshin Local Government Area of Plateau State, Nigeria

African Journal of Biology and Medical Research
Strongyloides stercoralis infection is common among children living in rural areas in developing countries especially in sub-Saharan Africa with serious public health significance. This study presents a mathematical modeling and analysis of transmission dynamics and control of Strongyloides stercoralis in Pankshin Local Government Area of Plateau State,
Ezema, M. A., Sangari, J. S., Chukwudike, C. O., Maduagwu, C. Q.   +3 more
openaire   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

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

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends

Environmental Research Letters, 2015
We examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982 to 2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models.
Jiafu Mao, Wenting Fu, Xiaoying Shi, Daniel M Ricciuto, Joshua B Fisher, Robert E Dickinson, Yaxing Wei, Willis Shem, Shilong Piao, Kaicun Wang, Christopher R Schwalm, Hanqin Tian, Mingquan Mu, Altaf Arain, Philippe Ciais, Robert Cook, Yongjiu Dai, Daniel Hayes, Forrest M Hoffman, Maoyi Huang, Suo Huang, Deborah N Huntzinger, Akihiko Ito, Atul Jain, Anthony W King, Huimin Lei, Chaoqun Lu, Anna M Michalak, Nicholas Parazoo, Changhui Peng, Shushi Peng, Benjamin Poulter, Kevin Schaefer, Elchin Jafarov, Peter E Thornton, Weile Wang, Ning Zeng, Zhenzhong Zeng, Fang Zhao, Qiuan Zhu, Zaichun Zhu   +40 more
doaj   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Genome-wide association analysis and transgenic characterization for amylose content regulating gene in tuber of Dioscorea zingiberensis

BMC Plant Biology
Background Amylose, a prebiotic found in yams is known to be beneficial for the gut microflora and is particularly advantageous for diabetic patients’ diet. However, the genetic machinery underlying amylose production remains elusive.
Shixian Sun, Binbin Guan, Yue Xing, Xiang Li, Lanlan Liu, Yanmei Li, Lu Jia, Shili Ye, Komivi Dossa, Li Zheng, Yunpeng Luan   +10 more
doaj   +1 more source

QS4D: Quantization‐Aware Training for Efficient Hardware Deployment of Structured State‐Space Sequential Models

Advanced Intelligent Systems, EarlyView.
Quantization‐aware training creates resource‐efficient structured state space sequential S4(D) models for ultra‐long sequence processing in edge AI hardware. Including quantization during training leads to efficiency gains compared to pure post‐training quantization.
Sebastian Siegel, Ming‐Jay Yang, Younes Bouhadjar, Maxime Fabre, Emre Neftci, John Paul Strachan   +5 more
wiley   +1 more source