Results 41 to 50 of about 56,385 (212)

Real‐Time High‐Definition Hyperspectral Endoscopy via Spatial‐Temporal Low‐Frequency‐Stochastic Spectral Encoding

Advanced Science, EarlyView.
A real‐time, high‐definition hyperspectral endoscopy is enabled by developing a spatial‐temporal spectral encoding approach based on low‐frequency stochastic filters combined with an encoding‐guided attention network. It provides hyperspectral image of in vivo tissue with fine superficial features, enables visualization of rapid and subtle ...
Xiaowei Liu, Jiakang Shao, Julin Xiao, Chenying Yang, Jiahe Zhang, Xiaoyu Yang, Xiang Hao, Ying Gu, Xu Liu, Yizhou Tan, Ji Qi, Qing Yang   +11 more
wiley   +1 more source

A Review of Financial Accounting Fraud Detection based on Data Mining Techniques

, 2012
With an upsurge in financial accounting fraud in the current economic scenario experienced, financial accounting fraud detection (FAFD) has become an emerging topic of great importance for academic, research and industries.
Panigrahi, Prabin Kumar, Sharma, Anuj
core   +1 more source

Probabilistic Modeling for Prediction Errors to Enhance Balancing Market Participation of Photovoltaic Systems: Error Threshold Estimation, Multisite Aggregation, and Overloading Effects

Advanced Energy and Sustainability Research, EarlyView.
This study proposes a method to increase the value of solar power in balancing markets by managing prediction errors. The approach models prediction uncertainties and quantifies reserve requirements based on a probabilistic model. This enables the more reliable participation of photovoltaic plants in balancing markets across multiple sites, especially ...
Jindan Cui, Xue Fang, Takashi Oozeki, Yuzuru Ueda   +3 more
wiley   +1 more source

Traceability of Agri‐Food Products: The Key to Conscious Trade

Agribusiness, EarlyView.
ABSTRACT Globalization and growing concerns about sustainability have led to improvements in product traceability, quality, and sustainability. Traceability contributes to environmental protection and supports sustainable development by fostering transparency in agricultural practices and encouraging the responsible use of resources.
Scarlett Queen Almeida Bispo, Fernanda Aparecida Silva, Michelle Márcia Viana Martins, Marcelo José Braga Nonnenberg, Ruan da Silva Vianna, Carla Cristina Passos Cruz   +5 more
wiley   +1 more source

Artificial Intelligence‐Driven Insights into Electrospinning: Machine Learning Models to Predict Cotton‐Wool‐Like Structure of Electrospun Fibers

Advanced Intelligent Discovery, EarlyView.
Electrospinning allows the fabrication of fibrous 3D cotton‐wool‐like scaffolds for tissue engineering. Optimizing this process traditionally relies on trial‐and‐error approaches, and artificial intelligence (AI)‐based tools can support it, with the prediction of fiber properties. This work uses machine learning to classify and predict the structure of
Paolo D’Elia, Giovanna Pappalardo, Aldo R. Boccaccini, Liliana Liverani   +3 more
wiley   +1 more source

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, EarlyView.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

A unified representation of conditioning rules for convex capacities [PDF]

This paper proposes a unified representation, called the G-updating rule, which includes three conditioning rules as special cases, the naïve Bayes rule, the Dempster-Shafer rule (Shafer(1976)), and the generalized Bayes' updating rule introduced by ...
Mayumi Horie
core  

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 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

Minimum information loss fusion in distributed sensor networks [PDF]

, 2016
A key assumption of distributed data fusion is that individual nodes have no knowledge of the global network topology and use only information which is available locally.
Clarke, D
core