Results 111 to 120 of about 8,989,075 (297)

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Combined Support Vector Machine Classifier and Brain Structural Network Features for the Individual Classification of Amnestic Mild Cognitive Impairment and Subjective Cognitive Decline Patients. [PDF]

Front Aging Neurosci, 2021
Huang W, Li X, Li X, Kang G, Han Y, Shu N.   +5 more
europepmc   +1 more source

Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine [PDF]

, 2012
Machine performance degradation assessment and remaining useful life (RUL) prediction are of crucial importance in condition-based maintenance to reduce the maintenance cost and improve the reliability.
Yang, Bo-Suk, Tran, Van Tung, Pham, Hong Thom, Nguyen, Tan Tien   +3 more
core   +1 more source

“Smelltronics”—From Gas to Smell Sensing

Advanced Materials, EarlyView.
The emerging field of smelltronics, encompassing sensing technologies for complex volatile organic compounds, holds significant potential for extracting valuable chemical information. It facilitates the noninvasive, real‐time monitoring of humans, food, and the environment.
Takeshi Ono, Tsunaki Takahashi, Jiangyang Liu, Haruka Honda, Zeng Jing, Wataru Tanaka, Takuro Hosomi, Takeshi Yanagida   +7 more
wiley   +1 more source

Developing Effective Techniques for the Recognition of Shanghai Dialect Text

IEEE Access
Recognizing Shanghai dialect text is crucial for preserving local dialects, yet research on its automatic distinction from Standard Mandarin remains limited.
Yida Bao, Zheng Zhang, Mohammad Arifuzzaman, Tran Duc Le, Qi Li, Masuzyo Mwanza, Jiaqing Lin, Philippe Gaillard, Jiafeng Ye   +8 more
doaj   +1 more source

Bioinspired Adaptive Surfaces for Intelligent Liquid Manipulation: Progressing From Passive and Active to Hybrid Strategies

Advanced Materials, EarlyView.
This review examines passive, active, and hybrid liquid manipulation strategies, highlighting hybrid approaches as an emerging route to reconcile energy efficiency with adaptive control. By actively reconstructing passive surfaces to store programmable interfacial energy, hybrid systems enable flexible yet low‐power liquid transport, with perspectives ...
Jiaqi Miao, Yiyuan Zhang, Liqiu Wang, Alan C. H. Tsang   +3 more
wiley   +1 more source

Real-time flood forecasting in Amo Chhu using machine learning model and internet of things

Cogent Engineering
The proposed research aims to predict flood events in Amo Chhu river of Bhutan using machine learning and Internet of Things. The Amo Chhu River has been posing threat to the residents along river Amo Chhu, and this research seeks to improve flood ...
Khameis Mohamed Al Abdouli, Ashmita Rai, Gyesa Tenzin, Ugyen Gayleg, Nimesh Chhetri, Anju Chhetri   +5 more
doaj   +1 more source

Hydrophobic MFI‐Type Zeolites via Alkali‐Cation‐Induced Defect Healing: Implications for Adsorbent and Catalyst Design

Advanced Materials, EarlyView.
Sub‐stoichiometric amounts of Na+ or K+ enhance defect healing during Silicalite‐1 (MFI) and TS‐1 calcination by promoting Si–O–Si annealing and healing framework vacancies. The resulting defect‐free zeolites are more hydrophobic and show improved butanol/water separation and improved activity and selectivity in the epoxidation of 1‐hexene, offering a ...
Christos Kanteler, Pau Ferri, Francisco Javier Escobar‐Bedia, Álvaro Mayoral, Alejandro Vidal‐Moya, Richard Kendra, Chen Lei, Miguel Palomino, Fernando Rey, Lukáš Grajciar, Christopher James Heard, Pedro Serna, Mercedes Boronat, Cristina Martínez, Manuel Moliner   +14 more
wiley   +1 more source

TESCLA: A Fully Soft Electromagnetic Linear Actuator With Continuous Bending Enabled by Liquid‐Metal Solenoids

Advanced Materials, EarlyView.
TESCLA (tubular electromagnetic soft conformal linear actuator) combines liquid‐metal solenoids and compliant magnetic composites to achieve large‐stroke bidirectional actuation with continuous bending. Integrated inductance‐based self‐sensing enables proprioceptive position estimation without external sensors, providing a versatile platform for soft ...
Yeongjin Choi, Jeongnam Kim, Seongjun Koh, Yong‐Lae Park   +3 more
wiley   +1 more source

Clinically adaptable machine learning model to identify early appreciable features of diabetes

Intelligent Medicine
Objective Diabetes mellitus is a serious disease where the body of affected patients are failed to produce enough insulin that causes an abnormality of blood sugar.
Nurjahan Nipa, Mahmudul Hasan Riyad, Shahriare Satu, Walliullah, Koushik Chandra Howlader, Mohammad Ali Moni   +5 more
doaj   +1 more source