Results 261 to 270 of about 1,011,171 (338)

Learning Crystallographic Disorder: Bridging Prediction and Experiment in Materials Discovery

Advanced Materials, EarlyView.
Machine learning based computational materials discovery workflows have recently proposed thousands of potentially stable crystalline materials. However, the experimental realization of these predictions is often challenging because the models assume perfectly ordered structures.
Konstantin S. Jakob, Aron Walsh, Karsten Reuter, Johannes T. Margraf   +3 more
wiley   +1 more source

Support Vector Machine for Stratification of Cognitive Impairment Using 3D T1WI in Patients with Type 2 Diabetes Mellitus. [PDF]

Diabetes Metab Syndr Obes
Xu Z, Zhao L, Yin L, Cao M, Liu Y, Gu F, Liu X, Zhang G.   +7 more
europepmc   +1 more source

Active Learning‐Guided Accelerated Discovery of Ultra‐Efficient High‐Entropy Thermoelectrics

Advanced Materials, EarlyView.
An active learning framework is introduced for the accelerated discovery of high‐entropy chalcogenides with superior thermoelectric performance. Only 80 targeted syntheses, selected from 16206 possible combinations, led to three high‐performance compositions, demonstrating the remarkable efficiency of data‐driven guidance in experimental materials ...
Hanhwi Jang, Wooseok Lee, Hwa‐Jung Kim, Sohyang Cha, Hosun Shin, Won Bo Lee, Min‐Wook Oh, Yeon Sik Jung, YongJoo Kim   +8 more
wiley   +1 more source

Classification of FAMACHA© Scores with Support Vector Machine Algorithm from Body Condition Score and Hematological Parameters in Pelibuey Sheep. [PDF]

Animals (Basel)
Torres-Chable OM, Tırınk C, Parra-Cortés RI, Delgado MÁG, Martínez IV, Gomez-Vazquez A, Cruz-Hernandez A, Camacho-Pérez E, Dzib-Cauich DA, Şen U, Tüfekci H, Bayyurt L, Çelik HT, Yılmaz ÖF, Chay-Canul AJ.   +14 more
europepmc   +1 more source

Ferroelectrics Hybrids: Harnessing Multifunctionality of 2D Semiconductors in the Post‐Moore Era

Advanced Materials, EarlyView.
In this Review, the state of art of ferroelectric hybrid systems—combining ferroelectrics, 2D semiconductors, and molecular switches is presented—as next‐generation platforms for high‐density, multifunctional electronics. By discussing 2D FeFET applications, nanoscale material downscaling, M3D integration, and emerging ferroelectrics, it highlights ...
Haixin Qiu, Xiaoshi Qian, Dahong Qian, Paolo Samorì   +3 more
wiley   +1 more source

An enhanced approach for predicting air pollution using quantum support vector machine. [PDF]

Sci Rep
Farooq O, Shahid M, Arshad S, Altaf A, Iqbal F, Vera YAM, Flores MAL, Ashraf I.   +7 more
europepmc   +1 more source

Sentiment Analysis of Pedulilindungi Application Reviews Using Naive Bayes Classifier and Support Vector Machine

Irfani Firdausy, Suhartono Suhartono, Mochamad Imamudin   +2 more
openalex   +2 more sources

Ion‐Regulating Membranes with Surface‐Enriched Charge Networks Enabling Stable Zinc‐Manganese Flow Batteries

Advanced Materials, EarlyView.
An ion‐regulating membrane is designed with a surface‐concentrated positively‐charged Zn2⁺ crosslinked network for zinc‐manganese flow batteries. The membrane effectively mitigates proton crossover and regulates zinc ion distribution to avoid dendrites, thus significantly improving areal capacity and prolonging the lifespan with a record accumulated ...
Jine Wu, Jiafeng Lei, Yi‐Chun Lu
wiley   +1 more source

Vision Sensor for Automatic Recognition of Human Activities via Hybrid Features and Multi-Class Support Vector Machine. [PDF]

Sensors (Basel)
Kamal S, Alhasson HF, Alnusayri M, Alatiyyah M, Aljuaid H, Jalal A, Liu H.   +6 more
europepmc   +1 more source

Analisis Sentimen dan Pemodelan Topik pada Ulasan Pengguna Aplikasi myIM3 Menggunakan Support Vector Machine dan Latent Dirichlet Allocation

Priyo Agung Prastyo, Berlilana Berlilana, Imam Tahyudin   +2 more
openalex   +2 more sources