Results 41 to 50 of about 7,836 (235)

Recent Progress in Memristor Array‐Based Neuromorphic Computing for on‐Chip Vector‐Matrix Multiplication

Advanced Materials Technologies, EarlyView.
Recent efforts of memristor array‐based hardware neuromorphic computing are discussed for efficient application of VMM on‐chip level in terms of circuit integration and actual application of AI algorithms. The parallel data processing principle of VMM operation is briefly reviewed, and hardware VMM is presented including convolutional transformation ...
Jingon Jang, Sang‐gyun Gi
wiley   +1 more source

TVB C++: A Fast and Flexible Back‐End for The Virtual Brain

Advanced Science, EarlyView.
TVB C++ is a streamlined and fast C++ Back‐End for The Virtual Brain (TVB), designed to make it as flexible as TVB, and FAST. Another pillar is to be fully compatible with TVB so easy bindings can be created from Python. Users can easily configure TVB C++ to execute the same code but with enhanced performance and parallelism.
Ignacio Martín, Gorka Zamora‐López, Jan Fousek, Michael Schirner, Petra Ritter, Viktor Jirsa, Gustavo Deco, Gustavo Patow   +7 more
wiley   +1 more source

Strong Proton‐Phonon Coupling Drives Fast Ion Transport in Perovskites

Advanced Science, EarlyView.
Experimental and computational phonon analysis of ABO3‐type proton conductor BaSnO3 shows that substitution on the B‐site with yttrium forms an imaginary phonon mode which is instrumental for the function as proton conductor. This overcompensates the adverse proton trapping effect of the yttrium.
Alexey Rulev, Nobumoto Nagasawa, Hongxin Wang, Vladimir Pomjakushin, Martin Kunz, Yoshitaka Yoda, Stephen P. Cramer, Qianli Chen, Artur Braun   +8 more
wiley   +1 more source

Physical Interpretation of Diffractive Optical Networks for High‐Dimensional Vortex Mode Sorting

Advanced Science, EarlyView.
The first layer‐resolved physical interpretation of diffractive optical networks trained for high‐dimensional vortex mode sorting is presented, revealing transformation division phenomena linked to saturated performance as layer numbers increase. This analysis reconciles physical theorems with network operations, enabling physics‐driven design of ...
Ruitao Wu, Juncheng Fang, Rui Pan, Rongyi Lin, Kaiyuan Li, Ting Lei, Luping Du, Xiaocong Yuan   +7 more
wiley   +1 more source

Impact of Order of Data in Word Problems on Division of a Whole into Unequal Parts

Journal on Efficiency and Responsibility in Education and Science, 2018
The paper investigates how the order of numerical data in word problems on division of a whole into unequal parts affects achievement and reasoning of 14-16-year old pupils.
Jarmila Novotná, Martin Chvál
doaj   +1 more source

Drawing a Scientific Map and Analyzing the Co-occurrence Network of Master's Dissertations and Doctoral Theses in Mathematics Education at Iranian Universities [PDF]

پژوهشنامه علم سنجی
Purpose: Studying the scientific research output of universities to identify researchers' interests and potential challenges for future research is considered a crucial endeavor.
Vahideh Soleymani Rad, Younes Karimi Fardinpour, Mohammad Hassan Behzadi, Ahmad Shahvarani Semnani   +3 more
doaj   +1 more source

Delayformer: Spatiotemporal Transformation for Predicting High‐Dimensional Dynamics

Advanced Science, EarlyView.
Delayformer introduces a multivariate spatiotemporal transformation (mvSTI) that converts observed variables into delay‐embedded states and cross‐learns their dynamics using a shared Vision Transformer encoder. This approach, grounded in dynamical systems theory, simultaneously predicts all variables in high‐dimensional systems, outperforming state‐of ...
Zijian Wang, Peng Tao, Luonan Chen
wiley   +1 more source

Examining the potential and pitfalls of AI in problem solving [PDF]

Journal of Pedagogical Research
The integration of artificial intelligence (AI) into mathematical problem-solving has shown significant potential to enhance student learning and performance.
Yasin Memiş
doaj   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source