Results 61 to 70 of about 2,370 (264)
On α ̌–φ ̆-Fuzzy Contractive Mapping in Fuzzy Normed Space
The idea of fixed points represents one of the most potent mathematical tools. This paper's main purpose is to introduce a new kind of fuzzy contractive mapping in a fuzzy normed space (briefly space) namely "fuzzy contractive mapping".
Raghad I. Sabri, Buthainah A. A. Ahmed
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Low‐Power Control Of Resistance Switching Transitions in First‐Order Memristors
Joule losses are a serious concern in modern integrated circuit design. In this regard, minimizing the energy necessary for programming memristors should be handled with care. This manuscript presents an optimal control framework, allowing to derive energy‐efficient programming voltage protocols for resistance switching devices. Following this approach,
Valeriy A. Slipko +3 more
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In this paper, we introduce the concept of coincidence best proximity point for multivalued Suzuki-type α -admissible mapping using θ -contraction in b-metric space.
Naeem Saleem +3 more
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Kinetic–energetic projection of time‐resolved photoluminescence reveals that charge‐transfer injection acts as a universal bottleneck in organic solar cells. A physics‐constrained Bayesian framework identifies an emergent effective CT injection rate governing the trade‐off between charge generation and nonradiative energy loss.
Rong Wang +16 more
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A new result on Branciari metric space using (α, γ)-contractive mappings
In this work, a new common fixed point result by generalized contractive functions fulfilling the type of admissibility condition in a Hausdorff Branciari metric space with the support of C-functions, was obtained.
Patil Jayashree +4 more
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ABSTRACT Brazil and the United States account for more than 40% of global poultry exports, with China and South Korea among their major destination markets. This study examines price transmission and market linkages between Brazil and the United States using monthly poultry export price data from January 1990 to December 2024. It also assesses which of
Khondoker Abdul Mottaleb +2 more
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ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho +4 more
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Automated generative process synthesis via transformer‐based dual‐loop simulation and optimization
Abstract This study presents a novel framework for automated generative process synthesis, addressing the complexity of simultaneously optimizing discrete topologies and continuous operating variables. To overcome conventional superstructure limitations, we propose a dual‐loop architecture integrating generative transformers with rigorous process ...
Yeong Woo Son +4 more
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This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
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Coincidences for Admissible and Φ★Maps and Minimax Inequalities
AbstractA coincidence theory for Φ★and admissible maps is presented in this paper. One can also deduce from this theory new minimax inequalities of von Neumann–Sion type.
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