Results 211 to 220 of about 1,306 (257)

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

open access: yesAdvanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz   +5 more
wiley   +1 more source

Transducers Across Scales and Frequencies: A System‐Level Framework for Multiphysics Integration and Co‐Design

open access: yesAdvanced Materials Technologies, EarlyView.
Transducers convert physical signals into electrical and optical representations, yet each mechanism is bounded by intrinsic trade‐offs across bandwidth, sensitivity, speed, and energy. This review maps transduction mechanisms across physical scale and frequency, showing how heterogeneous integration and multiphysics co‐design transform isolated ...
Aolei Xu   +8 more
wiley   +1 more source

Mechanical Fatigue in Liquid‐Metal Interconnects: Failure Mechanism Analysis and Validation of Improvement Strategies

open access: yesAdvanced Materials Technologies, EarlyView.
Multi‐million cycle reliability for liquid metal stretchable electronics is achieved through a continuous cycle of mechanical testing, failure mode and mechanism analysis and implementing subsequent mitigation strategies. ABSTRACT Stretchable electronics that combine mechanical compliance with reliable electrical performance are essential for ...
Lennert Purnal   +8 more
wiley   +1 more source

Problems in Finite Extremal Set Theory

open access: yesProblems in Finite Extremal Set Theory
openaire  

Extremal structure of the set of absolute norms (Noncommutative Structure in Operator Theory and its Application)

open access: yesExtremal structure of the set of absolute norms (Noncommutative Structure in Operator Theory and its Application)
openaire  

Massiveness of the sets of extremal functions in some problems in approximation theory

Ukrainian Mathematical Journal, 1993
The author establishes the existence of extremal functions for some problems in approximation theory and proves that the sets of functions of this sort are massive. His approach is based on the notions of category theory and the Baire theorem. He also considers the applications of his main result to problems in approximation theory.
V A Kofanov, Kofanov V A
exaly   +3 more sources

Extremal graph theory and finite forcibility [PDF]

open access: yesElectronic Notes in Discrete Mathematics, 2017
We study the uniqueness of optimal solutions to extremal graph theory problems. Our main result is a counterexample to the following conjecture of Lov´asz, which is often referred to as saying that “every extremal graph theory problem has a finitely ...
Andrzej Grzesik   +1 more
exaly   +2 more sources

Deep-Learning-Based Open Set Fault Diagnosis by Extreme Value Theory

IEEE Transactions on Industrial Informatics, 2022
Existing data-driven fault diagnosis methods assume that the label sets of the training data and test data are consistent, which is usually not applicable for real applications since the fault modes that occur in the test phase are unpredictable. To address this problem, open set fault diagnosis (OSFD), where the test label set consists of a portion of
Xiaolei Yu   +6 more
openaire   +1 more source

Construction of Binary Sensing Matrices Using Extremal Set Theory

IEEE Signal Processing Letters, 2017
The construction of binary sensing matrices is one of the active directions in the emerging field of compressed sensing (CS). Due to their sparse structure and competitive performance, they provide multiplier-less and faster dimensionality reduction in applications such as data compression.
R. Ramu Naidu, Chandra R. Murthy
openaire   +2 more sources

Coupling Deep Models and Extreme Value Theory for Open Set Fault Diagnosis

2020 International Conference on Sensing, Measurement & Data Analytics in the era of Artificial Intelligence (ICSMD), 2020
Existing deep-learning-based fault diagnosis methods assume that all possible fault modes are available during training process, which is sometimes not consistent with real applications. Unknown fault types may occur in the testing phase due to the fact that it is impossible to collect all the fault modes in the training phase.
Xiaolei Yu   +5 more
openaire   +1 more source

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