Results 101 to 110 of about 24,937 (297)
The minimizer of the sum of two strongly convex functions
The optimization problem concerning the determination of the minimizer for the sum of convex functions holds significant importance in the realm of distributed and decentralized optimization. In scenarios where full knowledge of the functions is not available, limiting information to individual minimizers and convexity parameters – either due to ...
Kuwaranancharoen, Kananart +1 more
openaire +2 more sources
On a problem connected with strongly convex functions [PDF]
Summary: In this paper we show that the result obtained by \textit{K. Nikodem} and \textit{Z. Páles} [Banach J. Math. Anal. 5, No. 1, 83--87 (2011; Zbl 1215.46016)] can by extended to a more general case. In particular, for a non-negative function \(F\) defined on a real vector space we define \(F\)-strongly convex functions and show that such ...
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This review explores advances in wearable and lab‐on‐chip technologies for breast cancer detection. Covering tactile, thermal, ultrasound, microwave, electrical impedance tomography, electrochemical, microelectromechanical, and optical systems, it highlights innovations in flexible electronics, nanomaterials, and machine learning.
Neshika Wijewardhane +4 more
wiley +1 more source
Recent Advances of Slip Sensors for Smart Robotics
This review summarizes recent progress in robotic slip sensors across mechanical, electrical, thermal, optical, magnetic, and acoustic mechanisms, offering a comprehensive reference for the selection of slip sensors in robotic applications. In addition, current challenges and emerging trends are identified to advance the development of robust, adaptive,
Xingyu Zhang +8 more
wiley +1 more source
When is the inverse of an invertible convex function itself convex? [PDF]
We provide a sufficient condition for an invertible (locally strongly) convex vector-valued function on RN to have a (locally strongly) convex inverse. We show under suitable conditions that if the gradient of each component of the inverse has negative ...
Planque, Bob
core +1 more source
Refinements of Some Integral Inequalities for φ-Convex Functions
In this paper, we are interested to deal with unified integral operators for strongly φ-convex function. We will present refinements of bounds of these unified integral operators and use them to get associated results for fractional integral operators ...
Moquddsa Zahra +2 more
doaj +1 more source
Laser‐assisted synthesis enables rapid (within 1 h) and high‐yield (≥90%) production of Co‐MOFs with mesoporous structures, tunable magnetic and optical properties, and efficient adsorption of N2, CH4, and CO2 for low‐energy gas separation. DFT calculations elucidate the electronic structure and adsorption behavior.
Saliha Mutlu +10 more
wiley +1 more source
Some New Improvements of Hermite-Hadamard Type Inequalities Using Strongly $(s,m)$-Convex Function with Applications [PDF]
The trapezoidal-type inequalities are discovered in this study using the fractional operator, which produces powerful results. We established a general identity for Caputo-Fabrizio integral operators and the second derivative function.
Arslan Munir +5 more
doaj +1 more source
A Pressure Microsensor Made of Parylene‐C for Use as Medical Implant
A monolithic parylene‐C pressure sensor with gold strain gauges provides 6.2 μV$\mu{\rm V}$·mmHg$\cdot{\rm mmHg}$−1$^{-1}$ sensitivity. The morphology of a sputtered thin film strain sensor is granular/columnar, which results in a high gauge factor of 7.5. Thermal bonding and parylene‐C coating create a hermetic cavity.
Ann‐Kathrin Klein +2 more
wiley +1 more source
When is the inverse of an invertible convex function itself convex?
We provide a sufficient condition for an invertible (locally strongly) convex vector-valued function on $\mathbb{R}^N$ to have a (locally strongly) convex inverse.
Planqué, Robert
core

