Results 61 to 70 of about 179,319 (288)

Iterative learning control for constrained linear systems [PDF]

, 2009
This paper considers iterative learning control for linear systems with convex control input constraints. First, the constrained ILC problem is formulated in a novel successive projection framework.
Chu, B., Owens, D.H.
core  

High resolution image reconstruction with constrained, total-variation minimization

, 2011
This work is concerned with applying iterative image reconstruction, based on constrained total-variation minimization, to low-intensity X-ray CT systems that have a high sampling rate.
Chartrand, Rick, Duchin, Yuval, Pan, Xiaochuan, Sidky, Emil Y., Ullberg, Christer   +4 more
core   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Strong convergence theorem of a hybrid projection algorithm for a family of quasi-ϕ-asymptotically nonexpansive mappings [PDF]

Opuscula Mathematica, 2010
The main purpose of this paper is by using a new hybrid projection iterative algorithm to prove some strong convergence theorems for a family of quasi-\(\phi\)-asymptotically nonexpansive mappings.
J. F. Tang, S. S. Chang, M. Liu, J. A. Liu   +3 more
doaj   +1 more source

Multimodal Mechanical Testing of Additively Manufactured Ti6Al4V Lattice Structures: Compression, Bending, and Fatigue

Advanced Engineering Materials, EarlyView.
In this experimental study, the mechanical properties of additively manufactured Ti‐6Al‐4V lattice structures of different geometries are characterized using compression, four point bending and fatigue testing. While TPMS designs show superior fatigue resistance, SplitP and Honeycomb lattice structures combine high stiffness and strength. The resulting
Klaus Burkart, Jonas Schmidt, Anastasiya Toenjes, Johanna Eisenträger   +3 more
wiley   +1 more source

A Relaxed Self-Adaptive Projection Algorithm for Solving the Multiple-Sets Split Equality Problem

Journal of Function Spaces, 2020
In this article, we introduce a relaxed self-adaptive projection algorithm for solving the multiple-sets split equality problem. Firstly, we transfer the original problem to the constrained multiple-sets split equality problem and a fixed point equation ...
Haitao Che, Haibin Chen
doaj   +1 more source

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Data Fusion of Objects Using Techniques Such as Laser Scanning, Structured Light and Photogrammetry for Cultural Heritage Applications

, 2015
In this paper we present a semi-automatic 2D-3D local registration pipeline capable of coloring 3D models obtained from 3D scanners by using uncalibrated images.
A Gallo, AW Fitzgibbon, DG Lowe, F Bernardini, H Lensch, HH Ip, JH Zhu, K Ikeuchi, M Callieri, M Corsini, M Dellepiane, M Dellepiane, M Pollefeys, MA Fischler, N Snavely, N Snavely, NR Pal, P Musialski, S Arya, SK Naik, Y Furukawa   +20 more
core   +3 more sources

Inertial Shrinking Projection Algorithm for Relatively Nonexpansive Mappings [PDF]

Sahand Communications in Mathematical Analysis
This paper introduces an inertial shrinking projection algorithm for approximating fixed points of relatively nonexpansive mappings in uniformly convex and smooth Banach spaces.
Sattar Alizadeh, Fridoun Moradlou
doaj   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source