Minimum solution of a function using particle cluster optimization

2018 ◽  
Vol 11 (7) ◽  
pp. 317-323
Author(s):  
Fernando Mesa ◽  
Pedro Pablo Cardenas Alzate ◽  
Diana Marcela Devia Narvaez
Keyword(s):  
Particle Cluster ◽  
Minimum Solution ◽  
Cluster Optimization

A Proof for the Possibility of Ce-Oxide from CMP Residuals in Si-Wafers by Analytical TEM

2012 ◽  
Author(s):  
Wayne Zhao ◽  
Liem Do Thanh ◽  
Michael Gribelyuk ◽  
Mary-Ann Zaitz ◽  
Wing Lai
Keyword(s):  
Technology Development ◽  
Early Stage ◽  
Chemical Mechanical Planarization ◽  
Particle Cluster ◽  
Limited Region ◽  
Physical Evidence ◽  
Analytical Tem ◽  
Transmission Electron ◽  
Oxide Particles

Abstract Inclusion of cerium (Ce) oxide particles as an abrasive into chemical mechanical planarization (CMP) slurries has become popular for wafer fabs below the 45nm technology node due to better polishing quality and improved CMP selectivity. Transmission electron microscopy (TEM) has difficulties finding and identifying Ce-oxide residuals due to the limited region of analysis unless dedicated efforts to search for them are employed. This article presents a case study that proved the concept in which physical evidence of Ce-rich particles was directly identified by analytical TEM during a CMP tool qualification in the early stage of 20nm node technology development. This justifies the need to setup in-fab monitoring for trace amounts of CMP residuals in Si-based wafer foundries. The fact that Cr resided right above the Ce-O particle cluster, further proved that the Ce-O particles were from the wafer and not introduced during the sample preparation.

scholarly journals Optical Imaging of Magnetic Particle Cluster Oscillation and Rotation in Glycerol

2021 ◽  
Vol 7 (5) ◽  
pp. 82
Author(s):  
River Gassen ◽  
Dennis Thompkins ◽  
Austin Routt ◽  
Philippe Jones ◽  
Meghan Smith ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Magnetic Fields ◽  
Magnetic Particles ◽  
Magnetic Particle ◽  
Barium Hexaferrite ◽  
Optical Microscope ◽  
Simplified Model ◽  
Particle Cluster ◽  
Average Deviation ◽  
Cross Sectional

Magnetic particles have been evaluated for their biomedical applications as a drug delivery system to treat asthma and other lung diseases. In this study, ferromagnetic barium hexaferrite (BaFe12O19) and iron oxide (Fe3O4) particles were suspended in water or glycerol, as glycerol can be 1000 times more viscous than water. The particle concentration was 2.50 mg/mL for BaFe12O19 particle clusters and 1.00 mg/mL for Fe3O4 particle clusters. The magnetic particle cluster cross-sectional area ranged from 15 to 1000 μμm2, and the particle cluster diameter ranged from 5 to 45 μμm. The magnetic particle clusters were exposed to oscillating or rotating magnetic fields and imaged with an optical microscope. The oscillation frequency of the applied magnetic fields, which was created by homemade wire spools inserted into an optical microscope, ranged from 10 to 180 Hz. The magnetic field magnitudes varied from 0.25 to 9 mT. The minimum magnetic field required for particle cluster rotation or oscillation in glycerol was experimentally measured at different frequencies. The results are in qualitative agreement with a simplified model for single-domain magnetic particles, with an average deviation from the model of 1.7 ± 1.3. The observed difference may be accounted for by the fact that our simplified model does not include effects on particle cluster motion caused by randomly oriented domains in multi-domain magnetic particle clusters, irregular particle cluster size, or magnetic anisotropy, among other effects.

scholarly journals An Inverse Node Graph-Based Method for the Urban Scene Segmentation of 3D Point Clouds

2021 ◽  
Vol 13 (15) ◽  
pp. 3021
Author(s):  
Bufan Zhao ◽  
Xianghong Hua ◽  
Kegen Yu ◽  
Xiaoxing He ◽  
Weixing Xue ◽  
...  
Keyword(s):  
Semantic Segmentation ◽  
Point Clouds ◽  
Intelligent Vehicles ◽  
Critical Data ◽  
Multi Scale ◽  
3D Point Clouds ◽  
Cluster Optimization ◽  
Urban Scene ◽  
Processing Steps

Urban object segmentation and classification tasks are critical data processing steps in scene understanding, intelligent vehicles and 3D high-precision maps. Semantic segmentation of 3D point clouds is the foundational step in object recognition. To identify the intersecting objects and improve the accuracy of classification, this paper proposes a segment-based classification method for 3D point clouds. This method firstly divides points into multi-scale supervoxels and groups them by proposed inverse node graph (IN-Graph) construction, which does not need to define prior information about the node, it divides supervoxels by judging the connection state of edges between them. This method reaches minimum global energy by graph cutting, obtains the structural segments as completely as possible, and retains boundaries at the same time. Then, the random forest classifier is utilized for supervised classification. To deal with the mislabeling of scattered fragments, higher-order CRF with small-label cluster optimization is proposed to refine the classification results. Experiments were carried out on mobile laser scan (MLS) point dataset and terrestrial laser scan (TLS) points dataset, and the results show that overall accuracies of 97.57% and 96.39% were obtained in the two datasets. The boundaries of objects were retained well, and the method achieved a good result in the classification of cars and motorcycles. More experimental analyses have verified the advantages of the proposed method and proved the practicability and versatility of the method.

scholarly journals Vector variational inequalities and their relations with vector optimization

2013 ◽  
Vol 4 (1) ◽  
pp. 35-44 ◽  
Author(s):  
Surjeet Kaur Suneja ◽  
Bhawna Kohli
Keyword(s):  
Variational Inequalities ◽  
Vector Optimization ◽  
Optimization Problem ◽  
Vector Optimization Problem ◽  
Clarke Subdifferential ◽  
Vector Variational Inequalities ◽  
Regularity Assumption ◽  
Weak Minimum ◽  
Minimum Solution ◽  
Clarke Subdifferentials

In this paper, K- quasiconvex, K- pseudoconvex and other related functions have been introduced in terms of their Clarke subdifferentials, where   is an arbitrary closed convex, pointed cone with nonempty interior. The (strict, weakly) -pseudomonotonicity, (strict) K- naturally quasimonotonicity and K- quasimonotonicity of Clarke subdifferential maps have also been defined. Further, we introduce Minty weak (MVVIP) and Stampacchia weak (SVVIP) vector variational inequalities over arbitrary cones. Under regularity assumption, we have proved that a weak minimum solution of vector optimization problem (VOP) is a solution of (SVVIP) and under the condition of K- pseudoconvexity we have obtained the converse for MVVIP (SVVIP). In the end we study the interrelations between these with the help of strict K-naturally quasimonotonicity of Clarke subdifferential map.

A hybrid regularization scheme for the inversion of magnetotelluric data from natural and controlled sources to layer and distortion parameters

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. E301-E315 ◽  
Author(s):  
Thomas Kalscheuer ◽  
Juliane Hübert ◽  
Alexey Kuvshinov ◽  
Tobias Lochbühler ◽  
Laust B. Pedersen
Keyword(s):  
Transfer Functions ◽  
Homogeneous Distribution ◽  
Stable Configuration ◽  
Inversion Algorithm ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Near Surface ◽  
Minimum Solution ◽  
Magnetic Transfer ◽  
Distortion Parameters

Magnetotelluric (MT), radiomagnetotelluric (RMT), and, in particular, controlled-source audiomagnetotelluric (CSAMT) data are often heavily distorted by near-surface inhomogeneities. We developed a novel scheme to invert MT, RMT, and CSAMT data in the form of scalar or tensorial impedances and vertical magnetic transfer functions simultaneously for layer resistivities and electric and magnetic galvanic distortion parameters. The inversion scheme uses smoothness constraints to regularize layer resistivities and either Marquardt-Levenberg damping or the minimum-solution length criterion to regularize distortion parameters. A depth of investigation range is estimated by comparing layered model sections derived from first- and second-order smoothness constraints. Synthetic examples demonstrate that earth models are reconstructed properly for distorted and undistorted tensorial CSAMT data. In the inversion of scalar CSAMT data, such as the determinant impedance or individual tensor elements, the reduced number of transfer functions inevitably leads to increased ambiguity for distortion parameters. As a consequence of this ambiguity for scalar data, distortion parameters often grow over the iterations to unrealistic absolute values when regularized with the Marquardt-Levenberg scheme. Essentially, compensating relationships between terms containing electric and/or magnetic distortion are used in this growth. In a regularization with the minimum solution length criterion, the distortion parameters converge into a stable configuration after several iterations and attain reasonable values. The inversion algorithm was applied to a CSAMT field data set collected along a profile over a tunnel construction site at Hallandsåsen, Sweden. To avoid erroneous inverse models from strong anthropogenic effects on the data, two scalar transfer functions (one scalar impedance and one scalar vertical magnetic transfer function) were selected for inversion. Compared with a regularization of distortion parameters with the Marquardt-Levenberg method, the minimum-solution length criterion yielded smaller absolute values of distortion parameters and a horizontally more homogeneous distribution of electrical conductivity.

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