An extension of min/max flow framework

In this paper, the min/max flow scheme for image restoration is revised. The novelty consists of the fol- 24 lowing three parts. The first is to analyze the reason of the speckle generation and then to modify the 25 original scheme. The second is to point out that the continued application of this scheme cannot result 26 in an adaptive stopping of the curvature flow. This is followed by modifications of the original scheme 27 through the introduction of the Gradient Vector Flow (GVF) field and the zero-crossing detector, so as 28 to control the smoothing effect. Our experimental results with image restoration show that the proposed 29 schemes can reach a steady state solution while preserving the essential structures of objects. The third is 30 to extend the min/max flow scheme to deal with the boundary leaking problem, which is indeed an 31 intrinsic shortcoming of the familiar geodesic active contour model. The min/max flow framework pro- 32 vides us with an effective way to approximate the optimal solution. From an implementation point of 33 view, this extended scheme makes the speed function simpler and more flexible. The experimental 34 results of segmentation and region tracking show that the boundary leaking problem can be effectively 35 suppressed

A Unified Pyramid Recurrent Network for Video Frame Interpolation

Flow-guide synthesis provides a common framework for frame interpolation, where optical flow is typically estimated by a pyramid network, and then leveraged to guide a synthesis network to generate intermediate frames between input frames. In this paper, we present UPR-Net, a novel Unified Pyramid Recurrent Network for frame interpolation. Cast in a flexible pyramid framework, UPR-Net exploits lightweight recurrent modules for both bi-directional flow estimation and intermediate frame synthesis. At each pyramid level, it leverages estimated bi-directional flow to generate forward-warped representations for frame synthesis; across pyramid levels, it enables iterative refinement for both optical flow and intermediate frame. In particular, we show that our iterative synthesis can significantly improve the robustness of frame interpolation on large motion cases. Despite being extremely lightweight (1.7M parameters), UPR-Net achieves excellent performance on a large range of benchmarks. Code will be available soon.Comment: arXiv admin note: text overlap with arXiv:2206.08572 by other author

Characteristics of pattern formation and evolution in approximations of physarum transport networks

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on Chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation. © 2010 Massachusetts Institute of Technology

Seismic energy envelopes in volcanic media : in need of boundary conditions

Peer reviewedPublisher PD

A Novel Diffusion-based Empirical Mode Decomposition Algorithm for Signal and Image Analysis

In the area of signal analysis and processing, the Fourier transform and wavelet transform are widely applied. Empirical Mode Decomposition(EMD) was proposed as an alternative frequency analysis tool. Although shown to be effective when analyzing non-stationary signals, the algorithmic nature of EMD makes the theoretical analysis and formulation difficult. Futhermore, it has some limitations that affect its performance. In this thesis, we introduce some methods to extend or modify EMD, in an effort to provide a rigorous mathematical basis for it, and to overcome its shortcomings. We propose a novel diffusion-based EMD algorithm that replaces the interpolation process by a diffusion equation, and directly construct the mean curve (surface) of a signal (image). We show that the new method simplifies the mathematical analysis, and provides a solid theory that interprets the EMD mechanism. In addition, we apply the new method to the 1D and 2D signal analysis showing its possible applications in audio and image signal processing. Finally, numerical experiments for synthetic and real signals (both 1D and 2D) are presented. Simulation results demonstrate that our new algorithm can overcome some of the shortcomings of EMD, and require much less computation time

Modeling single-phase flow and solute transport across scales

textFlow and transport phenomena in the subsurface often span a wide range of length (nanometers to kilometers) and time (nanoseconds to years) scales, and frequently arise in applications of CO₂ sequestration, pollutant transport, and near-well acid stimulation. Reliable field-scale predictions depend on our predictive capacity at each individual scale as well as our ability to accurately propagate information across scales. Pore-scale modeling (coupled with experiments) has assumed an important role in improving our fundamental understanding at the small scale, and is frequently used to inform/guide modeling efforts at larger scales. Among the various methods, there often exists a trade-off between computational efficiency/simplicity and accuracy. While high-resolution methods are very accurate, they are computationally limited to relatively small domains. Since macroscopic properties of a porous medium are statistically representative only when sample sizes are sufficiently large, simple and efficient pore-scale methods are more attractive. In this work, two Eulerian pore-network models for simulating single-phase flow and solute transport are developed. The models focus on capturing two key pore-level mechanisms: a) partial mixing within pores (large void volumes), and b) shear dispersion within throats (narrow constrictions connecting the pores), which are shown to have a substantial impact on transverse and longitudinal dispersion coefficients at the macro scale. The models are verified with high-resolution pore-scale methods and validated against micromodel experiments as well as experimental data from the literature. Studies regarding the significance of different pore-level mixing assumptions (perfect mixing vs. partial mixing) in disordered media, as well as the predictive capacity of network modeling as a whole for ordered media are conducted. A mortar domain decomposition framework is additionally developed, under which efficient and accurate simulations on even larger and highly heterogeneous pore-scale domains are feasible. The mortar methods are verified and parallel scalability is demonstrated. It is shown that they can be used as “hybrid” methods for coupling localized pore-scale inclusions to a surrounding continuum (when insufficient scale separation exists). The framework further permits multi-model simulations within the same computational domain. An application of the methods studying “emergent” behavior during calcite precipitation in the context of geologic CO₂ sequestration is provided.Petroleum and Geosystems Engineerin

The Ginninderra CH4 and CO2 release experiment: An evaluation of gas detection and quantification techniques

A methane (CH4) and carbon dioxide (CO2) release experiment was held from April to June 2015 at the Ginninderra Controlled Release Facility in Canberra, Australia. The experiment provided an opportunity to compare different emission quantification techniques against a simulated CH4 and CO2 point source release, where the actual release rates were unknown to the participants. Eight quantification techniques were assessed: three tracer ratio techniques (two mobile); backwards Lagrangian stochastic modelling; forwards Lagrangian stochastic modelling; Lagrangian stochastic (LS) footprint modelling; atmospheric tomography using point and using integrated line sensors. The majority of CH4 estimates were within 20% of the actual CH4 release rate (5.8 g/min), with the tracer ratio technique providing the closest estimate to both the CH4 and CO2 release rates (100 g/min). Once the release rate was known, the majority of revised estimates were within 10% of the actual release rate. The study illustrates the power of measuring the emission rate using multiple simultaneous methods and obtaining an ensemble median or mean. An ensemble approach to estimating the CH4 emission rate proved successful with the ensemble median estimate within 16% for the actual release rate for the blind release experiment and within 2% once the release rate was known. The release also provided an opportunity to assess the effectiveness of stationary and mobile ground and aerial CH4 detection technologies. Sensor detection limits and sampling rates were found to be significant limitations for CH4 and CO2 detection. A hyperspectral imager\u27s capacity to image the CH4 release from 100 m, and a Boreal CH4 laser sensor\u27s ability to track moving targets suggest the future possibility to map gas plumes using a single laser and mobile aerial reflector

A review of data mining applications in semiconductor manufacturing

The authors acknowledge Fundacao para a Ciencia e a Tecnologia (FCT-MCTES) for its financial support via the project UIDB/00667/2020 (UNIDEMI).For decades, industrial companies have been collecting and storing high amounts of data with the aim of better controlling and managing their processes. However, this vast amount of information and hidden knowledge implicit in all of this data could be utilized more efficiently. With the help of data mining techniques unknown relationships can be systematically discovered. The production of semiconductors is a highly complex process, which entails several subprocesses that employ a diverse array of equipment. The size of the semiconductors signifies a high number of units can be produced, which require huge amounts of data in order to be able to control and improve the semiconductor manufacturing process. Therefore, in this paper a structured review is made through a sample of 137 papers of the published articles in the scientific community regarding data mining applications in semiconductor manufacturing. A detailed bibliometric analysis is also made. All data mining applications are classified in function of the application area. The results are then analyzed and conclusions are drawn.publishersversionpublishe

Unraveling Recrystallization Mechanisms Governing Texture Development from Rare Earth Element Additions to Magnesium

The origin of texture components associated with rare-earth (RE) element additions in wrought magnesium (Mg) alloys is a long-standing problem in magnesium technology. The objective of this research is to identify the mechanisms accountable for rare-earth texture during dynamic recrystallization (DRX). Towards this end, we designed binary Mg-Cerium and Mg-Gadolinium alloys along with complex alloy compositions containing zinc, yttrium and Mischmetal. Binary alloys along with pure Mg were designed to individually investigate their effects on texture evolutions, while complex compositions are designed to develop randomized texture, and be used in automotive and aerospace applications. We selected indirect extrusion to thermomechanically process our materials. Different extrusion ratios and speeds were designed to produce partially and fully recrystallized microstructures, allowing us to analyze DRX from its early stages to completion. X-ray diffraction, electron backscattered diffraction (EBSD) and transmission electron microscopy (TEM) were used to conduct microstructure and texture analyses Our analyses revealed that rare-earth elements in zinc-containing magnesium alloys promote discontinuous dynamic recrystallization at the grain boundaries. During nucleation, the effect of rare earth elements on orientation selection was explained by the concomitant actions of multiple Taylor axes in the same grain. Isotropic grain growth was observed due to rare earth elements segregating to grain boundaries, which lead to texture randomization. The nucleation in binary Mg-RE alloys took place by continuous formation of necklace structures. Stochastic relaxation of basal and non-basal dislocations into lowangle grain boundaries produced chains of embryos with nearly random orientations. Schmid factor analysis showed a lower net activation of dislocations in RE textured grains compared to ones on the other side of the stereographic triangle. Lower dislocation densities within RE grains favored their growth by setting the boundary migration direction toward grains with higher dislocation density, thereby decreasing the system energy. We investigated the influence of RE elements on extension twinning induced hardening. RE addition enhanced tensile twinning induced hardening significantly. EBSD analysis illustrated that tensile twins cross low angle grain boundaries in Mg-RE alloys, which produced large twins and facilitated transmutation of basal to prismatic dislocations. Higher activity of pyramidal II dislocations in Mg-RE alloys resulted in higher twinning induced hardening