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Institution

Missouri University of Science and Technology

EducationRolla, Missouri, United States
About: Missouri University of Science and Technology is a education organization based out in Rolla, Missouri, United States. It is known for research contribution in the topics: Artificial neural network & Control theory. The organization has 9380 authors who have published 21161 publications receiving 462544 citations. The organization is also known as: Missouri S&T & University of Missouri–Rolla.


Papers
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Journal ArticleDOI
12 Mar 2018-Small
TL;DR: In this Review, the materials and fabrication methods to make micromodels, the main research activities that are conducted with micromadels and their applications in petroleum, geologic, and environmental engineering, as well as in the food and wood industries, are discussed.
Abstract: Complex fluid flow in porous media is ubiquitous in many natural and industrial processes. Direct visualization of the fluid structure and flow dynamics is critical for understanding and eventually manipulating these processes. However, the opacity of realistic porous media makes such visualization very challenging. Micromodels, microfluidic model porous media systems, have been developed to address this challenge. They provide a transparent interconnected porous network that enables the optical visualization of the complex fluid flow occurring inside at the pore scale. In this Review, the materials and fabrication methods to make micromodels, the main research activities that are conducted with micromodels and their applications in petroleum, geologic, and environmental engineering, as well as in the food and wood industries, are discussed. The potential applications of micromodels in other areas are also discussed and the key issues that should be addressed in the near future are proposed.

143 citations

Journal ArticleDOI
TL;DR: Data from over 200 species of migratory birds, mammals, fish, and invertebrates support the central conclusion of the model - that body size drives variation in maximum migration distance among species through its effects on metabolism and the cost of locomotion.
Abstract: Animal migration is one of the great wonders of nature, but the factors that determine how far migrants travel remain poorly understood. We present a new quantitative model of animal migration and use it to describe the maximum migration distance of walking, swimming and flying migrants. The model combines biomechanics and metabolic scaling to show how maximum migration distance is constrained by body size for each mode of travel. The model also indicates that the number of body lengths travelled by walking and swimming migrants should be approximately invariant of body size. Data from over 200 species of migratory birds, mammals, fish, and invertebrates support the central conclusion of the model - that body size drives variation in maximum migration distance among species through its effects on metabolism and the cost of locomotion. The model provides a new tool to enhance general understanding of the ecology and evolution of migration.

143 citations

Journal ArticleDOI
TL;DR: This paper derives the closed-form results on the precoding matrix, which maximizes the secrecy rate in the low signal-to-noise ratio (SNR) region, and reveal the optimal precoding structure in the high-SNR region.
Abstract: In this paper, we investigate the secrecy rate of finite-alphabet communications over multiple-input-multiple-output-multiple-antenna eavesdropper (MIMOME) channels. Traditional precoding designs based on Gaussian input assumption may lead to substantial secrecy rate loss when the Gaussian input is replaced by practical finite-alphabet input. To address this issue, we investigate linear precoding designs to directly maximize the secrecy rate for MIMOME systems under the constraint of finite-alphabet input. By exploiting the theory of Karush-Kuhn-Tucker (KKT) analysis and matrix calculus, we first present necessary conditions of the optimal precoding design when instantaneous channel-state information (CSI) of the eavesdropper is known at the transmitter. In this light, an iterative algorithm for finding the optimal precoding matrix is developed, utilizing a gradient decent method with backtracking line search. Moreover, we find that the beamforming design in MIMONE systems, which is a secrecy-capacity-achieving approach for Gaussian signaling, no longer provides the maximum secrecy rate for finite-alphabet input data. This case is substantially different from the Gaussian input case. In addition, we derive the closed-form results on the precoding matrix, which maximizes the secrecy rate in the low signal-to-noise ratio (SNR) region, and reveal the optimal precoding structure in the high-SNR region. A novel jamming signal generation method that draws on the CSI of the eavesdropper to additionally increase the secrecy rate is further proposed. The precoding design with only statistical CSI of the eavesdropper available at the transmitter is also considered. Numerical results show that the proposed designs provide significant gains over recent precoding designs through a power control policy and the precoding design with the Gaussian input assumption in various scenarios.

143 citations

Journal ArticleDOI
TL;DR: Methods for CAD model generation from digital data acquisition, motion capture, assembly modeling, human–computer interface, and data exchange between a CAD system and a VR/AR system are described.

143 citations

Journal ArticleDOI
TL;DR: A fiber-optic Fabry-Perot interferometric pressure sensor with its external diaphragm surface thinned and roughened by a femtosecond laser, which makes the sensor immune to variations in the ambient refractive index.
Abstract: In this Letter, we report on a fiber-optic Fabry-Perot interferometric pressure sensor with its external diaphragm surface thinned and roughened by a femtosecond laser. The laser-roughened surface helps to eliminate outer reflections from the external diaphragm surface and makes the sensor immune to variations in the ambient refractive index. The sensor is demonstrated to measure pressure in a high-temperature environment with low-temperature dependence.

143 citations


Authors

Showing all 9433 results

NameH-indexPapersCitations
Robert Stone1601756167901
Tobin J. Marks1591621111604
Jeffrey R. Long11842568415
Xiao-Ming Chen10859642229
Mark C. Hersam10765946813
Michael Schulz10075950719
Christopher J. Chang9830736101
Marco Cavaglia9337260157
Daniel W. Armstrong9375935819
Sajal K. Das85112429785
Ming-Liang Tong7936423537
Ludwig J. Gauckler7851725926
Rodolphe Clérac7850622604
David W. Fahey7731530176
Kai Wang7551922819
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202330
2022162
20211,047
20201,180
20191,195
20181,108