Missouri University of Science and Technology

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.

Social Network Structures in Open Source Software Development Teams

Abstract: Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a core/periphery model as the projects move forward.

Magnesium-doped lithium niobate for higher optical power applications

Abstract: Compositions of lithium niobate containing 4.5 at.% or more MgO have the ability to transmit, without distortion, light 100 times as intense as undopecl compositions. Holographic diffraction measurements of photorefraction have demonstrated that the improved performance is due to a hundredfold increase in the photoconductivity, rather than to a decrease in the Glass current. The damage-resistant compositions are also distinguished by a thermal activation energy of 0.1 eV for the diffraction efficiency, an OH-stretch vibration at 2.83 Am, a lattice phonon absorption at 21.2 Am, an electron spin resonance signal for Fe impurities at 1500 G, and, after reduction by heating in a vacuum, an optical absorption band at 1.2 um. (The corresponding values for undopedl LiNbO3 are 0.5 eV, 2.87 um, 21.8 um, 790 G, and 0.5 um, respectively.) The high photoconductivity is thus related to a distinctive electronic environment for impurities in the damage-resistant crystals. The photoconductivity strongly affects the impedance and time constants of signal processing devices made of LiNbO3.

Opportunistic scheduling for robotic assembly

Abstract: Impressive strides have been made in dealing with the spatial complexity of robotic assembly tasks. Unfortunately, advances in dealing with temporal complexity have not kept pace. It is proposed that one reason for this deficiency is the unnecessary confounding of planning and scheduling. These two activities are differentiated on the basis of knowledge required/knowledge available at robot programming time. It is suggested that giving the robot the ability to reason opportunistically over knowledge of part availability at run time is a practical, efficient way to streamline assembly tasks. Initial experimental results are presented to substantiate this conclusion.

Neural Network Control of Mobile Robot Formations Using RISE Feedback

Abstract: In this paper, an asymptotically stable (AS) combined kinematic/torque control law is developed for leader-follower-based formation control using backstepping in order to accommodate the complete dynamics of the robots and the formation, and a neural network (NN) is introduced along with robust integral of the sign of the error feedback to approximate the dynamics of the follower as well as its leader using online weight tuning. It is shown using Lyapunov theory that the errors for the entire formation are AS and that the NN weights are bounded as opposed to uniformly ultimately bounded stability which is typical with most NN controllers. Additionally, the stability of the formation in the presence of obstacles is examined using Lyapunov methods, and by treating other robots in the formation as obstacles, collisions within the formation do not occur. The asymptotic stability of the follower robots as well as the entire formation during an obstacle avoidance maneuver is demonstrated using Lyapunov methods, and numerical results are provided to verify the theoretical conjectures.