Trajectory and spray control planning on unknown 3D surfaces for industrial spray painting robot

Automated 3D path and spray control planning of industrial painting robots for unknown target surfaces is desired to meet demands on the production system. In this thesis, an image acquisition and laser range scanning based method has been developed. The system utilizes the XY projection of the boundaries of the target surface to generate the gun trajectory\u27s X and Y coordinates as well as the spray control. Z coordinates and gun direction, distance, and speed are generated based on the point cloud from the target that is acquired by the laser scanner. A simulation methodology was also developed which is capable of calculating the paint thickness across the target surface. Results have shown that the generated path could perform a full coverage on the target surface, while keeping the paint material waste at the minimum. Excellent paint thickness control could be achieved on 2D and straight line sweep surfaces, while a satisfactory thickness is obtained on other 3D arbitrary surfaces. Relationships among thickness, spray deposition profile, sampling roughness and geometric features of the target surfaces have been discussed to make this method more applicable in industry

Ultrafast dynamic conductivity and scattering rate saturation of photoexcited charge carriers in silicon investigated with a midinfrared continuum probe

We employ ultra-broadband terahertz-midinfrared probe pulses to characterize the optical response of photoinduced charge-carrier plasmas in high-resistivity silicon in a reflection geometry, over a wide range of excitation densities (10^{15}-10^{19} cm^{-3}) at room temperature. In contrast to conventional terahertz spectroscopy studies, this enables one to directly cover the frequency range encompassing the resultant plasma frequencies. The intensity reflection spectra of the thermalized plasma, measured using sum-frequency (up-conversion) detection of the probe pulses, can be modeled well by a standard Drude model with a density-dependent momentum scattering time of approx. 200 fs at low densities, reaching approx. 20 fs for densities of approx. 10^{19} cm^{-3}, where the increase of the scattering rate saturates. This behavior can be reproduced well with theoretical results based on the generalized Drude approach for the electron-hole scattering rate, where the saturation occurs due to phase-space restrictions as the plasma becomes degenerate. We also study the initial sub-picosecond temporal development of the Drude response, and discuss the observed rise in the scattering time in terms of initial charge-carrier relaxation, as well as the optical response of the photoexcited sample as predicted by finite-difference time-domain simulations.Comment: 9 pages, 4 figure

Automatic Classification of Bug Reports Based on Multiple Text Information and Reports' Intention

With the rapid growth of software scale and complexity, a large number of bug reports are submitted to the bug tracking system. In order to speed up defect repair, these reports need to be accurately classified so that they can be sent to the appropriate developers. However, the existing classification methods only use the text information of the bug report, which leads to their low performance. To solve the above problems, this paper proposes a new automatic classification method for bug reports. The innovation is that when categorizing bug reports, in addition to using the text information of the report, the intention of the report (i.e. suggestion or explanation) is also considered, thereby improving the performance of the classification. First, we collect bug reports from four ecosystems (Apache, Eclipse, Gentoo, Mozilla) and manually annotate them to construct an experimental data set. Then, we use Natural Language Processing technology to preprocess the data. On this basis, BERT and TF-IDF are used to extract the features of the intention and the multiple text information. Finally, the features are used to train the classifiers. The experimental result on five classifiers (including K-Nearest Neighbor, Naive Bayes, Logistic Regression, Support Vector Machine, and Random Forest) show that our proposed method achieves better performance and its F-Measure achieves from 87.3% to 95.5%

Predicting the Number of Future Events

This paper describes prediction methods for the number of future events from a population of units associated with an on-going time-to-event process. Examples include the prediction of warranty returns and the prediction of the number of future product failures that could cause serious threats to property or life. Important decisions such as whether a product recall should be mandated are often based on such predictions. Data, generally right-censored (and sometimes left truncated and right-censored), are used to estimate the parameters of a time-to-event distribution. This distribution can then be used to predict the number of events over future periods of time. Such predictions are sometimes called within-sample predictions and differ from other prediction problems considered in most of the prediction literature. This paper shows that the plug-in (also known as estimative or naive) prediction method is not asymptotically correct (i.e., for large amounts of data, the coverage probability always fails to converge to the nominal confidence level). However, a commonly used prediction calibration method is shown to be asymptotically correct for within-sample predictions, and two alternative predictive-distributionbased methods that perform better than the calibration method are presented and justified

Strong coupling of plasmonic bright and dark modes with two eigenmodes of a photonic crystal cavity

Dark modes represent a class of forbidden transitions or transitions with weak dipole moments between energy states. Due to their low transition probability, it is difficult to realize their interaction with light, let alone achieve the strong interaction of the modes with the photons in a cavity. However, by mutual coupling with a bright mode, the strong interaction of dark modes with photons is possible. This type of mediated interaction is widely investigated in the metamaterials community and is known under the term electromagnetically induced transparency (EIT). Here, we report strong coupling between a plasmonic dark mode of an EIT-like metamaterial with the photons of a 1D photonic crystal cavity in the terahertz frequency range. The coupling between the dark mode and the cavity photons is mediated by a plasmonic bright mode, which is proven by the observation of a frequency splitting which depends on the strength of the inductive interaction between the plasmon bright and dark modes of the EIT-like metamaterial. In addition, since the plasmonic dark mode strongly couples with the cavity dark mode, we observes four polariton modes. The frequency splitting by interaction of the four modes (plasmonic bright and dark mode and the two eigenmodes of the photonic cavity) can be reproduced in the framework of a model of four coupled harmonic oscillators

Stabilizing the Oxygen Lattice and Reversible Oxygen Redox Chemistry through Structural Dimensionality in Lithium-Rich Cathode Oxides.

Lattice-oxygen redox (l-OR) has become an essential companion to the traditional transition-metal (TM) redox charge compensation to achieve high capacity in Li-rich cathode oxides. However, the understanding of l-OR chemistry remains elusive, and a critical question is the structural effect on the stability of l-OR reactions. Herein, the coupling between l-OR and structure dimensionality is studied. We reveal that the evolution of the oxygen-lattice structure upon l-OR in Li-rich TM oxides which have a three-dimensional (3D)-disordered cation framework is relatively stable, which is in direct contrast to the clearly distorted oxygen-lattice framework in Li-rich oxides which have a two-dimensional (2D)/3D-ordered cation structure. Our results highlight the role of structure dimensionality in stabilizing the oxygen lattice in reversible l-OR, which broadens the horizon for designing high-energy-density Li-rich cathode oxides with stable l-OR chemistry