Physics-Informed Multistage Machine Learning Strategy for the Nanomachining-Induced Plastic Deformation Behavior

The evolution of the dislocation density induced by the nanomachining process dominates the plastic deformation behaviors of materials, thus affecting the mechanical properties significantly. However, a challenging topic related to how to establish an accurate model for predicting the dislocation density based on the limited simulations and experiments arises due to the complicated thermal–mechanical coupling mechanism during the machining process. Herein, a multistage method integrating machine learning, physics, and high-throughput atomic simulation is proposed to investigate the effect of cutting speed on the dislocation behavior in polycrystal copper. Compared with the traditional one-step machine learning method, the constraint of physical features effectively improves the accuracy and generalization ability of the model. The results indicate that the dislocation behaviors depend on the competition between the cutting force and temperature. In the low-cutting speed, the predominated role of the cutting temperature leads to a rapid decline of the dislocation density. In contrast, the dislocation density tends to be stable under a high-speed cutting process due to the dynamic balance between the effects of the cutting force and temperature. Notably, the proposed strategy provides a new and universal framework to design the machining parameters to obtain high-quality products.     

Steady-state limiting currents determined by coupled diffusion, migration, and chemical equilibrium

A simple theoretical model is presented for the reduction of a singly charged cation under conditions where migration is important and the cation is coupled to a neutral species through a chemical equilibrium, AB = A(+) + B(-). Only the steady-state transport-limited current, I(l), is considered. Simple algebraic equations describe the ratio of I(l) to the diffusion-limited current, I(d), as it depends on the degree of dissociation, determined by the ratio of equilibrium constant to formal concentration, K(AB)/C*(AB). The ratio I(l)/I(d) is found to depend on the ratio of electrolyte to equilibrium concentration of A(+) in bulk solution just as for the well-known result for the case without the equilibrium (i.e., K(AB) → ∞). The results are in accord with published experimental data for weak acids. Agreement and disagreement with other theoretical treatments of this problem are discussed. The main results are for 1:1 supporting electrolytes; extensions are made to 2:1, 1:2, and 2:2 supporting electrolytes.     

Research on the group decision-making about emergency event based on network technology

In order to improve decision-making efficiency about emergency event, this paper proposes a novel concept, i.e., Agile-Delphi Method, which is an integration of agile decision and Delphi Method implicating that the decision-makers instantly deliver, respond, treat, and utilize information via Delphi process while conducting group decision-making about emergency event. The paper details the mechanism of group decision-making about emergency event based on network technology and Agile-Delphi Method. Finally, the paper conducts an empiric analysis taking the “111 event”, i.e., the liquid ammonia spill event happened on November 1, 2006 in a phosphorus chemical company in China, as an example.     

Interactive surgery simulation for the nose augmentation using CT data

Surgery to reshape the nose with an implant has been a regular procedure for enhancing a patient’s appearance and self-confidence. The purpose of this study was to establish a computed tomography (CT) based three-dimensional assistant plastic surgery systems, which can provide the patients with realistic prediction of their own postoperative appearance in computer and specifically produce a nose implant for an individual patient. Preoperative CT data and 3D reconstruction techniques were employed to generate 3D model of the patient’s skull. 3D collision detection and finite elements model deformation were then applied to simulate nose augmentation surgery and predict postoperative appearance. According to the patient’s expectation, digital models of the nose implants were constantly modified. When the patient is satisfied with the simulated results, custom made silicone implants were produced by a computer controlled device. Accurately regeneration of 3D images and realistic operative simulations could be achieved with this system. The implants produced exactly conformed to the results of simulation. No curving and reshaping were needed during operating. The clinical results extremely matched with the simulations. The system enhances surgeon patient communication and facilitates preoperative planning. It is especially desirable for implant surgery with less guesswork of size, contour, and orientation of the implant. The best chance of optimal results could be achieved.     

Evaluation of Landsat 8 OLI imagery for unsupervised inland water extraction

The successful launch of the Landsat 8 satellite continues the Earth observation of the Landsat series, which has been taking place for nearly 40 years. With the increase in the band number and the improved spectral range compared with the previous Landsat imagery, it will be possible to expand the application of the new Landsat 8 imagery. The purpose of this study is to explore water extraction based on the new Landsat 8 Operational Land Imager (OLI) imagery. According to the specific inland water conditions (clear water, turbid water, and eutrophic water), a number of highly adaptable water indices are assessed for water extraction using Landsat OLI imagery. The results show that clear water is the easiest to extract among the different types of waterbodies, with the highest average accuracy of 97%. The highest-accuracy methods are the automated water extraction index for shadow pixels (AWEI_sh), the normalized difference water index using bands 4 and 7 (NDWI₄₇), and the normalized difference water index using bands 3 and 7 (NDWI₃₇), with accuracies of 98.55%, 95.50%, and 96.61%, corresponding to clear water, turbid water, and eutrophic water, respectively. Through the analysis of the different methods for optimal band selection, the seventh band OLI7 (shortwave infrared 2, SWIR-2) of Landsat OLI shows the best performance in water identification. When applying the water indices to water extraction, Otsu’s algorithm has been used to automatically select the water threshold. Using extensive experiments with Otsu’s algorithm and a manual method, it was found that Otsu’s algorithm can replace manual selection and has the ability to select an accurate threshold for water extraction.     

Activity recognition and intensity estimation in youth from accelerometer data aided by machine learning

Physical activity monitoring for youth is an area of increasing scientific and public health interest due to the high prevalence of obesity and downward trend in physical activity. However, accurate assessment of such activity remains a challenging problem because of the complex nature in which certain activities are performed. In this study, we formulated the issue as a machine learning problem—using a diverse set of 19 physical activities commonly performed by youth—via two approaches: activity recognition and intensity estimation. With the aid of training data, we implemented a distance metric learning method called DML-KNN that utilizes time-frequency features and is capable of effectively classifying both continuous and intermittent movement in youth subjects. Four different time-frequency feature extraction methods were then systematically evaluated. Our results show that the DML-KNN method performed competitively, especially when using features extracted by the Tamura method for intensity estimation, and by the Square Coefficient method for activity recognition.     

Surface tension calculation of the Ni3S2---FeS---Cu2S mattes

The surface tension of the Ni₃S₂-FeS-Cu₂S ternary mattes have been calculated from those of the Ni₃S₂-FeS·FeS-Cu₂S and Cu₂S-Ni₃S₂ pseudo-binary boundary systems by using geometric models (Kohler and Toop model) and a general solution model (Chou model). Taking account of the experimental accuracy of ±2.5%, the respective calculated results are in agreement with the experimental data. At the same time, surface tensions of molten Ni₃S₂-FeS-Cu₂S mattes and their pseudo-binary boundary systems are predicted based on Butler's original treatment with great attention to the model parameter β. The predicted results also agree with the experimental data. Therefore, the resulting iso-surface tension curves in molten Ni₃S₂-FeS-Cu₂S mattes at 1473K, especially calculated by using Kohler, Toop and Chou models, are generally acceptable.     

基于双链式存储的可靠通信网合并

本文介绍图的双链式存储结构在可靠通讯网合并算法中的应用.