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.     

基于粒子系统和音频系统的烟花模拟

针对模糊物体的模拟方法存在着粒子数量绘制巨大、粒子运动状态复杂、计算耗时、实时性及逼真性不够等问题,提出了一种基于粒子系统和音频系统的烟花模拟方法,以三角形格作为绘制烟花粒子的基本图元,结合纹理映射,色彩融合技术来绘制烟花粒子,在显示列表中生成纹理,再结合FMOD引擎技术,加入音频系统,实验结果表明提出的方法增强了模拟的逼真性.     

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.     

建筑结构裂缝的图形仿真

本文从建筑结构中构件裂缝的概念和表征出发,面向图形对象建立裂缝仿真模型,并 从计算机图形学的角度,运用粘贴技术来处理裂缝图形。为了使裂缝更逼真,在知识 推理的基础上,本文运用了随机处理技术。     

Comparison between on- and off-campus behaviour and adaptability in online learning: a case from China

More and more universities and colleges are providing online courses not only for on-campus students but also for off-campus students. Tutors have to consider the differences between on- and off-campus students in order to improve effective instruction. Comparisons are made in this paper between on- and off-campus performances in online learning from four areas: learning time, path of browsing courseware, intercommunication and adaptability towards online learning. The last two areas are emphasized. Multiple approaches were adopted to collect data, which include questionnaires, posted documents, online logs, interviews and observations. This study shows that the rush time of online learning, paths of browsing courseware and favourite intercommunication means of on- and off-campus students are similar. But there are also some differences between these two groups such as competence of self-learning, enthusiasm of interpersonal exchange, dependence on tutors, feeling of learning stress, etc.     

Synthesis of Single-Crystalline Silicon Nitride Nanobelts Via Catalyst-Assisted Pyrolysis of a Polysilazane

Recently, one-dimensional nanostructures have attracted extensive attention since they are potentially important for both applications and fundamental research. In this paper, we report the synthesis of ultra-long single crystal Si₃N₄ nanobelts via catalyst-assisted pyrolysis of polymeric precursors. The obtained products contain both α- and β-Si₃N₄ nanobelts, which are 50–100 nm in thickness, 400–1000 nm in width, and a few hundreds of micrometers to several millimeters in length. Different from previous techniques for synthesizing one-dimensional structures, the current nanobelts are synthesized through confined crystallization of an amorphous phase. A solid–liquid–gas–solid reaction/crystallization growth mechanism is proposed. The formation of nanobelts instead of nanowires is attributed to the anisotropy growth at an earlier stage.