CAN总线网络测试研究

介绍了CAN总线网络开发方法,搭建了CAN总线集成开发测试环境,对实际网络进行了测试,给出了位定时参数计算方法,比较了不同模拟终端电阻下的总线的报文正确率和总线负载率等性能指标.     

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.     

Guanxi Networks and Creativity in Taiwanese Project Teams

Personal connections, also called guanxi in Chinese culture, are embedded within a network of interdependent social exchanges, providing access to resources, information and supports, therefore facilitating performance. Building guanxi networks means building social networks. Project teams are commonly used as fundamental units in organizations, partly in order to generate more creative ideas, and so this paper evaluates how project teams use their guanxi networks within and outside of their teams and across boundaries to stimulate their creative performance. Fifty‐four product development project teams with 293 members from high‐tech Taiwanese firms participated in this study. Findings suggested that, in a guanxi culture such as Taiwan's, in order to facilitate a project team's creative performance, the most important task is to develop a more cohesive social unit before the team extends its external networks, since Chinese culture regards people first as members of groups, and secondly as individuals.     

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.     

Discriminant subspace analysis: a Fukunaga-Koontz approach

The Fisher Linear Discriminant (FLD) is commonly used in pattern recognition. It finds a linear subspace that maximally separates class patterns according to the Fisher Criterion. Several methods of computing the FLD have been proposed in the literature, most of which require the calculation of the so-called scatter matrices. In this paper, we bring a fresh perspective to FLD via the Fukunaga-Koontz Transform (FKT). We do this by decomposing the whole data space into four subspaces with different discriminability, as measured by eigenvalue ratios. By connecting the eigenvalue ratio with the generalized eigenvalue, we show where the Fisher Criterion is maximally satisfied. We prove the relationship between FLD and FKT analytically, and propose a unified framework to understanding some existing work. Furthermore, we extend our our theory to Multiple Discriminant Analysis (MDA). This is done by transforming the data into intra- and extra-class spaces, followed by maximizing the Bhattacharyya distance. Based on our FKT analysis, we identify the discriminant subspaces of MDA/FKT, and propose an efficient algorithm, which works even when the scatter matrices are singular, or too large to be formed. Our method is general and may be applied to different pattern recognition problems. We validate our method by experimenting on synthetic and real data.     

Neuroproteomics and its applications in research on nicotine and other drugs of abuse

The rapidly growing field of neuroproteomics is able to track changes in protein expression and protein modifications underlying various physiological conditions, including the neural diseases related to drug addiction. Thus, it presents great promise in characterizing protein function, biochemical pathways, and networks to understand the mechanisms underlying drug dependence. In this article, we first provide an overview of proteomics technologies and bioinformatics tools available to analyze proteomics data. Then we summarize the recent applications of proteomics to profile the protein expression pattern in animal or human brain tissues after the administration of nicotine, alcohol, amphetamine, butorphanol, cocaine, and morphine. By comparing the protein expression profiles in response to chronic nicotine exposure with those appearing in response to treatment with other drugs of abuse, we identified three biological processes that appears to be regulated by multiple drugs of abuse: energy metabolism, oxidative stress response, and protein degradation and modification. Such similarity indicates that despite the obvious differences among their chemical properties and the receptors with which they interact, different substances of abuse may cause some similar changes in cellular activities and biological processes in neurons.     

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.     

土石坝浇筑式沥青混凝土防渗心墙施工新技术的应用

随着我国大中小型水利水电工程的不断发展,土石坝浇筑式沥青混凝土防渗心墙施工新技术得以广泛推广和应用,既消除了传统混凝土工程中的分层离析现象,既提高了混凝土整体的均匀性,又可以保证混凝土防渗心墙的可靠性与安全性。本文针对土石坝浇筑式沥青混凝土防渗心墙施工新技术的研究与应用作了四个方面的探讨。