Fast human activity recognition based on structure and motion

We present a method for the recognition of human activities. The proposed approach is based on the construction of a set of templates for each activity as well as on the measurement of the motion in each activity. Templates are designed so that they capture the structural and motion information that is most discriminative among activities. The direct motion measurements capture the amount of translational motion in each activity. The two features are fused at the recognition stage. Recognition is achieved in two steps by calculating the similarity between the templates and motion features of the test and reference activities. The proposed methodology is experimentally assessed and is shown to yield excellent performance.     

3D-QSAR and molecular docking studies of selective agonists for the thyroid hormone receptor beta

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed using comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA) on a series of agonists of thyroid hormone receptor beta (TRbeta), which may lead to safe therapies for non-thyroid disorders while avoiding the cardiac side effects. The reasonable q(2) (cross-validated) values 0.600 and 0.616 and non-cross-validated r(2) values of 0.974 and 0.974 were obtained for CoMFA and CoMSIA models for the training set compounds, respectively. The predictive ability of two models was validated using a test set of 12 molecules which gave predictive correlation coefficients (r(pred)(2)) of 0.688 and 0.674, respectively. The Lamarckian Genetic Algorithm (LGA) of AutoDock 4.0 was employed to explore the binding mode of the compound at the active site of TRbeta. The results not only lead to a better understanding of interactions between these agonists and the thyroid hormone receptor beta but also can provide us some useful information about the influence of structures on the activity which will be very useful for designing some new agonist with desired activity.     

An adaptive model-free resource and power management approach for multi-tier cloud environments

With the development of cloud environments serving as a unified infrastructure, the resource management and energy consumption issues become more important in the operations of such systems. In this paper, we investigate adaptive model-free approaches for resource allocation and energy management under time-varying workloads and heterogeneous multi-tier applications. Specifically, we make use of measurable metrics, including throughput, rejection amount, queuing state, and so on, to design resource adjustment schemes and to make control decisions adaptively. The ultimate objective is to guarantee the summarized revenue of the resource provider while saving energy and operational costs. To validate the effectiveness, performance evaluation experiments are performed in a simulated environment, with realistic workloads considered. Results show that with the combination of long-term adaptation and short-term adaptation, the fluctuation of unpredictable workloads can be captured, and thus the total revenue can be preserved while balancing the power consumption as needed. Furthermore, the proposed approach can achieve better effect and efficiency than the model-based approaches in dealing with real-world workloads.     

Procedural models for cartoon cracks and fractures animations

We present an approach for animating cracks and fractures in cartoon style. In our method we take a 2D hand-drawn object as input and then construct a 2.5D model of the object in order to approximate the object volume. Next, we generate the Voronoi textures on the 2.5D object model for visual abstraction of cartoon cracks. Further, cracking gaps on the Voronoi textures are widened progressively until Voronoi cells split apart and finally fall onto ground according to simplified physical rules. With minimum user intervention, our model is able to generate cartoon cracks and fractures animations procedurally, as demonstrated by examples given in the paper.     

Model test of helical angle effect on coal loading performance of shear drum

The work presented in this paper focuses on improving coal loading performance of shear drum.Employing the similarity theory,we carried out a dimensional analysis of the correlation parameters which in...     

乙烯装置裂解气分馏及冷却的模拟计算

对于含有众多复什碳氢化合物的裂解汽油、裂解柴油和裂解燃料油等宽馏分以及氢、轻烃、大量水分的裂解气，采用虚拟组分以减少组分总数、用惰性气体描述水在烃类中的相行为，以物流混合和闪蒸过程组成一个闪蒸平衡级，并以逐级闪蒸计算来描述乙烯装置的裂解气分馏塔。     

全电动注塑机的特点及应用领域

重点分析了全电动注塑机与全液压注塑机的不同之处,简单地概述了国内塑料工业发展落后的现状以及把我国建成注塑机生产强国的突破口。详细介绍了全电动注塑机的应用领域,并展望了全电动注塑机的发展。     

Decision-feedback detection for block differential space-time modulation

Time variation on fading channels hinders accurate channel estimation in differential space-time modulation and deteriorates the performance. Decision-feedback differential detection is studied for block differential space-time modulation, and compared with conventional differential space-time modulation. It is observed that the proposed scheme does not suffer effective fading bandwidth expansion, as does the conventional scheme. An improved effective signal-to-noise ratio approach is proposed for analyzing the performance of the proposed scheme in time-varying flat Rayleigh fading. Theoretical analysis and simulations show the improved performance of the proposed scheme over the conventional scheme.     

成人高等教育专业导师制学生管理模式初探

文章对如何在成人高等院校实施专业导师制学生管理模式进行了探讨，指出专业导师制能适应成人高等教育业余学习的特点，并对继续教育的顺利发展起到积极作用。