Mesh Snapping: Robust Interactive Mesh Cutting Using Fast Geodesic Curvature Flow

This paper considers the problem of interactively finding the cutting contour to extract components from a given mesh. Some existing methods support cuts of arbitrary shape but require careful and tedious input from the user. Others need little user input however they are sensitive to user input and need a postprocessing step to smooth the generated jaggy cutting contours. The popular geometric snake can be used to optimize the cutting contour, but it cannot deal with the topology change. In this paper, we propose a geodesic curvature flow based framework to overcome all these problems. Since in many cases the meaningful cutting contour on a 3D mesh is locally shortest in the sense of some weighted curve length, the geodesic curvature flow is an ideal tool for our problem. It evolves the cutting contour to the nearby local minimum. We should mention that the previous numerical scheme, discretized geodesic curvature flow (dGCF) is too slow and has not been applied to mesh segmentation. With a careful observation to dGCF, we devise here a fast computation scheme called fast geodesic curvature flow (FGCF), which only needs to solve a smaller and easier problem. The initial cutting contour is generated by a variant of random walks algorithm, which is very fast and gives reasonable cutting result with little user input. Experiment results on the benchmark mesh segmentation data set show that our proposed framework is robust to user input and capable of producing good results reflecting geometric features and human shape perception.     

一类组合系统的特征与分散固定模

研究了在航空领域中经常遇到的一类组合系统．结果表明，由于这类系统结构的特殊性，它的很多性质，如能控性、能观性及稳定性等都可以通过判断两个低阶系统的相应性质得到．这类系统不存在分散固定膜的充要条件是其能控且能观．     

Effects of amplitude modulation on perception of wind turbine noise

Wind turbine noise is considered to be easily detectable and highly annoying at relatively lower sound levels than other noise sources. Many previous studies attributed this characteristic to amplitude modulation. However, it is unclear whether amplitude modulation is the main cause of these properties of wind turbine noise. Therefore, the aim of the current study is to identify the relationship between amplitude modulation and these two properties of wind turbine noise. For this investigation, two experiments were conducted. In the first experiment, 12 participants determined the detection thresholds of six target sounds in the presence of background noise. In the second experiment, 12 participants matched the loudness of modified sounds without amplitude modulation to that of target sounds with amplitude modulation. The results showed that the detection threshold was lowered as the modulation depth increased; additionally, sounds with amplitude modulation had higher subjective loudness than those without amplitude modulation.     

Numerical modeling and simulations of active direct methanol fuel cell (DMFC) systems under various ambient temperatures and operating conditions

Direct methanol fuel cells (DMFCs) are potential candidates for portable backup power generation and auxiliary power units owing to their advantageous features, such as ease of fuel storage and delivery. Optimizing each component of a DMFC system is critical to improving the overall system performance and power density. This paper presents an active DMFC system model, in which a one-dimensional DMFC stack model is combined with major system components, including fuel and water tanks, liquid–gas separator, heat exchangers, pumps, and blowers. The model is implemented using a commercial flow-sheet simulator, ASPEN-HYSYS, and then applied to an active DMFC system to analyze the effects of the DMFC operating parameters and heat management. Special emphasis is placed on establishing active control strategies for the DMFC stack temperature, methanol crossover rate, and water recovery by optimizing the system components and operating conditions. Overall, this study helps identify innovative active DMFC system designs and configurations.     

撞楔法支护在平硐冒顶段施工中的应用

该文介绍了在老平硐恢复过程中,撞楔法在冒顶段施工中的应用情况。实践证明,该方法能有效的通过类似地段,并取得显著的经济效益,为其他类似工程提供了有益的参考。     

Real-time face view correction for front-facing cameras

Face views are particularly important in person-to-person communication.Differenes between the camera location and the face orientation can result in undesirabl...     

Convex Optimization Algorithms for Active Balancing of Humanoid Robots

We show that a large class of active balancing problems for legged robots can be framed as a second-order cone programming (SOCP) problem, a convex optimization problem for which efficient and numerically robust algorithms exist. We describe this general SOCP balancing framework, show that several existing optimization-based balancing strategies reduce to special cases of this more general formulation, and investigate the computational performance of our SOCP algorithms through simulation studies involving a humanoid model.     

An augmented EDA with dynamic diversity control and local neighborhood search for coevolution of optimal negotiation strategies

In this paper, we present an estimation of distribution algorithm (EDA) augmented with enhanced dynamic diversity controlling and local improvement methods to solve competitive coevolution problems for agent-based automated negotiations. Since optimal negotiation strategies ensure that interacting agents negotiate optimally, finding such strategies—particularly, for the agents having incomplete information about their opponents—is an important and challenging issue to support agent-based automated negotiation systems. To address this issue, we consider the problem of finding optimal negotiation strategies for a bilateral negotiation between self-interested agents with incomplete information through an EDA-based coevolution mechanism. Due to the competitive nature of the agents, EDAs should be able to deal with competitive coevolution based on two asymmetric populations each consisting of self-interested agents. However, finding optimal negotiation solutions via coevolutionary learning using conventional EDAs is difficult because the EDAs suffer from premature convergence and their search capability deteriorates during coevolution. To solve these problems, even though we have previously devised the dynamic diversity controlling EDA (D²C-EDA), which is mainly characterized by a diversification and refinement (DR) procedure, D²C-EDA suffers from the population reinitialization problem that leads to a computational overhead. To reduce the computational overhead and to achieve further improvements in terms of solution accuracy, we have devised an improved D²C-EDA (ID²C-EDA) by adopting an enhanced DR procedure and a local neighborhood search (LNS) method. Favorable empirical results support the effectiveness of the proposed ID²C-EDA compared to conventional and the other proposed EDAs. Furthermore, ID²C-EDA finds solutions very close to the optimum.     

A planar catalytic combustion sensor using nano-crystalline F-doped SnO2 as a supporting material for hydrogen detection

A planar catlytic combustion gas sensor based on Pd/Pt catalyst supported on F-doped SnO₂ nano-crystalline materials has been designed and fabricated for hydrogen detection. The sensor consists of platinum heaters on an alumina plate coated with a catalytic layer and compensating layer. This sensor exhibited better performance than that of the sensors employing sensing material of Pd/Pt catalyst on γ-Al₂O₃ and of Pd/Pt catalyst on nano-crystalline SnO₂. The detection limit of the sensor at 370 °C is in the concentration range of 0.5–5% (v/v), with an excellent linearity of signal voltage to the hydrogen gas concentration.