未知环境下基于约束点的移动机器人路径规划

针对未知环境中障碍物种类多样性和位置不确定性的特点,提出了基于约束点的路径规划方法。首先对机器人在未知环境中检测到的局部障碍物信息进行分类和几何特征属性描述,得其约束点信息,然后引入改进后的A*算法,将其搜索范围局限于约束点上,计算约束点的评价函数值后得到子目标点,机器人到达子目标点后,若陷入死区,则采取回溯路径策略,重新选择子目标点,否则根据该点所属的障碍物种类采取跨越或绕行避障策略,最后移动机器人在未知环境中顺利到达目标点。仿真研究说明本文提出的路径规划方法具有可行性和有效性。     

Thermal diffusivity of fluids in a broad region around the critical point

Dynamic light scattering is a suitable method for the investigation of transport properties such as the thermal diffusivity of optically transparent fluids. The main advantages of the method are its quickness, the fact of the thermodynamic state of equilibrium of the sample (gradients are not required), and the relatively simple evaluation of data without the necessity of calibration. However, an insufficient production of intensity of scattered light may be a limiting effect. For that reason the vicinity of the gas-liquid critical point represents the classical range of application. In this paper, it is shown that by means of an appropriate choice of experimental apparatus, measurements are also feasible in an extended range of states. Broad regions around critical points of three pure fluids (sulfur hexafluoride, SF₆; ethane, C₂H₆; nitrous oxide, N₂O) over temperature ranges ¦T-T _c¦ of 0.02 to 50 K and density ranges (/_c) of 0.2 to 2 were investigated. In this region the thermal diffusivity shows great variations with temperature and density and cannot be described by means of ideal-gas behavior or relations for liquids. The measurements were carried out along the coexistence curve for both phases, along the critical isochore and along some isotherms with TT _c. The measured or calculated density, pressure, and thermal diffusivity data as well as some correlations are presented.     

高沸点溶剂法合成原乙酸三甲酯

对低沸点溶剂法制备原乙酸三甲酯工艺进行了改进，比较了煤油、2-乙基己醇、氯苯、异佛尔酮、邻苯二甲酸二丁酯、乙二醇二丁醚等高沸点溶剂对反应的影响，筛选出最优高沸点溶剂煤油：研究了新反应体系的醇解pH值、溶剂的循环使用次数对反应的影响及溶剂循环损耗率，结果表明，醇解的最佳pH值为5．6；随着溶剂循环次数增加，原乙酸三甲酯收率从83．6％(1次)逐渐下降到76．7％(16次)；溶剂次平均损耗率4．6％。实现了直接蒸馏产品，溶剂循环使用的新工艺。避免了旧工艺先蒸溶剂，后蒸产品，产品大量分解，收率低等缺点。     

Reliability-based robust design optimization: A general methodology using genetic algorithm

In this paper, we present an improved general methodology including four stages to design robust and reliable products under uncertainties. First, as the formulation stage, we consider reliability and robustness simultaneously to propose the new formulation of reliability-based robust design optimization (RBRDO) problems. In order to generate reliable and robust Pareto-optimal solutions, the combination of genetic algorithm with reliability assessment loop based on the performance measure approach is applied as the second stage. Next, we develop two criteria to select a solution from obtained Pareto-optimal set to achieve the best possible implementation. Finally, the result verification is performed with Monte Carlo Simulations and also the quality improvement during manufacturing process is considered by identifying and controlling the critical variables. The effectiveness and applicability of this new proposed methodology is demonstrated through a case study.     

Augment low-field intra-operative MRI with preoperative MRI using a hybrid non-rigid registration method

Background

Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery.

Method

To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery.

Results

The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92 ± 0.54 mm, and the compensation accuracy is 74.3 ± 5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value = .003) although these landmarks had larger initial displacements.

Conclusions

The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.     

基于Gabor多尺度空间的不变兴趣点检测

针对以往仿射不变兴趣点的特征尺度不能直接断定的问题, 提出一种基于Gabor多尺度空间的不变兴趣点检测算法。该算法主要包括三个步骤：应用Gabor滤波器组与图像卷积建立图像Gabor多尺度空间; 通过极大值准则检测兴趣点并直接断定特征尺度; 采用二阶矩矩阵描述兴趣点局部结构。实验结果表明, 相比较其他Hessian-Affine、MSER等算法, 该算法在图像模糊和JPEG压缩情况下可重复率和可匹配率均取得最好结果, 是一种能有效直接提取特征尺度的兴趣点检测算法。     

基于改进符号化度量方法的机场噪声异常检测

机场噪声中的异常情况拥有很大价值,利用它能够及时完善飞机和机场的设备。结合机场噪声数据的特点,对上述问题进行研究并提出一种基于改进的符号化聚集近似(Symbolic Aggregate Approximation,SAX)相似性度量的单监测点的时间序列异常检测方法。其运用相似性度量方法计算出度量结果,再运用k近邻异常检测方法进行异常发现,最后发现异常时间段。该方法在理论验证可行性之后在某机场的实测数据中进行应用,取得了良好的效果。     

Managing nutrient losses from rural point sources and urban environments

Nutrient loss from rural point sources and urban environments need to be minimised as part of strategies to overcome declining water quality on the Swan Coastal Plain and in the Peel-Harvey estuary in Western Australia. This paper discusses the management of nutrient losses from domestic effluent, urban stormwater runoff, domestic gardens and public open space, intensive animal industries and intensive irrigated agriculture. Measures to minimise nutrient losses from these sources are outlined, using cooperative, technological and regulatory approaches.     

ESTIMATION FOR NONNEGATIVE AUTOREGRESSIVE PROCESSES WITH AN UNKNOWN LOCATION PARAMETER

Abstract. Consider an AR(1) process given by X ^t=γ+ø X _t+ Z _t≥ 1. where 0 ≤γ, 0 ≤ø 1 are unknown parameters and the innovations Z _t, ≥ 1, are independently and identically distributed positive random variables. We propose estimates of (γø) which are obtained as the solution to a linear programming problem and establish their strong consistency. When the Z _ts have the exponential distribution. our estimate becomes the conditional maximum likelihood estimate given X ₀. Under the assumption of regular variation of the innovation distribution at its left and right endpoints (assumed to be 0 and ∝ respectively), we establish asymptotic limit laws for the estimates. Consistent estimators for a class of moving-average processes with heavy-tailed innovation distribution are also presented.