Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

Simulating the psychological experience of human vision，a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly，based on the spectral and texture information，the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally，three types of identified road information are verified and merged，and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye，and the overall classification accuracy is higher，indicating that the algorithm is effective and feasible and has good use value.     

碎软煤层条带瓦斯地面高效抽采技术研究

为了提高碎软煤层条带瓦斯抽采效率和效果,基于目前地面瓦斯抽采主要采用垂直井或从式井的方式抽采效果差、效率低的现状,通过理论和实验分析论证了穿岩层压裂改造煤储层的可行性,提出了在目标煤层顶板岩层中钻水平井,并通过垂直向下射孔以及采用泵送桥塞分段进行压裂的方式进行地面瓦斯抽采。试验结果表明:顶板分段压裂水平井单井产量高、高稳产期更长、产量衰减更慢;有效水平井段控制区域内瓦斯下降均匀,更有利于进行条带瓦斯抽采;相同投资条件下,采用水平井的方式瓦斯抽采效率和投入产出比更高。     

Smart optical measurement probe for autonomously detecting nano-defects on bare semiconductor wafer surface: Verification of proposed concept

We propose a new method of inspecting a surface for fine defects that combines the optical inspection method with observation of the physical behavior of a liquid. A liquid thin film on a substrate behaves as a near-field physical probe that autonomously captures nano-particulate defects. Optical observation of the interfacial behavior of the liquid thin film is used to detect minute defects. This method combines the characteristics of optical detection (i.e., detection from a remote field and simultaneous detectability on a plane) and the high sensitivity of a physical near-field probe. We examined the basic principles of the proposed method through numerical calculation and applied it in experiments to detect fine particulate defects on a silicon substrate for semiconductor manufacturing to demonstrate the validity of the basic concept of the proposed method.     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

萃取塔数学模型及过程强化的若干研究进展

萃取塔因生产能力大、占地面积小、密闭性好等优点，在石油、化工、生物、医药和环境工程等多领域被广泛应用。本文从以下几个方面介绍了萃取塔近些年的研究进展：综述了传统萃取塔（脉冲萃取塔、转盘塔与Kühni塔等）的水力学、轴向扩散与传质模型的发展，分析比较了表面张力、传质方向、放大效应等因素对模型的影响；介绍了计算流体动力学（CFD）在萃取塔中单液滴、单相流模拟、液-液两相流模拟、外加能量模拟、与群体平衡模型（PBM）耦合模拟中的应用进展；介绍了国内外设计开发的新型萃取塔，包括改变传统塔的内构件和引入多种外场能量等方式来强化相间传质。研究表明，将先进实验研究方法、准确经验模型和可靠理论计算相结合，将会是萃取塔研究的重要手段和方向。     

Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

陶瓷及陶瓷基复合材料微缺陷的超声检测

为研究陶瓷及陶瓷基复合材料微缺陷的超声检测能力，针对一些人工缺陷试样进行了超声检测试验。试验主要采用了纵波垂直入射法和泄漏瑞利波法。通过试验结果，比较了两种方法的检测能力。     

超临界流体萃取技术生产重交通道路沥青的研究

研究了采用超临界流体萃取技术(SFEF),以减压渣油和催化裂化油浆为原料,制备重交通道路沥青产品的可行性.结果表明:当原料中油浆掺入量为10%～30%时,可以生产出牌号为AH70,AH90,AH110的重交通道路沥青产品.工业试验表明,生产牌号为AH70,AH90的重交通道路沥青,采用此技术方案是可行的.