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.     

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。     

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.     

自制煤层气井排采试气流程

根据煤层气井排采试气特点，调研目前各公司煤层气井排采流程的使用情况，结合武MXX多分支水平井产水量高、产气量高的要求，自制一套煤层气排采试气流程，满足大部分井的排采需要。     

细节决定采输卤的成败

通过认真学习《细节决定成败》，结合井矿盐开采的实际，分别以生产过程中的三个细节为主，讨论了在采输卤生产技术控制中的细节的重要性。     

FCC汽油光催化氧化脱硫的实验室研究

采用光催化氧化与液液萃取同时进行的方法，考察了光敏剂十六烷基三甲基溴化铵的用量、pH值、双氧水体积分数和反应时间对脱硫效果的影响。结果表明，在光源为主波长365nm的300W中压汞灯，双氧水体积分数为25％，FCC汽油与双氧水体积比为1：3，总体积为120mL，加入0．20g十六烷基三甲基溴化铵，以7000r／min高速均质5min，pH值为4，光照10h的实验条件下，FCC汽油脱硫率可达91．20％；脱硫后的双氧水及光敏剂可以重复使用，不会造成二次污染。     

Extracting Light from Polymer Light‐Emitting Diodes Using Stamped Bragg Gratings

In this paper, we describe a method for increasing the external efficiency of polymer light‐emitting diodes (LEDs) by coupling out waveguided light with Bragg gratings. We numerically model the waveguide modes in a typical LED structure and demonstrate how optimizing layer thicknesses and reducing waveguide absorption can enhance the grating outcoupling. The gratings were created by a soft‐lithography technique that minimizes changes to the conventional LED structure. Using one‐dimensional and two‐dimensional gratings, we were able to increase the forward‐directed emission by 47 % and 70 %, respectively, and the external quantum efficiency by 15 % and 25 %.     

磷酸酯类离子液体在燃油深度脱硫中的应用

研究了3种磷酸酯类离子液体,即1,3-二甲基咪唑磷酸二甲酯盐([MM im]DM P)、1-乙基-3-甲基咪唑磷酸二乙酯盐([EM im]DEP)和1-丁基-3-甲基咪唑磷酸二丁酯盐([BM im]DBP)的制备过程,考察了这3种磷酸酯类离子液体对模型油中3-甲基噻吩、苯并噻吩和二苯并噻吩的脱除效果及磷酸酯类离子液体的电化学再生方法。实验结果表明,这3种磷酸酯类离子液体的脱硫能力强弱顺序为:[EM im]DEP>[BM im]DBP[MM im]DM P;且对二苯并噻吩的脱除效果最好,对苯并噻吩的脱除效果次之,对3-甲基噻吩的脱除效果较差。以[EM im]DEP为萃取剂,油剂质量比为1∶1时,经5次萃取后,二苯并噻吩的脱除率可达到99.5%。利用电解法对[EM im]DEP进行了再生,在5~10V电压下电解10h,[EM im]DEP的脱硫率可以达到新鲜[EM im]DEP的90%以上。