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.     

测井资料在优选压裂层位中的应用

压裂是低孔、低渗油层改造的主要增产措施。根据常规测井资料、岩石物理实验分析数据及试油成果。研究储层四性关系，确定区块的低孔、低渗储层评价标准。进一步对油层进行分类，有针对性地为油层压裂提供施工层位和准确的储层参数。通过商543区块实例，阐述了选择压裂层位的方法。     

动态评价技术在塔河碳酸盐岩缝洞型油气藏中的应用

塔河油田奥陶系油气藏是大型碳酸盐岩溶洞型油气藏，其储渗空间主要为大小不同的溶洞、裂缝带、溶蚀孔隙等组成，该油气藏具有极强的非均质性，单纯用静态资料来认识这类油气藏是非常困难。文章提出利用生产动态资料和信息进行该类型油气藏研究的新思路，利用人工神经网络技术在处理非线性相关参数预测方面的优势，并以渗流理论为基础，结合试井成果，选用已知油井的产量、油嘴、油压、含水率、气油比、原油密度等6个开发动态参数作为样品输入数据，推导出影响油气藏开发的重要参数（地层系数）与生产信息的关系，建立了人工神经网络预测储层参数的结构模型。通过塔里木盆地塔河油气田实例研究，说明了利用动态信息评价油气藏技术在碳酸盐岩缝洞型油气藏储层预测和非均质性分析等方面具有较高的实用价值。     

接轨站设置位置和布置图型的影响因素及其分类

通过对接轨站设置位置和布置图型主要影响因素的分析。按照能够充分反映接轨站作业特点的交接方式。对接轨站所采用的布置图型进行了归纳和分类。     

ca油田稠油油藏系统保护油气层研究

针对ca油田多层状砂泥薄互层稠油油藏的特点,开展了热采和非热采条件下储层变化特征研究、钻井和固井过程入井液的研究、采油工艺技术等系统保护油气层研究,了解各种变化的作用过程和原因,有效地预防现场施工中可能发生的储层伤害,从而达到储层保护、提高采收率的目的。     

湘中海相浅层湘冷1井酸压工艺研究及应用

湘冷1井具有气层埋藏浅（400m-500m）、纵向上裂隙发育的特点，属低孔、低渗的含泥质灰岩致密储层。大量室内实验和研究采用“前置液酸压＋闭合酸化”工艺技术，并优选了相应降阻酸和闭合酸配方。通过酸压实现了该井工业油气流的突破，取得了明显的增产效果，为新区海相浅层气的开发探索出了一套成熟的改造增产措施。     

储层应力敏感性影响因素研究

全面分析储层应力敏感性产生的机理认为，外部因素的改变会引起储层产生应力敏感性．而储层岩石物性等内部因素对应力敏感性的强弱起决定性作用。室内岩心应力敏感性评价时．仪器与设备的精度、加载与卸载方式、实验用流体类型以及各种人为因素等都会对评价结果产生影响，其中岩心密封套在高压、高温条件下的密闭性会对实验结果产生较大影响。所以储层应力敏感性不应该从孔隙度和渗透率的高低进行简单评价，中、高渗储层和低渗储层在生产过程也都可能表现出较强的应力敏感性现象。     

番禺30-1砂岩强水驱气藏储层非均质性研究

针对垂向非均质性严重且边底水能量强的番禺30-1气田面临的潜在开发问题，通过岩心分析及测井二次解释，对其夹层特征及储层非均质性等进行了研究，划分出19个流动单元并定量描述了各流动单元的特征参数，建立了该气田的精细地质模型。综合评价表明，新建的地质模型具有较高的精度，为该气藏合理开发提供了坚实的地质基础。     

Biotransformation of l‐menthol by twelve isolates of soil‐borne plant pathogenic fungi (Rhizoctonia solani) and classification of fungi

The microbial transformation of l‐menthol ( 1 ) was investigated by using 12 isolates of soil‐borne plant pathogenic fungi, Rhizoctonia solani (AG‐1‐IA Rs24, Joichi‐2, RRG97‐1; AG‐1‐IB TR22, R147, 110.4; AG‐1‐IC F‐1, F‐4, P‐1; AG‐1‐ID RCP‐1, RCP‐3, and RCP‐7) as a biocatalyst. Rhizoctonia solani F‐1, F‐4 and P‐1 showed 89.7–99.9% yields of converted product from 1 , RCP‐1, RCP‐3, and RCP‐7 26.0–26.9% and the other isolates 0.1–12.0%. In the cases of F‐1, F‐4 and P‐1, substrate 1 was converted to (?)‐(1S,3R,4S,6S)‐6‐hydroxymenthol ( 2 ), (?)‐(1S,3R,4S)‐1‐hydroxymenthol ( 3 ) and (+)‐(1S,3R,4R,6S)‐6,8‐dihydroxymenthol ( 4 ), which was a new compound. Substrate 1 was converted to 2 and/or 3 by RRG97‐1, 110.4, RCP‐1, RCP‐3 and RCP‐7. The structures of the metabolic products were elucidated on the basis of their spectral data. In addition, metabolic pathways of the biotransformation of 1 by Rhizoctonia solani are discussed. Finally, from the main component analysis and the differences in the yields of converted product from 1 , the 12 isolates of Rhizoctonia solani were divided into three groups based on an analysis of the metabolites. Copyright © 2003 Society of Chemical Industry     

砾岩储层精细描述中标准测井资料的应用

克拉玛依油田七区的标准测井资料是指使用标准电极系视电阻率测井、自然电位测井和井径测井,以相同的1:500深度比例尺及相同的横向比例进行测井作业所取得的资料.这种资料本来并不具备定量解释储层孔隙度和含油饱和度的能力,但这种资料占该区测井资料总量的比率高达34%.利用标准电极系视电阻率资料和岩心分析资料建立了视电阻率-岩性图版,利用自然电位减小系数α和岩心孔隙度分析资料φ建立了α-φ图版,根据综合测井资料求出标准测井视电阻率校正系数,进而确定了饱和度计算方程的参数.与相应的综合测井资料计算结果相对比,用该方法得到的孔隙度平均绝对误差及相对误差分别为1.85%和11.88%;含油饱和度平均绝对误差及相对误差分别为9.08%和24.75%.将该方法有选择地应用到该区砾岩储层精细描述研究中,弥补了缺乏综合测井资料无法进行测井储层评价及参数研究的缺陷.