Collaborative innovation of E-Commerce enterprises based on FPGA and convolutional neural network

Everything you need to know about e-commerce. The term "e-commerce" refers to any commercial transaction type that requires the transmission of information over the Internet. By definition, it uses the Internet as a platform for communication and financial transactions or, at the same time, covering various business activities. In the previous method based on Deep learning and .net for Collaborative Innovation of E-Commerce platform. In the existing method, perception of security and reliability and data integrity and protection are drawbacks of the previous method. The proposed FPGA (Field-programmable gate array) and Convolutional Neural Network (CNN) are used to develop the Collaborative Innovation of E-Commerce platform and easily interface with the network without any complexity. E-commerce is an Internet-based tool, usually the exchange of Internet-based products and services. E-commerce refers to commercial transactions and commercial transactions involving exchange (e.g., money) within organizational or personal boundaries. The Web exchanges cross-organizational or personal boundary value (such as gold) for products and services for commercial transactions and commercial transactions. Here focus effectively on trade between digital companies and individuals.     

白酒人工催陈技术研究进展

白酒自然陈酿具有周期长、占地面积大和投资成本高等问题，因此白酒人工催陈技术受到了广泛的关注。目前白酒人工催陈技术主要包括物理催陈、化学催陈和生物催陈等，其中，物理催陈和生物催陈应用潜力较大，这些技术的应用可以大幅度缩短储存时间，提高白酒品质，降低生产成本。本文从白酒陈酿机理、储存条件出发，综述中国白酒人工催陈技术的研究现状，并对不同的催陈技术及其应用前景进行了分析和比较，旨在为今后白酒人工催陈的研究提供参考和借鉴。     

Nutrient enrichment of dairy curd by incorporation of whole and ruptured microalgal cells (Nannochloropsis salina)

This work investigated incorporation of Nannochloropsis salina into renneted dairy gels and curd. Whole and ruptured microalgal cells did not impair κ-casein macropeptide cleavage by the rennet enzyme. However, insoluble components of ruptured cells impeded gelation, presumably by hindering interactions between renneted casein micelles. Confocal imaging showed that whole cells were retained and homogenously distributed within the protein network of the gels and cooked curd, whereas ruptured algae formed large aggregates that altered the protein matrix. Eicosapentaenoic acid (EPA) in the whole microalgal cells was incorporated within the curds, with considerably less EPA retained for ruptured cells. Soluble algal debris did not impair gelation, however EPA wasn't retained in the curd. The study demonstrates that nutrient enrichment of renneted dairy products is possible by incorporating whole microalgal cells to displace milk fat with protein and the beneficial long-chain omega-3 fatty acid EPA. Future research into the optimisation of product organoleptic properties is required.     

基于气动性能与刚度特性的风力机翼型优化设计

结合翼型泛函集成理论与叶片截面刚度矩阵数学计算模型,提出了风力机中等厚度翼型气动性能与结构刚度特性的一体化设计方法,实现了翼型气动性能与叶片截面刚度特性的同时提高。对考虑叶片截面铺层参数变化设计的WQ-B300翼型与DU97-W-300翼型进行了气动性能与结构刚度特性对比分析,结果表明:相比于DU97-W-300翼型,WQ-B300翼型的气动性能与叶片截面刚度性能均有显著提高,其挥舞刚度和摆振刚度分别提高了6.2%和8.4%,验证了该设计方法的可行性,给风力机中等厚度及大厚度翼型设计提供了一种思路。     

垂直轴风力机两种翼型气动性能比较研究

叶片是风力机最重要的组成部分,在不同的风能资源情况下,翼型的选择对垂直轴风力机气动特性有着重要的影响。文章分别以NACA0018翼型(对称翼型)和NACA4418翼型(非对称翼型)建立3叶片H型垂直轴风力机二维仿真模型。应用数值模拟的研究方法,从功率系数、单个叶片切向力系数等方面比较两种风力机模型在不同叶尖速比下的气动特性,并采用风洞实验数据验证了流场计算的准确性。CFD计算结果表明:在低叶尖速比下,NACA4418翼型风力机气动特性优于NACA0018翼型风力机,适用于低风速区域;在高叶尖速比下,NACA0018翼型风力机气动特性较好,适用于高风速地区。而且在高叶尖速比时,NACA0018翼型在上风区时,切向力系数平均值要高于NACA4418翼型,在下风区时,NACA418翼型切向力系数平均值高。该研究可为小型垂直轴风力机翼型的选择提供参考。     

芝麻粕蛋白酶法提取工艺优化及组分分析

为了综合利用芝麻粕资源，以芝麻粕为原料，利用硬脂酸、吐温80、十二烷基硫酸钠三种表面活性剂对其进行脱脂处理，再采用水剂法去除表面活性剂，最后利用中性蛋白酶、碱性蛋白酶和木瓜蛋白酶对芝麻粕蛋白进行水解，以芝麻粕蛋白溶出率为考察指标优选出最佳水解酶。在此基础上，通过单因素试验和正交试验对酶解工艺条件进行优化，并利用2,4-二硝基氟苯柱前衍生高效液相色谱法分析水解物成分。结果表明，吐温80脱脂效果最好，芝麻粕脱脂率达93.49%；碱性蛋白酶为最佳水解酶，其最佳酶解条件为料水比1∶10（g∶mL）、酶解温度50 ℃、加酶量0.04%、酶解时间3.0 h。在此最佳酶解条件下，芝麻粕蛋白溶出率为88.94%。水解物中含有20种氨基酸，其中8种人体必需氨基酸含量高于FAO/WHO的推荐值。     

Visual Detection of Adenosine Triphosphate by Taylor Rising: A Simple Point-of-Care Testing Method Based on Rolling Circle Amplification

Rapid and sensitive point-of-care testing (POCT) is an extremely critical mission in practical applications, especially for rigorous military medicine, home health care, and in the third world. Here, we report a visual POCT method for adenosine triphosphate (ATP) detection based on Taylor rising in the corner of quadratic geometries between two rod surfaces. We discuss the principle of Taylor rising, demonstrating that it is significantly influenced by contact angle, surface tension, and density of the sample, which are controlled by ATP-dependent rolling circle amplification (RCA). In the presence of ATP, RCA reaction effectively suppresses Taylor-rising behavior, due to the increased contact angle, density, and decreased surface tension. Without addition of ATP, untriggered RCA reaction is favorable for Taylor rising, resulting in a significant height. With this proposed method, visual sensitive detection of ATP without the aid of other instruments is realized with only a 5 μL droplet, which has good selectivity and a low detection limit (17 nM). Importantly, this visual method provides a promising POCT tool for user-friendly molecular diagnostics.     

基于流形学习的光学遥感图像分类

随着光学遥感图像技术的快速发展与广泛应用,对光学遥感图像的准确分类具有深远的研究意义。传统特征提取方式提取的高维特征中夹杂着许多冗余信息,分类过程可能导致过拟合现象,针对传统的线性降维算法不足以保持原始数据的内部结构,容易造成数据失真这一问题,提出基于流形学习的光学遥感图像分类算法。该算法首先提取出图像的SIFT特征,然后将流形学习运用于特征降维,最后结合支持向量机进行训练和识别。实验结果表明,在Satellite、NWPU和UCMerced实验数据中,冰川、建筑群和海滩分类精度得到了有效提高,达到85%左右;针对沙漠、岩石、水域等特殊环境遥感图像,分类精度提高了10%左右。总而言之,基于流形学习的分类算法对通过降维之后的数据能够保持在原高维空间中的拓扑结构,相似特征点能得到有效聚合,预防了"维数灾难",减少了计算量,保证了分类精度。     

基于机器视觉的香蕉果肉缺陷预测方法

针对香蕉内部果肉缺陷难以预测的问题,运用机器视觉技术对香蕉果皮与果肉进行图像识别,对识别参数进行数据拟合得到果肉缺陷的预测模型。将采集到的图像灰度化并进行滤波去噪,通过双阀值二值化和形态学分析对图像进行识别处理,提取香蕉果皮、香蕉果肉、香蕉果皮黑斑与香蕉果肉缺陷。计算提取区域的像素点总数,将其作为区域面积。分别用香蕉果皮总面积/香蕉果肉总面积与果皮黑斑面积/果肉缺陷面积之比来定义香蕉果皮黑斑度与果肉缺陷度。运用多项式拟合法,根据训练样本得出果肉缺陷预测函数,对预测函数进行残差分析。通过预测模型对香蕉划分等级,总准确率达到88.9%,与通过香蕉果皮进行等级划分其他方法相比,试验所得模型的预测准确率较高,表明通过香蕉果肉进行预测的方法具有一定的优越性。