A Hybrid Optimization Approach of Single Point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with Principal Component Analysiss

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with Principal Component Analysis(PCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with PCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

Feature Extraction of Sectorial Scan Image of Thick-Walled Electron Beam Welding Seam Based on Principal Component Analysis

A feature extraction method was proposed to sectorial scan image of Ti-6Al-4V electron beam welding seam based on principal component analysis to solve problem of high-dimensional data resulting in timeconsuming in defect recognition. Seven features were extracted from the image and represented 87. 3% information of the original data. Both the extracted features and the original data were used to train support vector machine model to assess the feature extraction performance in two aspects: recognition accuracy and training time. The results show that using the extracted features the recognition accuracy of pore,crack,lack of fusion and lack of penetration are 93%,90.7%,94.7% and 89.3%,respectively,which is slightly higher than those using the original data. The training time of the models using the extracted features is extremely reduced comparing with those using the original data.

Voltammetric Identification of Motor Oils Using Electronic Tongue on Carbon-Paste Electrode Basis

Viscous organic liquids are common products which are used in human life. The motor oils used to lubricate the moving parts of internal combustion engines present an important group of these substances. Timeous monitoring of motor oil quality allows providing durability of engine. For this purpose the problem of designing of express sensor devices for identification of motor oils and other viscous organic liquids using inexpensive voltammetric methods of analysis is solved. In this paper, the results of motor oils identification using electronic tongue on the carbon-paste electrode basis with motor oils as a binder have been presented. The possibility of univocal identification of individual samples of motor oils has been shown.

Comparison of Algorithms for an Electronic Nose in Identifying Liquors

When the electronic nose is used to identify different varieties of distilled liquors, the pattern recognition algorithm is chosen on the basis of the experience, which lacks the guiding principle. In this research, the different brands of distilled spirits were identified using the pattern recognition algorithms （principal component analysis and the artificial neural network）. The recognition rates of different algorithms were compared. The recognition rate of the Back Propagation Neural Network （BPNN） is the highest. Owing to the slow convergence speed of the BPNN, it tends easily to get into a local minimum. A chaotic BPNN was tried in order to overcome the disadvantage of the BPNN. The convergence speed of the chaotic BPNN is 75.5 times faster than that of the BPNN.

Characterization and comparison of the aroma-active compounds on different grades of sesame-flavor Baijiu by headspace solid-phase microextraction and gas chromatography-olfactometry-mass spectrometry

This study investigated the aroma-active compounds and compared the differences of three different grades of sesame-flavor Baijiu by headspace solid-phase microextraction(HS-SPME)coupled with gas chromatography-olfactometry-mass spectrometry(GC-O-MS).A total of 54 aroma-active compounds were detected.Principal component analysis showed that JZ1,JZ2,and JZ3 were well separated from each other.JZ1 as the premium-grade Baijiu had the highest aroma intensities,concentrations.According to aroma intensities and concentrations,dimethyl trisulfide,butanoic acid,phenylacetaldehyde,2-furylmethanethiol,ethyl hexanoate,2,6-dimethylpyrazine,etc.could be potentially applied as volatile makers to distinguish the three different grades of sesame-flavor Baijiu as their significant difference(P<0.05)in three Baijiu samples.Roasted aroma had the significant difference(P<0.05)in three sample base on aroma profiles.Meanwhile,2-furylmethanethiol,2,6-dimethylpyrazine were related to the roasted aroma,they may be had a significant contribution to the differences of three different grades of sesame-flavor Baijiu.This study has provided a comprehensive understanding of the differences of three different grades of sesame-flavor Baijiu.

Data Masking for Chinese Electronic Medical Records with Named Entity Recognition

With the rapid development of information technology,the electronifi-cation of medical records has gradually become a trend.In China,the population base is huge and the supporting medical institutions are numerous,so this reality drives the conversion of paper medical records to electronic medical records.Electronic medical records are the basis for establishing a smart hospital and an important guarantee for achieving medical intelligence,and the massive amount of electronic medical record data is also an important data set for conducting research in the medical field.However,electronic medical records contain a large amount of private patient information,which must be desensitized before they are used as open resources.Therefore,to solve the above problems,data masking for Chinese electronic medical records with named entity recognition is proposed in this paper.Firstly,the text is vectorized to satisfy the required format of the model input.Secondly,since the input sentences may have a long or short length and the relationship between sentences in context is not negligible.To this end,a neural network model for named entity recognition based on bidirectional long short-term memory(BiLSTM)with conditional random fields(CRF)is constructed.Finally,the data masking operation is performed based on the named entity recog-nition results,mainly using regular expression filtering encryption and principal component analysis(PCA)word vector compression and replacement.In addi-tion,comparison experiments with the hidden markov model(HMM)model,LSTM-CRF model,and BiLSTM model are conducted in this paper.The experi-mental results show that the method used in this paper achieves 92.72%Accuracy,92.30%Recall,and 92.51%F1_score,which has higher accuracy compared with other models.

不同发酵期浓香型青稞酒糟醅理化指标及基酒香气组分差异

基于前期优化的浓香型青稞酒发酵工艺,探究不同发酵期(40 d,50 d和60 d)对浓香型青稞酒糟醅理化指标和基酒挥发性香气组分的影响。结果表明,不同发酵期浓香型青稞酒出窖糟醅的水分、酸度、还原糖和淀粉差异显著(p<0.05)。随着发酵期的增加,出窖糟醅的水分增加,还原糖、酸度和淀粉呈现下降趋势。延长发酵期有利于延长微生物分解代谢,提高淀粉的利用率,提升出酒率。不同发酵期青稞酒的挥发性香气组分含量差异较大。随着发酵期增加,挥发性香气组分的种类及总含量呈现增加趋势。酸类、醇类和酯类为主要的挥发性香气组分,酸类和醇类组分的含量呈现先增加后下降的趋势,可能与醇酸酯化合成酯类有关,与酯类组分的含量增加趋势相一致。长发酵期有利于提高青稞酒中酯类组分的含量,进而增加青稞酒的香气浓郁度和丰富度。

基于电子鼻的海产干制品风味研究及品质鉴定

要:采用电子鼻采集干贝、墨鱼干、鱿鱼干、虾米、小鱼干、花蛤干的挥发性物质,分析不同种类的气味物质成分差异和特征,构建了线性判别模型和聚类分析树图,实现六种海产干制品的分类鉴别,进一步构建了干贝的品质判别模型用于未知样本的大小鉴定。为海产干制品的风味研究、鉴定、加工生产提供新的思路和方法,有望在海产干制品的品质研究、风味形成、加工指导等方面发挥更大的作用。

基于主元-分形理论的电子式电压互感器计量误差自主辨识方法研究

电子式电压互感器(EVT)由大量的电子单元组成,易受变电站复杂运行环境的影响,计量误差的长期稳定性较差。常规检测方法是定期与标准互感器比对校准,属于一种设备状态的抽样检测方法,无法评估EVT的计量数据对节点电能累积作用的影响。针对这一问题,文章基于电力系统节点三相对称的运行特性,通过对三相EVT的计量数据进行主元分形,在残差子分量中建立平方预测方差SPE统计量实现了EVT计量误差的自检测;通过计算EVT运行过程中SPE统计量的分形维数,实现了EVT计量误差劣化形式的自主辨识。研究成果有利于推动EVT的状态检测由定期检测发展为按需检测。

基于主成分分析法构建浓香型白酒香气分类模型

浓香型白酒分为三大流派,目前通过感官品评无法准确的对不同流派浓香型白酒进行分类,且受评价者的主观影响,导致评价结果难以量化。为探索不同流派浓香型白酒可量化的分类方法,本研究采用顶空固相微萃取结合气质联用技术对3种流派的7种优质浓香型白酒样品进行香气检测,利用主成分分析法对选定的优质浓香型白酒香气成分进行综合分析。结果表明,从7种白酒样品中共检测出145种挥发性风味成分,主要以酯类、芳香类、醇类、醛酮类化合物为主。通过主成分分析,鉴定出对优质浓香型白酒贡献度高的特征性风味组分有19种,包括己酸乙酯、正丁醇、丁酸乙酯、丁酸苯乙酯、乙缩醛等。通过构建的香气分类模型,可将七种浓香型白酒分成四簇,浓香多粮型白酒J1、J5归为一类,浓香单粮型白酒J2、J4归为一类,纯浓派鲁酒J6、J7归为一类,纯浓派苏酒J3单独归为一类,与对应白酒感官品评与聚类分析结果相一致。通过浓香型白酒香气分类模型的构建,对相关浓香型白酒香气的差异性形成理性分析及参考,同时为浓香型白酒的分类提供数据支持。

腌制剂及冲洗工艺对宣威火腿滋味的影响

以宣威火腿为研究对象,探讨3种腌制剂及2种冲洗工艺对其滋味特征的影响。通过钠离子含量、水分含量、水分活度、氨基酸、核苷酸、肽分子质量分布和电子舌分析不同宣威火腿滋味化合物和滋味属性的差异。结果表明,海藻碘盐腌制且高压水枪冲洗的火腿钠离子含量最高,为6.61 g/100 g;氯化钠腌制且清水浸泡冲洗的火腿中氨基酸含量最高,为961.96 mg/100 g;海藻碘盐腌制且高压水枪冲洗的火腿中核苷酸含量最高,为493.38 mg/100 g;分子质量分布分析表明,清水浸泡冲洗的火腿中小分子肽(<1000 Da)含量最多;电子舌分析发现高压水枪冲洗的火腿鲜味和咸味显著高于清水浸泡处理的火腿;主成分分析发现,高压水枪冲洗的条件下海藻碘盐和氯化钠腌制的宣威火腿在鲜味、咸味和丰富度上更加接近,该研究在阐明不同腌制剂及冲洗工艺对宣威火腿滋味影响的前提下,为提升宣威火腿的品质及其工业化提供了理论依据及技术支撑。

米香白酒舒适度量表分析及舒适度与挥发性风味成分相关性研究

为更加科学的评估消费者端对酒样的喜好,区别酒样品质差异,建立米香型白酒挥发性风味成分与舒适度关系,该研究采用调查问卷的方式对白酒饮用者饮酒1 h的感受进行调查,并对酒样主要挥发性风味成分进行定量测定,利用主成分分析(PCA)及建立回归模型的方式探索饮酒舒适度与白酒中主要挥发性风味成分的相关性。调查问卷结果显示,白酒饮后1 h常出现的典型症状为嗜睡、头晕、心悸、注意力不集中、疲倦、心跳加速问题;PCA结果表明,正丙醇、异戊醇、己酸乙酯、正已酸是影响所选五款酒样白酒风味的主要成分,且通过PCA可以将不同的酒样进行区分。建立了舒适度量表与白酒主要挥发性风味成分之间的回归方程,说明正性量表及负性量表综合得分与白酒挥发性风味综合指标之间呈现较好的拟合关系,三次方回归和多元线性回归关系良好。该研究初步探索了基于调查问卷、色谱分析及统计学分析的白酒饮后评价方法,为饮酒舒适度提升提供参考。

我国市售虾酱产品品质分析与评价

为了解我国市售虾酱产品的品质现状,探究不同品种虾酱之间的品质差异,采集了32种市售虾酱,进行了感官评价和水分、盐分、蛋白质、氨基酸态氮等理化指标的检测,对品质相关数据进行了统计分析和主成分分析,并进一步采用电子鼻和气相–离子迁移谱(GC-IMS)对气味进行了分析。结果表明,市售虾酱色泽和质地差异相对较小,而气味差异较大。理化指标中,市售虾酱的氨基酸态氮含量变异系数为33.91%,离散程度最大。在主成分分析中,提取到3个主成分,累计方差贡献率达82.32%,表明能够涵盖虾酱品质的基本信息,水分、氨基酸态氮、气味是影响虾酱综合品质的关键指标。电子鼻聚类热图表明,在欧式距离4.03处可将32种虾酱聚为4类,原料是影响聚类的主要因素。对海银虾、蜢子虾和白虾3种原料的虾酱进行GC-IMS分析,共鉴定出63种挥发性成分,主要是醇类。研究结果可为虾酱产品品质评价与生产工艺改进提供参考。

不同地区酱香型白酒风格特征及风味物质构成差异相关性研究

采用感官评价和气相色谱(GC)法探究不同地区酱香型白酒感官特征和骨架风味物质含量,并对结果进行主成分分析(PCA)及Spearman相关性分析,解析不同地区酱香型白酒感官特征与骨架风味物质的差异及相关性。结果表明,贵州地区酱香型白酒酱香、曲香和焦香得分较高,南方其他地区花果香和草木香较突出,山东地区和北方其他地区醇香和粮香风格明显。风味物质分析结果发现,贵州地区酱香型白酒酯类含量最高,山东地区和南方其他地区酱香型白酒醇类含量较高,北方其他地区酱香型白酒羰基类含量较低,且贵州地区的酱香型白酒乙酸乙酯和乳酸乙酯的比率均在1.4~1.9范围内。PCA结果表明,贵州地区酱香型白酒风味物质结构相似性最高。Spearman相关性分析结果表明,酱香、焦香、曲香和陈香被聚为一类,与正丁醇、3-羟基-2-丁酮、异戊酸乙酯、辛酸乙酯、异戊醛和糠醛呈极显著正相关(P<0.01)。

基于电子鼻和电子舌的洞庭(山)碧螺春茶冲泡条件优化

目的探究洞庭(山)碧螺春茶水最佳冲泡条件。方法采用电子鼻和电子舌技术对茶汤气味和滋味进行检测与分析,对不同茶水比(1:30、1:50、1:75、1:150,g:mL)、冲泡时间(1、2、4、8 min)以及冲泡温度(40、60、80、100℃)条件下进行电子鼻和电子舌检测,结果响应值进行雷达图分析(radar chart analysis,RCA)、主成分分析(principal components analysis,PCA)和线性判别分析(linear discriminant analysis,LDA)。结果碧螺春茶在茶水比为1:50(g:mL)、冲泡时间为4 min、冲泡温度为80℃的冲泡条件下,滋味与气味均达到最佳。结论不同冲泡条件下碧螺春茶茶汤气味与滋味均有不同,综合两者分析,得到碧螺春茶最佳冲泡条件。

基于主成分分析和聚类分析的食盐综合评价

为了解我国食盐产品的品质现状,文章对28种市售食盐的成分和滋味进行解析,通过相关性分析、主成分分析、建立综合评价模型和聚类分析方法对食盐样品进行评价和分类。结果表明,井矿盐氯化钠含量较高,最高可达99.72%;海盐氯化钠含量较低,但钙、镁、钾等无机元素丰富。食盐样品5种滋味指标间呈现显著性差异(P<0.05);在10种品质评价指标中提取了4个主成分,累计方差贡献率达79.041%;建立综合评价模型,发现海盐得分最高,井矿盐次之,湖盐得分最低;在欧氏距离为10时,可将食盐样品分为4类,符合样品实际情况。综上,主成分分析和聚类分析效果良好,将其应用于品质评价领域可为食盐的质量控制提供科学依据。

不同茶树品种绿杨春茶的适制性评价及其抗氧化活性研究

研究旨在筛选绿杨春茶适制品种,为绿杨春茶的品质提升和茶树良种引进提供理论依据。对仪征市5个主栽茶树品种制作的绿杨春茶进行综合比较,通过品质成分分析、电子舌分析和感官审评结果,研究不同品种绿杨春茶的适制性。结果表明,不同品种绿杨春茶的感官审评的总得分与滋味得分、电子舌鲜味值的排序结果一致,均为‘白叶1号’>‘群体种’>‘黄金芽’>‘龙井长叶’>‘福鼎大毫’。品质成分分析表明,鲜味值最高的‘白叶1号’和‘群体种’,所含鲜味氨基酸谷氨酸和天冬氨酸的含量均最高;涩味值最低‘黄金芽’所含EGCG的含量也最低(6.08%);苦味值最低的‘龙井长叶’含有最低的咖啡碱含量(2.78%);而‘福鼎大毫’含有最高的咖啡碱(3.44%)、EGCG(8.89%)和儿茶素(17.64%),且谷氨酸和天冬氨酸含量均最低,故苦味、涩味值最高而鲜味值最低,滋味较差,与感官审评结果一致。此外,‘龙井长叶’表现出最强的DPPH(IC_(50)=38.20μg/mL)、ABTS自由基(IC_(50)=17.44μg/mL)清除活性,抗氧化活性较强。综上,‘白叶1号’用于制备绿杨春茶最有优势,其次是‘群体种’和‘黄金芽’,而‘龙井长叶’虽在品质上稍差于‘白叶1号’,但具有较强的抗氧化活性,用于制备绿杨春茶也具备一定的优势。‘福鼎大毫’所制香气和滋味明显差于其他品种,不太适制绿杨春茶。

扫描电镜/能谱法对粉底液的检测分类研究

为建立一种将扫描电镜/能谱法与多元统计学结合检测粉底液物证的方法。对收集到的50个粉底液样本进行前处理,利用扫描电镜/能谱仪对样本进行分析测试,将50个样本大致分成2大类;结合K-Means聚类对实验数据进行处理,将2大类样本细化分为4类;最后利用随机森林算法搭建分类模型,40个样本作为训练集,10个样本作为测试集,测试集的预测正确率达到86.6%,预测效果良好,可实现样本分类自动化。此方法操作简单,可实现无损检材、分类效果良好,可直接用于公安机关侦查破案,在法庭科学领域有广阔的应用前景。

我国省域电子商务发展水平测度与聚类分析

电子商务在助力稳增长、促消费、保就业、惠民生等方面取得了显著成效,作为经济的“稳定器”“加速器”作用愈发凸显。从电子商务交易水平、区域信息化水平、电子商务人力资本水平这3个方面选取11个指标,构建电子商务发展水平的评价指标体系,采用主成分分析法和聚类分析法对2021年我国省域进行综合评价。研究表明:电子商务发展整体呈“东强西弱”的格局,广东、北京遥遥领先于其它地区,在5类地区中分别聚为一类,为电子商务的区域发展提出对策建议。

数字电子技术课程思政达成度分析

课程思政是构建全员、全程、全课程育人体系的重要环节,可与思想政治理论课同向同行,提升全方位育人效果。为了分析“数字电子技术”课程的课程思政达成度,通过调查问卷获得数据并使用SPSS对收集的数据进行信度分析、效度分析以及主成分分析,进而对数据进行降为并分析各个主成分所对应的实际意义,最终获得学生对不同思政点的了解程度,分析明确了该课程思政的重点内容和落实举措与重要意义。