In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space...In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space hierarchical clustering are proposed.Firstly,the parameter-optimized odd partial Gabor filter is used to distinguish bobbin and yarn texture,to explore Garbor parameters for yarn bobbins,and to accurately discriminate frequency characteristics of yarns and texture.Secondly,multi-color clustering segmentation using color spaces such as red,green,blue(RGB)and CIELUV(LUV)solves the problems of over-segmentation and segmentation errors,which are caused by the difficulty of accurately representing the complex and variable color information of yarns in a single-color space and the low contrast between the target and background.Finally,the segmented bobbin is combined with the odd partial Gabor’s edge recognition operator to further distinguish bobbin texture from yarn texture and locate the position and size of the residual yarn.Experimental results show that the method is robust in identifying complex texture,damaged and dyed bobbins,and multi-color yarns.Residual yarn identification can distinguish texture features and residual yarns well and it can be transferred to the detection and differentiation of complex texture,which is significantly better than traditional methods.展开更多
Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibratio...Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibration ratiometric fluorescent sensing platform has been designed for sensitive visual detection of levofloxacin(LEV)based on fluorescent europium metal-organic framework(Eu-MOF)probe.Specifically,the Eu-MOF was facilely synthesized via directly mixing Eu^(3+)with 1,10-phenanthroline-2,9-dicarboxylic acid(PDA)ligand at room temperature,which exhibited well-stable red fluorescence at 612 nm.Upon the addition of target LEV,the significant fluorescence quenching from Eu^(3+)was observed owing to the inner filter effect between the Eu-MOF and LEV.While the intrinsic fluorescence for LEV at 462nm was gradually enhanced,thereby realizing the self-calibration ratiometric fluorescence responses to LEV.Through this strategy,LEV can be detected down to 27 nmol/L.Furthermore,a test paper-based Eu-MOF integrated with the smartphone assisted RGB color analysis was exploited for the quantitative monitoring of LEV through the multi-color changes from red to blue,thus achieved portable,convenient and visual detection of LEV in honey and milk samples.Therefore,the developed strategy could provide a useful tool for supporting the practical on-site test in food samples.展开更多
During the sizing process,yarn congestion fault occurs at the reed teeth of a sizing machine.At present,the yarn congestion fault is generally handled by manual detection.The sizing production line operates on a large...During the sizing process,yarn congestion fault occurs at the reed teeth of a sizing machine.At present,the yarn congestion fault is generally handled by manual detection.The sizing production line operates on a large scale and runs continuously.Untimely handling of the yarn congestion fault causes a large amount of yarn waste.In this research,a machine vision-based algorithm for yarn congestion fault detection is developed.Through the analysis of the congestion fault and interference contour characteristics,the basic idea of image phase subtraction to identify the congestion fault is determined.To address the interference information appearing after image phase subtraction,the image pre-processing methods of Canny edge extraction and mean filtering are employed.According to the fault size and location characteristics,the fault contour detection algorithm based on inter-frame difference is designed.To mitigate the camera vibration interference,the anti-vibration interference algorithm based on affine transformation is studied,and the fault detection algorithm for the total yarn congestion fault is determined.The detection of 20 sets of field data is carried out,and the detection rate reaches 90%.This fault detection algorithm realizes the automatic detection of yarn congestion fault of sizing machine with certain real-time performance and accuracy.展开更多
This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is establish...This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is established with production error and production cost as optimization objectives,combined with constraints such as the number of equipment and the number of layers.Second,a decoupled multi-objective optimization algorithm(DMOA)is proposed based on the linear programming decoupling strategy and non-dominated sorting in genetic algorithmsⅡ(NSGAII).The size-combination matrix and the fabric-layer matrix are decoupled to improve the accuracy of the algorithm.Meanwhile,an improved NSGAII algorithm is designed to obtain the optimal Pareto solution to the MCOP problem,thereby constructing a practical intelligent production optimization algorithm.Finally,the effectiveness and superiority of the proposed DMOA are verified through practical cases and comparative experiments,which can effectively optimize the production process for garment enterprises.展开更多
为了解决生物信息学中基因多序列比对的计算速度慢和软件陈旧的问题,提出了基于Yarn(Yet Another Resource Negotiator)云平台的生物基因多序列比对并行计算方法Yarn_clustalW。分析了clustalW算法的数学模型及其面向MapReduce的任务划...为了解决生物信息学中基因多序列比对的计算速度慢和软件陈旧的问题,提出了基于Yarn(Yet Another Resource Negotiator)云平台的生物基因多序列比对并行计算方法Yarn_clustalW。分析了clustalW算法的数学模型及其面向MapReduce的任务划分方式,Yarn_clustalW中综合考虑了基因的长度和数目,采用一种基于阈值刻度的任务划分方式。利用NCBI的GenBank生物基因数据作为案例程序进行了测试。实验结果表明:Yarn_clustalW比起多序列比对clustalW串行计算方法具有更快的运行时间与加速比,可以使生物科研人员节省很多时间与精力,方便对于药物靶标的发现,缩短生物药物的开发周期。展开更多
为解决Hadoop现有调度器调度任务时不能根据任务的紧迫程度分配资源的问题,研究YARN中的资源调度机制,改进原调度器(Capacity Scheduler),提出一种基于优先级权重的Hadoop YARN(Yet Another Resource Negotiator)调度算法(Weight Schedu...为解决Hadoop现有调度器调度任务时不能根据任务的紧迫程度分配资源的问题,研究YARN中的资源调度机制,改进原调度器(Capacity Scheduler),提出一种基于优先级权重的Hadoop YARN(Yet Another Resource Negotiator)调度算法(Weight Scheduler Based on Priority)。为叶子队列设置队列优先级,结合队列资源利用率和队列优先级选择队列;将应用程序的初始权重设置为应用程序优先级的大小,通过等待时间判断是否更新权重,根据权重对队列中的应用程序进行排序,调度时优先为权重高的应用程序分配资源。实验结果表明,与原有调度算法相比,改进算法平均任务执行时间约减少141 s,平均等待时间减少34.5%,保证了用户执行任务的相对公平,提高了用户总体满意度。展开更多
基金Key Research and Development Plan of Shaanxi Province,China(No.2023-YBGY-330)。
文摘In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space hierarchical clustering are proposed.Firstly,the parameter-optimized odd partial Gabor filter is used to distinguish bobbin and yarn texture,to explore Garbor parameters for yarn bobbins,and to accurately discriminate frequency characteristics of yarns and texture.Secondly,multi-color clustering segmentation using color spaces such as red,green,blue(RGB)and CIELUV(LUV)solves the problems of over-segmentation and segmentation errors,which are caused by the difficulty of accurately representing the complex and variable color information of yarns in a single-color space and the low contrast between the target and background.Finally,the segmented bobbin is combined with the odd partial Gabor’s edge recognition operator to further distinguish bobbin texture from yarn texture and locate the position and size of the residual yarn.Experimental results show that the method is robust in identifying complex texture,damaged and dyed bobbins,and multi-color yarns.Residual yarn identification can distinguish texture features and residual yarns well and it can be transferred to the detection and differentiation of complex texture,which is significantly better than traditional methods.
基金supported by the National Natural Science Foundation of China(Nos.32260247 and 22064010)the Natural Science Foundation of Jiangxi Province(Nos.20232BAB215071 and 20224BAB213009).
文摘Developing an accurate and visual sensing strategy for trace levels of fluoroquinolone residues that pose threat to food safety and human health is highly desired but remains challenging.Herein,a target selfcalibration ratiometric fluorescent sensing platform has been designed for sensitive visual detection of levofloxacin(LEV)based on fluorescent europium metal-organic framework(Eu-MOF)probe.Specifically,the Eu-MOF was facilely synthesized via directly mixing Eu^(3+)with 1,10-phenanthroline-2,9-dicarboxylic acid(PDA)ligand at room temperature,which exhibited well-stable red fluorescence at 612 nm.Upon the addition of target LEV,the significant fluorescence quenching from Eu^(3+)was observed owing to the inner filter effect between the Eu-MOF and LEV.While the intrinsic fluorescence for LEV at 462nm was gradually enhanced,thereby realizing the self-calibration ratiometric fluorescence responses to LEV.Through this strategy,LEV can be detected down to 27 nmol/L.Furthermore,a test paper-based Eu-MOF integrated with the smartphone assisted RGB color analysis was exploited for the quantitative monitoring of LEV through the multi-color changes from red to blue,thus achieved portable,convenient and visual detection of LEV in honey and milk samples.Therefore,the developed strategy could provide a useful tool for supporting the practical on-site test in food samples.
基金National Key Research and Development Program of China(No.2017YFB1304001)。
文摘During the sizing process,yarn congestion fault occurs at the reed teeth of a sizing machine.At present,the yarn congestion fault is generally handled by manual detection.The sizing production line operates on a large scale and runs continuously.Untimely handling of the yarn congestion fault causes a large amount of yarn waste.In this research,a machine vision-based algorithm for yarn congestion fault detection is developed.Through the analysis of the congestion fault and interference contour characteristics,the basic idea of image phase subtraction to identify the congestion fault is determined.To address the interference information appearing after image phase subtraction,the image pre-processing methods of Canny edge extraction and mean filtering are employed.According to the fault size and location characteristics,the fault contour detection algorithm based on inter-frame difference is designed.To mitigate the camera vibration interference,the anti-vibration interference algorithm based on affine transformation is studied,and the fault detection algorithm for the total yarn congestion fault is determined.The detection of 20 sets of field data is carried out,and the detection rate reaches 90%.This fault detection algorithm realizes the automatic detection of yarn congestion fault of sizing machine with certain real-time performance and accuracy.
基金Supported by the Natural Science Foundation of Zhejiang Province(No.LQ22F030015).
文摘This work addresses the cut order planning(COP)problem for multi-color garment production,which is the first step in the clothing industry.First,a multi-objective optimization model of multicolor COP(MCOP)is established with production error and production cost as optimization objectives,combined with constraints such as the number of equipment and the number of layers.Second,a decoupled multi-objective optimization algorithm(DMOA)is proposed based on the linear programming decoupling strategy and non-dominated sorting in genetic algorithmsⅡ(NSGAII).The size-combination matrix and the fabric-layer matrix are decoupled to improve the accuracy of the algorithm.Meanwhile,an improved NSGAII algorithm is designed to obtain the optimal Pareto solution to the MCOP problem,thereby constructing a practical intelligent production optimization algorithm.Finally,the effectiveness and superiority of the proposed DMOA are verified through practical cases and comparative experiments,which can effectively optimize the production process for garment enterprises.
文摘为了解决生物信息学中基因多序列比对的计算速度慢和软件陈旧的问题,提出了基于Yarn(Yet Another Resource Negotiator)云平台的生物基因多序列比对并行计算方法Yarn_clustalW。分析了clustalW算法的数学模型及其面向MapReduce的任务划分方式,Yarn_clustalW中综合考虑了基因的长度和数目,采用一种基于阈值刻度的任务划分方式。利用NCBI的GenBank生物基因数据作为案例程序进行了测试。实验结果表明:Yarn_clustalW比起多序列比对clustalW串行计算方法具有更快的运行时间与加速比,可以使生物科研人员节省很多时间与精力,方便对于药物靶标的发现,缩短生物药物的开发周期。
文摘为解决Hadoop现有调度器调度任务时不能根据任务的紧迫程度分配资源的问题,研究YARN中的资源调度机制,改进原调度器(Capacity Scheduler),提出一种基于优先级权重的Hadoop YARN(Yet Another Resource Negotiator)调度算法(Weight Scheduler Based on Priority)。为叶子队列设置队列优先级,结合队列资源利用率和队列优先级选择队列;将应用程序的初始权重设置为应用程序优先级的大小,通过等待时间判断是否更新权重,根据权重对队列中的应用程序进行排序,调度时优先为权重高的应用程序分配资源。实验结果表明,与原有调度算法相比,改进算法平均任务执行时间约减少141 s,平均等待时间减少34.5%,保证了用户执行任务的相对公平,提高了用户总体满意度。
