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高速IC激光打标机的研制

电子工业专用设备 2005年第9期34卷 46-48页

作者：施广涛上海交通大学机械与动力工程学院上海200030

概述了新型激光打标机的研制思路,就提高打标速度、解决定位精度、降低产品损耗等问题给出了具体的解决方案。

关键词：高速定位传输视觉系统

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一类关于投资组合和消费选择的最优控制问题

山东大学学报（理学版） 2004年第4期39卷 1-6页

作者：王光臣史敬涛山东大学数学与系统科学学院山东济南250100

论了一类在金融市场上只有两种投资选择———股票和外汇存款情形下的最优投资组合和消费率的选择问题 ,对“绝对风险厌恶 (HARA)”情形的效用函数 ,给出了显式的最优投资决策 .

关键词：最优投资组合绝对风险厌恶(HARA) HJB方程

Translation of steel surface defect detection algorithm with fusion of multiple attention detection heads

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Optoelectronics Letters 2025年

作者： shi tao CUI Jie LI Song Tianjin University of Technology， School of Electrical Engineering and Automation North China University of Science and Technology， School of Electrical Engineering

This paper proposes an end-to-end defect detection algorithm model called YOLOv5-CJ to address the issues of missed detections and low accuracy in visual steel surface defect detection. By incorporating the C3＿MSBlock module， which is designed based on Res2Net and contains multi-scale information， into the backbone network， the model can represent multi-scale features at a finer granularity level and increase the network's receptive field. In the detection head， the DyHead attention mechanism is introduced， which integrates scale awareness， spatial awareness， and task awareness， to help the model better cope with complex industrial scenes with large background interference， significant defect scale variations， and easily confused defect categories. Soft NMS is employed to enhance the recognition capability in overlapping regions. Experimental results demonstrate that the proposed YOLOv5-CJ model outperforms YOLOv5s，achieving an average precision (mAP0.5 and mAP0.5:0.95) improvement of 1.9% and 7.2% on the NEU-DET dataset， and 5.3% and 4.3% on the GC10-DET dataset， respectively， validating the feasibility and effectiveness of the proposed model.

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OLAP中基于FP-增长的关联规则挖掘

计算机科学 2004年第4期31卷 113-116,122页

作者：阎星娥鞠时光蔡涛辛燕江苏大学镇江212013

关联规则挖掘是一种发现属性间关系的方法,主要用于在商务事务记录中挖掘事务间关系。本文将已经广泛使用的FP-增长(frequent-pattern growth,频繁模式增长)算法进行改进,实现了OLAP中的关联规则挖掘。改进算法分别针对单维、多维、混... 详细信息

关联规则挖掘是一种发现属性间关系的方法,主要用于在商务事务记录中挖掘事务间关系。本文将已经广泛使用的FP-增长(frequent-pattern growth,频繁模式增长)算法进行改进,实现了OLAP中的关联规则挖掘。改进算法分别针对单维、多维、混合维三种关联规则,将多维立方体转化成不同的关系表,通过关系表产生关联规则,并利用立方体中的事实值作为进一步约束,生成了更有价值的规则。

关键词：数据挖掘关系数据库事务数据库关联规则 OLAP

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点击流中事务数据模型的设计与实现

计算机科学 2003年第7期30卷 73-76页

作者：辛燕鞠时光蔡涛阎星娥江苏大学镇江212013

In this paper, we first briefly introduce the concepts of clickstream data and data warehouse, analyze twoexisting clickstream star schema click star schema and session star schema in webhouse, then induce a new mod-el transaction star model based on them, and expressed the method of bringing out the model. Comparing withthe two schemas mentioned above, its most apparent speciality is that it includes a series of meaningful page-view se-quence rather than a single click. Thus, on the one hand it improves the query performance of data, on the other handit is in favor of executing more deepen analysis data mining, and simplifies the process of data pretreatment. Atlast ,the paper verifies its' feasibility and validity using association rules based on the model.

关键词：数据仓库数据模型数据挖掘数据库事务数据模型设计点击流数据

Steel surface defect detection based on lightweight YOLOv7

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Optoelectronics Letters 2025年

作者： shi tao Wu Rongxin Zhu Wenxu Ma Qingliang School of Electrical Engineering and Automation， Tianjin University of Technology North China University of Science and Technology， College of Electrical Engineering guangzhou Institute of Measurement and Testing Technology

Aiming at the problems of low detection efficiency and difficult positioning of traditional steel surface defect detection methods， a lightweight steel surface defect detection model based on YOLOv7 is proposed. First， a CSS Block module is proposed， which uses more lightweight operations to obtain redundant information in the feature map， reduces the amount of computation， and effectively improves the detection speed. Secondly， the improved SPPCSPC structure is adopted to ensure that the model can also pay attention to the defect location information while predicting the defect category information， obtain richer defect features. In addition， the convolution operation in the original model is simplified， which significantly reduces the size of the model and helps to improve the detection speed. Finally， using EIOU Loss to focus on high-quality Anchors， speed up convergence and improve positioning accuracy. Experiments were carried out on the NEU-DET steel surface defect dataset. Compared with the original YOLOv7 model， the number of parameters of this model was reduced by 40%， the FPS reached 112， and the average accuracy reached 79.1%.， the detection accuracy and speed have been improved， which can meet the needs of steel surface defect detection.

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EBD-YOLO：a lightweight auxiliary driving detection algorithm based on YOLOv5

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Optoelectronics Letters 2025年

作者： SUN Lianshuai shi tao DING Yao LI Song Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems， School of Electrical Engineer-ing and Automation， Tianjin University of Technology College of Electrical Engineering， North China University of Science and Technology

A lightweight road-assistant detection algorithm， EBD-YOLO， based on YOLOv5s is proposed to address the problems of high model complexity， computation cost， and difficulty in deployment on resource-limited embedded terminals in existing assisted driving detection algorithms. First， lightweight Transformer model EfficientViT was used as the backbone feature extraction network of YOLOv5s model to reduce network parameters and calculation costs. Secondly， a Focal-GIoU Loss function is proposed for bounding box regression to accelerate model convergence and reduce loss. Thirdly， the feature pyramid structure is improved to a weighted bi-directional feature pyramid network (BiFPN) to enhance localization and semantic features. Then， a dynamic head framework is added to unify the attention mechanism with the object detection head to improve its performance. Finally， a Soft-CIoU＿NMS algorithm is proposed in the post-processing stage to enhance occluded targets' localization and detection ability and reduce the missed detection rate. We conducted experiments on the KITTI and BDD100K datasets for autonomous driving， and the results showed that the EBD-YOLO model reduced in size by 38.4% and 37.2%， respectively. In comparison， the computational cost was reduced by 48.1%. As measured by mAP@0.5， the detection accuracy improved by 0.5% and 5.8%， respectively， and mAP@0.5:0.95 improved by 2.8% and 7%， respectively. These improvements satisfied the requirements for deployment on embedded terminals in cars.

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Near-infrared organic photosensitizers with aggregation-induced emission and switchable fluorescence for fungal infection therapy

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Science China Chemistry 2025年

作者： Xinzhe Yang Zixuan Huang Keke Ding Huili Yang Lirong Wang Qing Xia Rong Hu guang shi Bingjia Xu Anjun Qin School of Chemistry South China Normal University State Key Laboratory of Luminescent Materials and Devices Guangdong Provincial Key Laboratory of Luminescence from Molecular Aggregates Center for Aggregation-Induced Emission AIE Institute South China University of Technology Department of Urology The First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College) School of Chemistry and Chemical Engineering University of South China

The development of near-infrared (NIR) photosensitizers with aggregation-induced emission (AIE) properties,switchable luminescence colors,and satisfactory photodynamic therapy (PDT) effects on the treatment of fungal infection is of great importance but very ***,two ionic organic luminogens are constructed by employing diphenylamine,diphenylacrylonitrile/1,2-diphenylethene,and methylated quinoline cation as building *** is found that the resulting compounds TCQF and TQF show apparent AIE properties and produce intense fluorescence with high photoluminescence quantum yields of up to 31.2%in the solid *** the meantime,their emission colors can be switched between red and NIR and in the NIR region by mechanical force and solvent vapor,respectively,thereby enabling remarkable and reversible mechanochromism with emission variations of up to 104 *** excitingly,TCQF and TQF can efficiently generate ROS under the illumination of white light and show excellent antimicrobial activities and satisfactory PDT *** by the unique anti-fungus properties,TCQF is employed as a biocompatible NIR photosensitizer for treating wound infection with ***,and apparent PDT effects are *** work provides a new direction for the development of multifunctional NIR materials with AIE properties.

关键词：

云南元谋不同海拔土壤微生物对车桑子碳、氮、磷化学计量特征及土壤特性的影响

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植物生态学报 2017年第3期41卷 311-324页

作者：王雪梅闫帮国赵广史亮涛刘刚才方海东中国科学院水利部成都山地灾害与环境研究所中国科学院山地表生过程与生态调控重点实验室成都610041 中国科学院大学北京100049 云南省农业科学院热区生态农业研究所云南元谋651300

了解不同气候下土壤微生物对植物生态化学计量特征的影响有利于理解未来温度变化下植物与土壤的相互关系。该文以车桑子(Dodonaea viscosa)为研究对象,从云南省元谋县两个海拔区采集车桑子根际土壤样品,并设定相应的两个温度处理,通过... 详细信息

了解不同气候下土壤微生物对植物生态化学计量特征的影响有利于理解未来温度变化下植物与土壤的相互关系。该文以车桑子(Dodonaea viscosa)为研究对象,从云南省元谋县两个海拔区采集车桑子根际土壤样品,并设定相应的两个温度处理,通过微生物灭菌和接种处理,测定了车桑子叶片养分及其所在的土壤特性,研究了温度、微生物及温度与微生物的交互作用对车桑子的碳(C)、氮(N)、磷(P)化学计量特征的影响,分析其N、P养分特征与土壤特性间的关系。研究结果表明:相比于灭菌处理,两个海拔区的土壤微生物对车桑子养分吸收都有促进作用,对P的促进作用极为显著。温度对车桑子C、N、P化学计量特征无显著影响,但温度与微生物的交互作用对车桑子的C、N、P化学计量特征有显著影响。这种交互作用主要体现在:在接种高海拔区土壤微生物的处理中,温度没有显著影响车桑子的C、N、P化学计量特征,而在接种低海拔区土壤微生物的处理中,相比于高温条件,低温显著抑制了车桑子对N、P的养分吸收。土壤微生物对养分吸收的促进作用可能源于其中有益微生物(如丛枝菌根真菌)的直接促进作用,而并非是通过土壤微生物的养分循环过程。由于接种微生物处理使车桑子从土壤中吸收了更多的N、P,从而使该处理的土壤有效N、P显著低于灭菌处理。在元谋干热河谷未来气温变凉的情况下,由于土壤微生物对植物的反馈作用,该区车桑子的生长可能会受到一定的抑制。

关键词：生态化学计量土壤微生物植物-土壤反馈气候变化车桑子