I-DCGAN and TOPSIS-IFP:A simulation generation model for radiographic flaw detection images in light alloy castings and an algorithm for quality evaluation of generated images

The intelligent detection technology driven by X-ray images and deep learning represents the forefront of advanced techniques and development trends in flaw detection and automated evaluation of light alloy castings.However,the efficacy of deep learning models hinges upon a substantial abundance of flaw samples.The existing research on X-ray image augmentation for flaw detection suffers from shortcomings such as poor diversity of flaw samples and low reliability of quality evaluation.To this end,a novel approach was put forward,which involves the creation of the Interpolation-Deep Convolutional Generative Adversarial Network(I-DCGAN)for flaw detection image generation and a comprehensive evaluation algorithm named TOPSIS-IFP.I-DCGAN enables the generation of high-resolution,diverse simulated images with multiple appearances,achieving an improvement in sample diversity and quality while maintaining a relatively lower computational complexity.TOPSIS-IFP facilitates multi-dimensional quality evaluation,including aspects such as diversity,authenticity,image distribution difference,and image distortion degree.The results indicate that the X-ray radiographic images of magnesium and aluminum alloy castings achieve optimal performance when trained up to the 800th and 600th epochs,respectively.The TOPSIS-IFP value reaches 78.7%and 73.8%similarity to the ideal solution,respectively.Compared to single index evaluation,the TOPSIS-IFP algorithm achieves higher-quality simulated images at the optimal training epoch.This approach successfully mitigates the issue of unreliable quality associated with single index evaluation.The image generation and comprehensive quality evaluation method developed in this paper provides a novel approach for image augmentation in flaw recognition,holding significant importance for enhancing the robustness of subsequent flaw recognition networks.

Comprehensive Detection and Analysis of Defects in Foundation Pile of Bridge

In the process of piling ,there are many various defects in foundation pile of bridge such as mud-bearing,sediment-bearing, isolation, honeycomb, broken piles, and so on, showing physical and mechanical features of low-density and low-intensity. In fact, by using the comprehensive detection of acoustic transmission method, the reflected wave method as well as drill coring sample method, and the rational utilization of engineering geological condition in field, the characteristics, size and location of common defects of foundation pile of bridge can be accurately detected and judged and the integrity of piles and the quality of concrete can be impersonally estimated.comprehensive detecting and analyzing methods on this kind of piles are introduced briefly. The physical characters of defects and basic features of detecting curves and their corresponding relation are emphasized, and causes are analyzed in in detail in this paper.

Stream-computing of High Accuracy On-board Real-time Cloud Detection for High Resolution Optical Satellite Imagery

This paper focuses on the time efficiency for machine vision and intelligent photogrammetry, especially high accuracy on-board real-time cloud detection method. With the development of technology, the data acquisition ability is growing continuously and the volume of raw data is increasing explosively. Meanwhile, because of the higher requirement of data accuracy, the computation load is also becoming heavier. This situation makes time efficiency extremely important. Moreover, the cloud cover rate of optical satellite imagery is up to approximately 50%, which is seriously restricting the applications of on-board intelligent photogrammetry services. To meet the on-board cloud detection requirements and offer valid input data to subsequent processing, this paper presents a stream-computing of high accuracy on-board real-time cloud detection solution which follows the “bottom-up” understanding strategy of machine vision and uses multiple embedded GPU with significant potential to be applied on-board. Without external memory, the data parallel pipeline system based on multiple processing modules of this solution could afford the “stream-in, processing, stream-out” real-time stream computing. In experiments, images of GF-2 satellite are used to validate the accuracy and performance of this approach, and the experimental results show that this solution could not only bring up cloud detection accuracy, but also match the on-board real-time processing requirements.

Design of comprehensive test system for detecting overlying strata mining-induced fractures on surface with radon gas

Based on radon gas properties and its existing projects applications, we firstly attempted to apply geo- physical and chemical properties of radon gas in the field of mining engineering, and imported radioac- tive measurement method to detect the development process of the overlying strata mining-induced fractures and their contained water quality in underground coal mining, which not only innovates a more simple-fast-reliable detection method, but also further expands the applications of radon gas detection technology in mining field. A 3D simulation design of comprehensive testing system for detecting strata mining-induced fractures on surface with radon gas (CTSR) was carried out by using a large-scale 3D solid model design software Pro/Engineer (Pro/E), which overcame three main disadvantages of ''static design thought, 2D planar design and heavy workload for remodification design'' on exiting design for mining engineering test systems. Meanwhile, based on the simulation design results of Pro/E software, the sta- bility of the jack-screw pressure bar for the key component in CTSR was checked with a material mechan- ics theory, which provided a reliable basis for materials selection during the latter machining process.

Fuzzy recognition of missile borne multi-line array infrared detection based on size calculating

In order to improve the infrared detection and discrimination ability of the smart munition to the dynamic armor target under the complex background,the multi-line array infrared detection system is established based on the combination of the single unit infrared detector.The surface dimension features of ground armored targets are identified by size calculating solution algorithm.The signal response value and the value of size calculating are identified by the method of fuzzy recognition to make the fuzzy classification judgment for armored target.According to the characteristics of the target signal,a custom threshold de-noising function is proposed to solve the problem of signal preprocessing.The multi-line array infrared detection can complete the scanning detection in a large area in a short time with the characteristics of smart munition in the steady-state scanning stage.The method solves the disadvantages of wide scanning interval and low detection probability of single unit infrared detection.By reducing the scanning interval,the number of random rendezvous in the infrared feature area of the upper surface is increased,the accuracy of the size calculating is guaranteed.The experiments results show that in the fuzzy recognition method,the size calculating is introduced as the feature operator,which can improve the recognition ability of the ground armor target with different shape size.

Mural Defects Detection with Enhanced Terahertz Images

In mausoleum murals, existing bubbles are one kind of the most harmful defects for the repair and protection of relics. For this reason, it is necessary to detect bubbles, especially the ones with small size. A method to detect the small bubbles with enhanced terahertz （THz） images is proposed. To simulate the bubbles in the mausoleum murals, circular grooves have been hidden in the plaster and then measured by the THz reflected time domain spectroscopy imaging system. To observe the small bubbles in murals, a comprehensive enhancement algorithm is adopted to process the obtained THz images. With the enhanced method, the circular grooves in the murals can be observed clearly, even for the circular groove with a diameter of 1.5 mm. The results indicate that the proposed comprehensive method can be used to detect the tiny defects of murals.

应用综合干预措施对促进住院患者抗菌药物治疗前病原学送检的效果评价

目的探讨应用综合干预措施对促进住院患者抗菌药物治疗前病原学送检的效果。方法选取2020年1月—2021年12月某三甲医院治疗性使用抗菌药物的住院患者为研究对象,2021年1月开始实施综合干预措施,比较干预前组(2020年1—12月)和干预后组(2021年1—12月)抗菌药物治疗前病原学送检率、送检分类和重点监管科室送检率。结果共纳入治疗性使用抗菌药物的住院患者10239例,其中干预前组4526例,干预后组5713例。干预后的抗菌药物治疗前、限制级抗菌药物治疗前、特殊级抗菌药物治疗前病原学送检率分别为94.56%、94.72%、96.03%,高于干预前的83.74%、84.47%、84.95%,差异均有统计学意义(均P<0.05)。干预后的指向性病原体送检率为64.87%,高于干预前的28.04%,差异均有统计学意义(均P<0.05)。干预后的重症医学科、呼吸与危重症医学科、儿科、神经外科和普通外科治疗性使用抗菌药物病原学送检率分别为93.20%、91.17%、92.20%、94.12%、91.15%,高于干预前的85.00%、82.19%、83.20%、83.33%、83.03%,差异均有统计学意义(均P<0.05)。结论应用综合干预措施可提高住院患者抗菌药物治疗前病原学送检率,应密切关注医院感染诊断相关病原学送检指标和无菌体液送检指标。

软件运行时配置研究综述

运行时配置为用户使用软件提供了灵活性和可定制性,但其巨大的规模和复杂的机制也带来了巨大的挑战.大量学者和研究机构针对软件运行时配置展开了研究,以提升软件系统在复杂外部环境中的可用性和适应性.建立运行时配置研究分析框架,从配置分析与理解、配置缺陷检测与故障诊断、配置应用3个阶段对现有研究工作进行归类和分析,总结归纳现有研究的不足和面临的挑战,并对未来的研究趋势进行展望,对下一步研究具有一定的指导意义.

荧光探针合成与可视化检测三硝基苯酚综合实验开发

根据待测物2,4,6-三硝基苯酚(TNP)的性质,以香豆素为荧光团、噻二唑为识别基团,调整共轭体系和电子流向,设计具有绿色荧光的有机小分子探针,实现特异性检测与可视化识别。引导学生深入探索化学学科的内在联系,掌握基础知识的同时了解学科领域发展。设置智能手机检测模块,将科学研究与日常生活紧密联接,拉近学生与科学研究的距离,激发学生探索创新的意识。

城市轨道交通新型检测技术及应用浅析

城市轨道交通的高质量发展对检测技术的安全性、可靠性、实时性、标准化和集成化等提出了更高的要求。激光检测技术、机器视觉检测技术、超声检测技术和红外检测技术等新型技术的出现和应用,很好地弥补了传统检测技术的不足,满足了城市轨道交通现阶段检测技术的需求。双轨机器人、检测管理平台、主动预警系统及非接触检测等方法在不同场景应用,给城市轨道交通新型检测技术的推广提供了支持。本文通过综合分析,预测综合性、基于信息化、智能化、主动检测及动态与非接触检测相结合等将成为城市轨道交通新型检测技术的方向发展。

“三全育人”视角下高职《药物残留检测技术》课程教学探索与实践

课程思政是新时代中国高等教育的理论创新与实践创新,是构建全员、全程、全方位育人即“三全育人”格局的有力抓手。依托高职院校药品质量与安全专业群建设,对《药物残留检测技术》课程思政育人的必要性、存在问题和教学改革进行研究,探索通过设立体系化的课程思证目标、优化课程思政教学设计、提升专业课教师课程思政教学能力、建立科学实效性的课程思政教学质量评价体系充分发挥课堂教学的育人功能,促进高职院校专业教育与政治思想教育同向同行。

视频人像检验鉴定综合实验设计

为了更好地讲授视频人像检验鉴定的原理和方法,本文设计了视频人像检验鉴定综合实验系统,实现了视频中人脸检测与定位、图像预处理、特征提取和人像比对。系统使用警视通软件的辅助功能对检材和样本进行多种方法的人像标注和检验鉴定,学生可根据实验比对的结果对检材和样本中存在的多个相似点和差异点进行剖析,从而完成人像检验鉴定的全过程。该综合实验系统的设计不仅有助于学生对人像检验鉴定相关原理的理解,还可以提升学生的科研素养和实战能力,激发学生对视频图像侦查技术的学习兴趣。

隧道综合巡检机器人设计及研究

为解决城轨隧道病害检测采集的问题,设计了一台隧道综合巡检机器人。对机器人的实现功能进行规划与设计,确定实现方式,并使用SolidWorks软件设计并建立机器人不同模块的结构模型;对底盘驱动模块进行电机计算与校核,利用ANSYS Workbench对底盘进行有限元静力学分析;对机器人样机进行生产加工组装,并在真实隧道环境中进行测试实验。实验测试结果表明,机器人结构与控制部分设计合理,可实现对隧道内壁与道床的病害数据采集,机器人运动性能达到预期的目标。

一种新型铜离子比色探针在实验教学中的应用

新型比色探针H-6的合成、表征及对铜离子的快速检测,是由科研转化而来的本科化学综合实验项目。该实验通过分子设计、有机合成,红外、核磁和质谱表征,以及紫外特性分析、实际应用和密度泛函理论(DFT)计算探针识别机理等全流程教学,提升了学生的实验技能和科研素养,激发了创新意识。该实验将有机化学、无机分析、材料科学、仪器分析等多学科交叉融合,强化了实验教学的系统性和应用性。将新型比色探针检测手段科研成果融入本科实验教学的思路与理念对推动实验教学改革有借鉴意义。

基于语义拼写理解和门控注意力机制的不良言论检测

如何自动检测网络传播的不良言论信息是自然语言处理研究领域的热门研究内容之一。针对不良言论中语义表达和拼写习惯的特点,提出一种基于语义拼写理解和门控注意力机制的不良言论检测方法。该方法采用自注意力机制获取文本的语义特征,采用卷积神经网络提取文本的拼写特征,采用前期特征融合和门控注意力机制相结合的方式融合语义和拼写特征。在两个公共数据集上的实验结果表明,提出的模型能够有效地提取不良言论的语义特征,提高不良言论检测的性能。

基于关系增强图卷积网络的机器阅读理解式事件检测

在面对具有复杂句法关系的长文本上下文时,现有机器阅读理解式事件检测模型难以挖掘关键词之间长距离依赖关系。针对上述问题,提出一种基于关系增强图卷积网络(REGCN)的机器阅读理解式事件检测模型(MRCREGCN)。首先,利用预训练语言模型对问题和文本进行联合编码,得到融入先验信息的单词向量表示;其次,引入动态的关系增强标签信息,并利用REGCN深入学习单词之间的句法依存关系,增强模型对长文本句法结构的感知能力;最后,利用多分类器得到文本单词在所有事件类型下的概率分布。在ACE2005英文语料上的实验结果表明,所提模型在触发词分类上的F1分值相较于同类机器阅读理解模型EEQA(Event Extraction by Answering(almost)natural Questions)和最佳基线模型DEGREE(Data-Efficient GeneRation-based Event Extraction)分别提升了2.49%和1.23%,验证了MRC-REGCN具有更好的事件检测性能。

樱桃根癌病研究进展

樱桃根癌病由土壤农杆菌引起,主要通过伤口侵染,促使植株细胞产生过量的生长激素,从而形成瘤状物,影响植株的营养吸收,进而降低樱桃产量和品质。综述了樱桃根癌病的发病症状、病原菌分类、病原菌基因组信息,阐述了病原菌的发病机制及对该病的综合防治方法,为樱桃根癌病的后期研究及防治提供参考。

铜碘簇合物的制备及荧光检测亚硝酸盐——推荐一个综合化学设计性实验

为培养学生的科研思维及创新能力,加深学生对无机簇合物概念及荧光性能的认识与理解,设计开发了铜碘簇合物的制备及荧光检测亚硝酸盐的综合性实验。利用纳米沉淀的方法合成铜碘簇合物,通过红外光谱、X射线粉末衍射、扫描电子显微镜、紫外光谱、荧光光谱等分析手段对材料进行结构及性能表征,考察材料的荧光及检测亚硝酸盐的性能。结果表明:材料对亚硝酸盐具有高选择、高灵敏检测,检出限为3.73μmol·L^(-1),可作为监测亚硝酸盐的“开‐关”荧光探针。通过该实验,学生不仅对簇合物的结构及荧光分析法检测亚硝酸盐等前沿知识加深理解,还可学习紫外分析仪、荧光分光光度计等仪器的基本原理及操作技能,为将来从事相关科研及工作奠定基础。

纳米材料与农残检测交叉融合综合实验设计

打破传统学科之间的壁垒,促进基础研究与应用研究相互衔接,实现多学科交叉融合,对于培养满足国家社会发展需求的复合型高层次创新人才具有重要意义。从纳米材料的制备出发,采用化学还原法获得了银纳米颗粒,结合XPS、SEM对其进行了物性表征。在此基础上,采用PERS-F700便携式拉曼检测仪,以贵金属纳米颗粒为增强剂,对红提表皮的倍硫磷进行拉曼快速检测,得出了标准的阳性检测结果。实验涵盖材料的制备、表征及实际应用,融合了材料、物理、化学、农业等专业的相关知识,具有典型的学科交叉特色,有利于锻炼学生的专业技能,提高学生的综合素养和科研创新能力。

隧道结构智能综合检测装备研制与应用

为解决隧道结构健康检测常规方式存在检测指标相对单一、机械化程度低、检测效率低、智能化水平低、安全风险高等突出问题,通过“非接触远距离检测”“表观病害智能检测与识别”“装备集成与智能控制”等关键技术研究与创新,研制出隧道结构智能综合检测装备,实现隧道结构内部病害、表观病害、结构形变等一体化综合检测。经工程验证,该装备可实现隧道衬砌厚度、背后空洞、钢拱架分布、衬砌裂缝、衬砌裂损、渗漏水、隧道断面及盾构法隧道椭圆度、管片错台等非接触高效综合检测,其综合作业效率为10~40 km/h,比常规检测方式提升2~8倍,检测方舱采用模块化设计,可搭载于轮式汽车底盘、轨道平板车等多种载体,适用于隧道建设施工过程中、竣工验收及运营期等多种工况,市场应用前景广阔。