Radiographic Equipment and Accessories as a Potential Source of Nosocomial Infection

Background: Nosocomial infections have become a major challenge in healthcare facilities as they affect the quality of medical care. Radiological imaging plays a crucial role in medical diagnosis. However, the equipment and accessories used increase the risk of transmission of nosocomial bacteria. Objective: This study aims to reveal the extent and nature of microbiological contamination in four hospital diagnostic imaging departments to determine their potential role in the spread of nosocomial bacteria and to evaluate the effectiveness of routine daily disinfection practices in controlling microorganisms in diagnostic imaging departments. Methods & Results: In each department, swabs were taken from the surfaces of selected parts of the equipment and accessories three times a day (early morning, noon, and evening) for five consecutive days. Bacteria were isolated from 65 swabs (36.1% of all samples). The bacteria were isolated 3 times (4.6%) in the morning, 16 times (24.6%) at midday, and 46 times (70.7%) in the evening. The bacteria isolated were Escherichia coli (isolated 34 times;52.3%), Staphylococcus aureus (20 times;30.8%), Staphylococcus epidermidis (6 times;9.3%), and Klebsiella species (5 times;7.7%). Discussion & Conclusion: Findings demonstrated that radiology equipment and accessories are not free of bacteria and further improvements in the sterilization and disinfection of radiology equipment and accessories are needed to protect staff and patients from nosocomial infections.

Automatic infrared image recognition method for substation equipment based on a deep self-attention network and multi-factor similarity calculation

Infrared image recognition plays an important role in the inspection of power equipment.Existing technologies dedicated to this purpose often require manually selected features,which are not transferable and interpretable,and have limited training data.To address these limitations,this paper proposes an automatic infrared image recognition framework,which includes an object recognition module based on a deep self-attention network and a temperature distribution identification module based on a multi-factor similarity calculation.First,the features of an input image are extracted and embedded using a multi-head attention encoding-decoding mechanism.Thereafter,the embedded features are used to predict the equipment component category and location.In the located area,preliminary segmentation is performed.Finally,similar areas are gradually merged,and the temperature distribution of the equipment is obtained to identify a fault.Our experiments indicate that the proposed method demonstrates significantly improved accuracy compared with other related methods and,hence,provides a good reference for the automation of power equipment inspection.

Real-time parameters monitoring system for underground equipment based on panoramic images

Complex terrain and working equipment in coal mine underground need a way to ensure coal mine safety. In this paper, the way to monitor the real-time status of underground equipment was put forward, and it was proved to be effective as commanding and dispatching system. Monitoring system for underground equipment based on panoramic images was effectively combined with real-time sensor data and static panoramic images of underground surrounding, which not only realizes real-time status monitoring for underground equipment, but also gets a direct scene for underground surrounding. B/S mode was applied in the monitoring system and this is convenient for users to monitor the equipment. Meantime, it can reduce the waste of the data resource.

Opening and Sharing of Large-scale Instruments and Equipment in Agricultural Research Institutes:A Case Study of Environment and Plant Protection Institute of Chinese Academy of Tropical Agricultural Sciences

The article introduces the main practices and achievements of the Environment and Plant Protection Institute of Chinese Academy of Tropical Agricultural Sciences in promoting the sharing of large-scale instruments and equipment in recent years,analyzes the existing problems in the management system,management team,assessment incentives and maintenance guarantee,and proposes improvement measures and suggestions from aspects of improving the sharing management system,strengthening management team building,strengthening sharing assessment and incentives,improving maintenance capabilities and expanding external publicity,to further improve the sharing management of large-scale instruments and equipment.

Research of Personnel Operational Ability Evaluation of Large-scale Complex Equipment

The level of personnel operation ability determines the expected effectiveness of large-scale complex equipment. Firstly, this paper constructs the personnel operational ability evaluation index system and analyzes the data source of index. Secondly, the weight of index is determined and the fuzzy comprehensive evaluation model is proposed. Finally, results of instance analysis show that the evaluation model is feasible and effective.

Industrial Equipment Troubleshooting with Imaging Technique Improved Gamma-Ray Absorption Scans

Gamma scanning is one of the most common nuclear techniques on troubleshooting industrial equipments like distillation columns and reactors. With a very simple concept, the technique is easy to implement. Searching for a competitive edge the industry has been long developing solutions to achieve better results. On the last decades, significant development has been done with the advent of new equipments, electronics, portable computers and software. Continuous scanning and wireless detection systems are examples of successful field solutions, while new software aid on reporting and data presentation. However the type and quality of the results itself has not dramatically changed since its beginning. A scan profile is simple to understand, although the process to build it can be very complex as it requires a specific blend of knowledge and abilities. Process engineering, chemical engineering, internal hydraulic project, nuclear engineering and field abilities are pre requisites for of any scan specialist. Correct data gathering, interpretation and reporting are abilities often difficult to match or requires a long time of training. The industry faces a similar difficult on the customer side, as it is always necessary to train end users to understand a report and how to use its best. This paper describes our effort on developing a new approach on the gamma scan test using image reconstruction techniques that would result on a graphic image rather than a XY plot. Direct and easier to understand, a report with graphic images would be also be accessible to a wider audience, not limited to the customers experienced with gamma scan interpretation.

Large-scale conditions of Tibet Plateau vortex departure

Based on the circumfluence situation of the out- and in-Tibet Plateau Vortex (TPV) from 1998–2004 and its weather-influencing system,multiple synthesized physical fields in the middle–upper troposphere of the out- and in-TPV are computationally analyzed by using re-analysis data from National Centers for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) of United States.Our research shows that the departure of TPV is caused by the mutual effects among the weather systems in Westerlies and in the subtropical area,within the middle and the upper troposphere.This paper describes the large-scale meteorological condition and the physics image of the departure of TPV,and the main differences among the large-scale conditions for all types of TPVs.This study could be used as the scientific basis for predicting the torrential rain and the floods caused by the TPV departure.

Interactive mobile equipment safety task-training in surface mining

Improving the quality of equipment training for the Heavy Equipment Operators(HEO)is a critical task in improving safety and eliminating equipment-related injuries in mining.One of major responsibilities for the HEOs is proper machine inspection.Traditional miner safety training includes the use of hardcopy documents and video instructions.However,modern mobile and computer technology offers tremendous potential to improve the training process.In this study,we apply a 360-degree camera,opensource platform WordPress^(TM),and the software Unity3D in order to create materials and tools for the HEOs safety training to help trainees better understand the pre-shift safety machine inspection.The computer-based safety task training developed in this research is tested and implemented at a surface mine in the southern United States.

True Image Server软件在医疗设备维修中的应用

本文比较了TrueImageServer软件与GHOST软件在应用上的差别。介绍了TrueImageServer软件在医疗设备维修中的使用方法。

Applied the Large Scale Particle Image Velocimetry Technique for Measurement the Velocity of Gravity Currents in the Laboratory

This study includes a series of laboratory experiments for investigated the gravity current of fresh water with density ρ-?ρ, and initial speed u0 upon the free surface of an ambient liquid (salty water) with density ρ at rest in a basin. It’s have been presented to illuminate the dominant flow and transport phenomena in the presence of river, stream and wetland ecology, stream corridor restoration, in the case of accidental pollution spills. The characterized of the local kinematic field, i.e. the local velocity and vorticity fields, the measurement methods include particle image velocimetry (PIV) at the water surface using a technique similar to large scale of particle image velocimetry (LSPIV).

Multi-Index Image Retrieval Hash Algorithm Based on Multi-View Feature Coding

In recent years,with the massive growth of image data,how to match the image required by users quickly and efficiently becomes a challenge.Compared with single-view feature,multi-view feature is more accurate to describe image information.The advantages of hash method in reducing data storage and improving efficiency also make us study how to effectively apply to large-scale image retrieval.In this paper,a hash algorithm of multi-index image retrieval based on multi-view feature coding is proposed.By learning the data correlation between different views,this algorithm uses multi-view data with deeper level image semantics to achieve better retrieval results.This algorithm uses a quantitative hash method to generate binary sequences,and uses the hash code generated by the association features to construct database inverted index files,so as to reduce the memory burden and promote the efficient matching.In order to reduce the matching error of hash code and ensure the retrieval accuracy,this algorithm uses inverted multi-index structure instead of single-index structure.Compared with other advanced image retrieval method,this method has better retrieval performance.

基于真实世界数据的大型影像设备资源配置模型的构建与分析

目的构建基于真实世界数据(Real World Data,RWD)的计算机断层扫描(Computed Tomography,CT)、磁共振成像(Magnetic Resonance Imaging,MRI)设备的资源配置模型,以优化公立医院大型影像设备的配置问题。方法选取我院2018年1月至2023年12月医学影像科CT、MRI设备作为研究对象,使用年投资收益率指标分级评价设备的经济效益,然后采用Pearson相关系数法分析医院门诊人次、出院人次、CT/MRI设备检查量与时间的相关性,最后构建基于数据拟合与回归分析的配置预测模型并进行分析评价。结果CT和MRI设备检查量与住院人次的Pearson相关系数r分别为0.557和0.851(P<0.01),住院人次、CT和MRI设备检查量与月份的r分别为0.415、0.559和0.731(P<0.01),相关性强。通过数据拟合与回归分析得到三次配置拟合模型更符合我院实际情况,在未来3年内至少需要增配1台CT和2台MRI设备以顺应医院高速发展需求。结论构建基于RWD的CT、MRI设备的资源配置模型,有效地优化了大型影像设备的配置规划,为公立医院配置大型影像设备提供决策依据。

基于YOLOv5s和Android部署的电气设备识别

针对变电站多种电气设备实时检测的需求,提出了一种基于改进YOLOv5s的电气设备识别方法,并设计基于Android部署的电气设备识别APP,以便对电气设备进行识别与学习。以电力变压器、绝缘子串等6种常见变电站电气设备为例构建图像数据集。数据集进行图像预处理后对YOLOv5s算法进行改进。通过引入C2f模块提高小目标检测精度,采用Soft-NMS提高检测框筛选能力,减少漏检和误检的情况,使用改进后的算法对数据集进行模型训练。将训练好的识别网络模型通过TensorFlow Lite框架进行模型部署,设计电气设备识别APP。经验证,改进后的变电站电气设备识别网络模型mAP稳定在91.6%,与原模型相比提高了3.3百分点。部署后的APP具有设备识别和设备介绍等界面,使用移动端进行识别时每张图片识别时间都小于1 s,具有较快的识别速度和较高的识别精度,可以高效地实现变电站电气设备的实时检测与设备学习。

基于自适应特征融合和注意力机制的变电设备红外图像识别

针对变电设备红外图像复杂背景下多目标、小目标及遮挡目标识别效果差的问题,该文提出一种基于中心点网络(CenterNet)的变电设备红外图像识别方法。通过将自适应特征融合模块(ASFF)和特征金字塔(FPN)相结合,构建ASFF+FPN结构的特征融合网络,增强了模型对多目标和小目标的跨尺度特征融合能力,排除背景信息;针对网络对遮挡目标特征捕捉能力差的问题,在特征融合网络中添加全局注意力机制,增强目标显著度;为实现模型轻量化,引入深度可分离卷积,减少参数量和推理时间;最后,通过引入分布焦点损失函数,克服了原损失函数对遮挡目标敏感性差的问题,提升了模型收敛速度和识别精度。在包含7种红外变电设备图像的自建数据集上进行测试。实验表明该算法与原始算法相比,识别精度提升了3.55%,达到了95.19%,模型参数量仅为32.52M,与4种主流目标识别算法对比,该算法在识别精度和算法复杂度上具有明显优势。

放射影像设备的质控管理及维修分析

临床对放射影像设备进行质控管理的预期目标是在符合行业的标准要求下,采用适当的影像检查技术条件为临床提供优质的图像信息。我院1.5T MRI设备于2015年10月开始使用,虽然该设备已使用了8年,经过持续而严格的质控,使该设备的各项技术指标依然保持在较好状态,不但满足了正常的工作需求,而且保持了较低的故障率。设备的良好运转、医务人员准确的技术应用,以及患者的最佳配合才能得到优质的影像图像。对于放射影像设备的质量控制,其覆盖了设备的整个使用周期,且质量控制的过程也是设备在整个使用周期中的运行流程。只有通过科学的手段,强化和优化放射影像设备的质量控制,提升设备的使用效率,才能为临床诊断提供有效的技术支持。同时及时的维修和独立的解决问题既能保证诊疗的正常进行,还能给医院节省资金。因此,优秀的技术能力加上严格规范的质控管理是我院影像设备安全运行的最好保证。

医学影像设备维修管理中存在的问题及解决方法

在现代医疗环境中,医学影像设备的维修管理是一个关键环节,其效率和准确性直接影响到医疗机构的运营和患者的治疗效果。本文以医学影像设备的维修管理为切入点,详细分析了常见的设备以及故障类型,以及目前存在的问题,并提出了针对这些问题的解决办法,旨在优化医学影像设备的维修管理,提高医疗服务的质量和效率。

基于YOLOv8的气象设备识别监控算法

在人烟稀少的地区,气象设备的监测与检查面临设备安置位置偏僻、缺乏实时巡检等问题。为解决这一难题,基于在图像识别领域表现卓越的YOLOv8算法,提出了一种新的气象设备识别监控模型,通过将原有的高效的空间金字塔池化(spatial pyramid pooling-fast,SPPF)层替换为空间金字塔池化-全连接空间金字塔卷积(spatial pyramid pooling-fully connected spatial pyramid convolution,SPPFCSPC)层,成功降低了计算量,提升了气象设备检测的速度。为了进一步提升模型在复杂环境下的性能,提出了YOLOv8-SA模型,通过在主干网络(backbone)中加入多头自注意力机制,更精准地捕获图像中不同区域之间的关联性,有力地提高了模型的准确性。为了验证模型的有效性,创建了一个专门的气象设备数据集,并进行了对比实验。实验结果表明,本文提出的YOLOv8-SA模型在检测速度和准确性方面均取得了显著的提升,在自制的数据集中检测精度为98.6%,与传统的YOLOv8模型相比,检测精度提升了0.6%。该模型可有效解决人烟稀少地区气象设备的监测问题,为提升监测系统的实用性和效率提供新思路。

V-SHEL风险管理模型在医学影像设备故障中的应用研究

目的 探讨V-SHEL风险管理模型在降低NMR、CT和DSA等医学影像设备故障发生风险的应用效果。方法 选取某医院2020—2021年临床科室正常运行使用的15台医学影像设备,将2020年采用日常传统管理方法归入对照组;将2021年采用V-SHEL风险管理模式纳入研究组。比较两个组别的合格率、故障率和设备使用人员满意度。结果 研究组设备合格率高于对照组,故障率低于对照组,设备自身原因产生故障率高于对照组,差异有统计学意义(P<0.05)。研究组设备整洁及规范度、运行性能和及时性满意度评分高于对照组,差异有统计学意义(P<0.05)。结论 V-SHEL风险管理模型可降低医学影像设备故障率,提高设备使用满意度。

基于纹理特征的钢渣沥青路面抗滑性能测试与评价

沥青路面的抗滑性能快速下降一直是各国学者高度关注的问题。随着表面纹理逐渐磨损,沥青路面的抗滑性能也持续减弱。为了能更科学地评估和预测路面抗滑性能的衰减,有必要定量地建立起路面纹理和抗滑性能之间的关系。本研究采用了小型加速加载设备、高精度三维扫描设备以及数字图像处理来模拟路面纹理的磨损过程。本研究基于三维纹理特征系统评价了沥青路面的抗滑性能衰减。研究结果显示,英国摆值(BPN)与本研究采用的评价指标三维纹理参数(Sq、Ssk、Vmp、Vmc和Vvc)之间存在着紧密的联系。随着加载次数的增加,BPN和三维纹理参数都呈现出相同的衰减趋势。这些三维纹理参数不仅可以作为评估沥青路面抗滑性能的指标,还能精确地描绘钢渣沥青路面的微观磨损机制。本研究建立的关系将有助于预测路面的抗滑衰减情况,为钢渣沥青路面的路用性能研究提供了有力的技术支持。

基于红外图像技术的运行设备热故障状态检测系统设计

变电站设备在发电过程中因老化与恶劣环境等因素的影响容易发生热故障,传统人工检测方法难度大且准确性低,提出基于红外图像的变电站设备热故障状态检测系统设计。硬件设计上,由红外图像采集模块与地面服务模块组成系统整体架构。软件设计上,采用串并联扫描方式采集变电站设备的红外图像,通过均值滤波法与直方图均衡化算法预处理原始采集的红外图像,基于红外图像的相对温差法完成热故障状态检测。最后通过对变电站常见设备进行热故障状态检测试验,验证了设计系统的可行性与可靠性。