汽轮机故障诊断的因果网络群智能算法模型

在利用概率因果网络模型进行汽轮机故障诊断过程中,传统的基于简约覆盖理论的求算方法不能直接得到诊断问题的解,而且当故障节点较多或网络层次较多时,存在着"组合爆炸"、计算量呈指数速度增加等问题;对此,基于群智能理论,建立汽轮发电机组故障诊断系统概率因果网络群智能算法模型,给出基本的群运算法则及改进方法,将焦点放在有限空间的诊断推理上,并实现并行处理,很好地解决了传统算法中的问题;最后一个应用实例验证了此方法的优越性及工程实用性。     

一种RBAC改进模型及其在军事Web信息系统中的应用

军事Web信息系统要求用户权限必须严格控制、统一管理、维护简便.基于RBAC的访问控制模型能有效弥补DAC和MAC的不足.针对著名的RBAC96模型的缺陷,提出数据资源以业务功能表示、预设角色与用户临时权限的改进角色权限控制模型.该改进方法已经在某军事Web信息系统中得到了应用.     

基于分数傅立叶变换的机载SAR多运动目标检测

机载合成孔径雷达（SAR）运动目标回波本质上为chirp信号,基于分数阶傅里叶变换（FRFT）的chirp基分解特性及分数阶傅立叶变换与时频分布的关系,给出了一种基于FRFT的针对强度相差较大的多运动目标检测方法。与传统的WVD方法相比,FRFT是一个线性变换,因此对于多个动目标就没有交叉项的干扰,简化了处理过程降低了处理复杂度。仿真结果验证了其有效性。     

基于Windows系统的木马程序隐蔽行径分析

文章介绍了特洛伊木马的基本概念、分类及特点。针对基于Windows系统的木马分别从木马运行形式、木马通信形式、木马启动方式、以及木马程序在宿主机磁盘上的隐蔽技术进行了分析,为已知和未知木马的防范和检测提供参考。     

基于IP网络门禁控制系统通信模块的设计与开发

对基于IP网络的门禁控制系统整体设计方案及原理进行了简要的分析,提出了在系统框架上将B／S模式和C／S模式相结合的设计思想,同时通过引入通信模块,在管理软件和控制器之间架起了专用的TCP通道,给出了一种实现TCP／IP通信的新方法,并加入门禁控制器主动通信方式,测试证明该通信平台运行稳定,能够提高门禁控制系统的工作效率。     

基于Web的学位论文评审信息平台的设计与实现

阐述了基于ASP．NET开发适应的省级优秀学位论文评审信息化平台的体系结构模型,分析了平台功能和数据库的构建,并简述了平台的实现。     

Preozonation of Chlorophenolic Wastewater for Subsequent Biological Treatment

Preozonation was investigated for its effects on the biodegradability of five chlorophenolic compounds in activated-sludge systems. The biodegradability was expressed in terms of the oxidation of each compound itself and of the total organic contents of the whole sample.

Results indicate that preozonation could either promote or retard the biodegradability, depending primarily on whether or not the sludge used in the subsequent biological system had been acclimated beforehand. For unacclimated sludge, preozonation was found to be helpful in promoting the biodegradability of all the compounds, especially the chlorophenols with a meta-position chlorine attachment. For acclimated sludge, a reverse effect generally, was observed.     

低温等离子体处理模式对冷藏南美白对虾中假单胞菌的抑菌效果及机理研究

摘 要：目的 探究低温等离子体(cold plasma, CP)处理模式对冷藏南美白对虾中常见荧光假单胞菌(Pseudomonas fluorescens)的抑菌效果及其作用机制。方法 通过CP直接处理和循环处理P. fluorescens,研究了两种处理模式下臭氧含量动态变化对P. fluorescens的生长曲线、细胞活力,生物膜形成、细胞壁、细胞膜完整性和南美白对虾菌落总数及假单胞菌数等指标的影响。结果 两种处理模式在CP处理3 min或3 cycles后,包装内臭氧含量达到最高值,分别为(850±10) mg/m3和(874±20) mg/m3。CP循环处理模式使得臭氧含量随处理循环数递增,因此获得更长的臭氧存在时间从而具有更大的抑菌能力。P. fluorescens生长曲线表明CP处理使得菌体延迟期变长且对数生长期推迟。此外,CP处理后的P. fluorescens细胞活力显著下降(P<0.05),CP-1 min,CP-3 min和CP-3 cycles组的细胞活力分别为33.03%、5.90%和4.82%。同时相比CP-3 min组,CP-3 cycles组的P. fluorescens生物膜OD值下降27.61%。碱性磷酸酶(alkaline phosphatase, AKP)活性和核酸蛋白泄漏量结果表明,细胞壁和细胞膜完整性受损可能是P. fluorescens失活的直接原因。对虾保鲜测试结果证实,贮藏第6 d,CP-3 cycles组虾体中的菌落总数和假单胞菌数相比CP-3 min组分别降低了58.02%和79.54%。结论 CP循环处理模式通过延长对臭氧与对虾的暴露时间,提高了对P. fluorescens的灭活效果,同时还具有更优越的保鲜能力。本研究为开发基于CP技术的新型保鲜技术应用提供了理论参考。 关键词：低温等离子体;荧光假单胞菌;抑菌机制;保鲜     

Blood cell counting based on U-Net++ and YOLOv5

Clinical information about a variety of disorders is available through blood cell counting, which is usually done by manual methods. However, manual methods are complex, time-consuming and susceptible to the subjective experience of inspectors. Although many efforts have been made to develop automated blood cell counting algorithms, the complexity of blood cell distribution and the highly overlapping nature of some red blood cells (RBCs) remain significant challenges that limit the improvement of analytical accuracy. Here, we proposed an end-to-end method for blood cell counting based on deep learning. Firstly, U-Net++ was used to segment the whole blood cell image into several regions of interest (ROI), and each ROI contains only one single cell or multiple overlapping cells. Subsequently, YOLOv5 was used to detect blood cells in each ROI. Specifically, we proposed several strategies, including fine classification of RBCs, adaptive adjustment for non-maximal suppression (NMS) threshold and blood cell morphology constraints to improve the accuracy of detection. Finally, the detection outcomes for each ROI were combined and superimposed. The results show that our method can effectively address the issue of high overlap and precisely segment and detect blood cells, with a 98.18% accuracy rate for blood cell counting.