Effects of retrospective quality control on pressure-flow data with computer-based urodynamic systems from men with benign prostatic hyperplasia

Aim： To evaluate the effects of retrospective quality control on pressure-flow data with computer-based urodynamic systems from men with benign prostatic hyperplasia （BPH）. Methods： A total of 582 traces of pressure-flow study from 181 men with BPH was included in the study. For each trace, maximum urinary flow rate （Qmax） and detrusor pressure at Qmax （pdet.Qmax） were, respectively, read from manually smoothed and corrected uroflow and detrusor pressure curves from the computer print-outs. Obstruction coefficient, International Continence Society （ICS） and Schaefer nomograms were used to detect urethral resistance and to diagnose obstruction. The results obtained by manual reading were compared with those from computer-based systems. Results： After manual correction, Qmax underwent a consistently significant decrease by 1.2 mL/s on average （P 〈 0.001）, and had a change range of 0.5-10.4 mL/s. However, pdet.Qmax underwent inconsistently intra-individual changes after correction. The obstruction coefficient increased significantly, by an average of 0.07 （P 〈 0.05）. Using the ICS nomogram, the percentage of obstruction increased from 69.8% to 73.9%, and of the non-obstruction decreased from 8.8% to 5.3% （P 〈 0.05）. There were 11% of traces that changed the classifications using the ICS nomogram, and 28.9% that changed the grades for the Schaefer nomogram. Conclusion： Systematically significant differences in parameters from pres- sure-flow study between manual readings and computer recordings were demonstrated. Manual correction resulted in a consistently lower Q a higher urethral resistance, and an aggravating obstruction. Manual readings can correct considerable false diagnoses for obstruction. Retrospective quality control of pressure-flow data with com- puter-based systems is necessary.

A Genetic Based Fuzzy Q-Learning Flow Controller for High-Speed Networks

For the congestion problems in high-speed networks, a genetic based fuzzy Q-learning flow controller is proposed. Because of the uncertainties and highly time-varying, it is not easy to accurately obtain the complete information for high-speed networks. In this case, the Q-learning, which is independent of mathematic model, and prior-knowledge, has good performance. The fuzzy inference is introduced in order to facilitate generalization in large state space, and the genetic operators are used to obtain the consequent parts of fuzzy rules. Simulation results show that the proposed controller can learn to take the best action to regulate source flow with the features of high throughput and low packet loss ratio, and can avoid the occurrence of congestion effectively.

Branch Quality Control of Gas-Liquid Two-Phase Flow Using a Novel T-Junction Type Distributor

In order to eliminate mal-distribution and ensure the side arm to produce desirable gas quality a special distributor is proposed. The experimental distributor mainly consists of a straight through section,a gas extraction line,a liquid extraction line and a side arm branch. A gas orifice and a liquid orifice are mounted at the gas and liquid extraction line respectively to control the outlet gas quality. The diameter of the liquid orifice was set to 2. 50 mm and three gas orifices with different size( dG= 2. 65,5. 00,10. 00 mm) were tested. The experiments were carried out at an air-water two-phase flow loop. The gas superficial velocity ranged from 6. 0 to 20. 0 m /s and the liquid superficial velocity was in the range of 0. 02- 0. 18 m /s. Flow patterns such as wave flow,slug flow and annular flow were observed. The gas quality of the side arm branch was found mainly determined by the flow area ratio of the gas orifice to the liquid orifice and independent of gas and liquid superficial velocity,flow patterns and extraction flux.

Validation and quality control of hematolymphoid neoplasm immunophenotyping by flow cytometry

cytometric immunophenotyping has evolved from two-parameter quantitative measurement of peripheral blood lymphocytes to five-or more parameter qualitative evaluation of bone marrow for hematopathology.Leukemia/lymphoma immunophenotyping represent an important addition to histomorphology in the diagnosis,classification and monitoring of hematolymphoid neoplasms.The complexity of five-or more parameter analyses and the interpretation of the data rely on standardization and validation of the instrument,the reagent and the procedure.In addition,clinical flow cytometry laboratories in U.S.are required to document proficiency testing,sample preparation,method accuracy,specificity,sensitivity and precision.CLSI and the U.S.-Canadian Consensus Conference have provided recommendations,but each laboratory is responsible for validating its own qualitative and quantitative procedures.This paper introduces the procedures for quality control of all levels of the operation in a clinical flow cytometry laboratory in USA.

Graft Quality Control with the Traditional Roller Pump Flow Measurement in Comparison to the Transit-Time Flow Measurement

Objective: Vein graft quality control had been traditionally done for more than 20 years with a roller-pump flow measurement (RPFM) in our institute until off-pump coronary artery bypass grafting was introduced as the standard technique of myocardial revascularization in the year 2009 in our institute. In this study, the RPFM method was compared with the Transit-time flow measurement (TTFM). Patients and Methods: From February to September 2005, 31 patients (5 females) undergoing CABG in our institute were included into the study. All the patients were operated with cardiopulmonary bypass. In those patients, 27 distal anastomoses were done with the left internal thoracic artery and 99 anastomoses were done with vein grafts. Those 99 vein graft were assessed both, with the RPFM method and TTFM method. Results: CABG could be safely performed in all cases. In all target vessels, the RPFM method overestimated bypass flow compared to the TTFM method, and simple linear regression revealed no correlation between the TTFM measurement and the RPFM measurement (r = 0.08, p = 0.21). There were two cases in which a graft problem could be detected only with TTFM method, even in our small patient cohort. Conclusion: The present study suggests that the TTFM method is clearly superior to the traditional RPFM method and we believe now that TTFM should be performed routinely in all CABG to improve patient care and quality of surgical results.

Optimum control strategy for all-variable speed chiller plant

The optimum control strategy and the saving potential of all variable chiller plant under the conditions of changing building cooling load and cooling water supply temperature were investigated. Based on a simulation model of water source chiller plant established in dynamic transient simulation program (TRNSYS),the four-variable quadratic orthogonal regression experiments were carried out by taking cooling load,cooling water supply temperature,cooling water flow rate and chilled water flow rate as variables,and the fitting formulas expressing the relationships between the total energy consumption of chiller plant with the four selected parameters was obtained. With the SAS statistical software and MATHEMATICA mathematical software,the optimal chilled water flow rate and cooling water flow rate which result in the minimum total energy consumption were determined under continuously varying cooling load and cooling water supply temperature. With regard to a chiller plant serving an office building in Shanghai,the total energy consumptions under different control strategies were computed in terms of the forecasting function of cooling load and water source temperature. The results show that applying the optimal control strategy to the chiller plant can bring a saving of 23.27% in power compared with the corresponding conventional variable speed plant,indicating that the optimal control strategy can improve the energy efficiency of chiller plant.

Mathematical Modeling,Field Calibration and Numerical Simulation of Low-Speed Mixed Traffic Flow in Cities

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Novel flow control mechanism based on improved BP neural network in cognitive packet network

In this paper, a novel flow control mechanism in cognitive packet network (CPN) based on the improved back propagation (BP) neural network is proposed, considering the flow distribution status predicted by BP neural network when packets are routed. The objective is to increase the capacity of CPN and improve the quality of service (QoS) by achieving flow balance. Besides, considering the slow convergence speed of traditional BP algorithm and the quick change of the flow status in cognitive packet network, an improved BP algorithm with dynamic learning rate is designed in order to achieve a higher convergence speed. The mechanism, which we propose, regards the predicated traffic data as an important factor when packets are routed to implement flow control. By achieving balance, the quality of network can be improved obviously. The simulation results show that the proposed mechanism provides better average time delay and packets loss ratio.

Direct Power Control of Variable Wind Speed Based on the Doubly Fed Asynchronous Machine

In this work, the authors propose the study of a wind speed variable based on the DFAM （double fed asynchronous machine）. The model of the turbine is drawn from the classical equations describing the operation of a variable wind speed. The torque generated by the turbine is applied to the DFAM directly connected on the network side and the stator via a bidirectional converter side rotor. This configuration allows velocity variations of ±30% around the synchronous speed and the converter is then sized to one third of the rated power of the machine. The DFAM is controlled by a control vector ensuring operation of the wind turbine power coefficient maximum.

Operational guidance for aeration and flow augmentation for the Chicago Area Waterway System—A case study

The Chicago Area Waterway System(CAWS)is a 133.9 km branching network of navigable waterways controlled by hydraulic structures,in which the majority of the flow is treated wastewater effluent and there are periods of substantial combined sewer overflows.The CAWS comprises a network of effluent dominated streams.More stringent dissolved oxygen(DO)standards and a reduced flow augmentation allowance have been recently applied to the CAWS.Therefore,a carefully calibrated and verified one-dimensional flow and water quality model was applied to the CAWS to determine emission-based real-time control guidelines for the operation of flow augmentation and aeration stations.The goal of these guidelines was to attain DO standards at least 95%of the time.The“optimal”guidelines were tested for representative normal,dry,and wet years.The finally proposed guidelines were found in the simulations to attain the 95%target for nearly all locations in the CAWS for the three test years.The developed operational guidelines have been applied since 2018 and have shown improved attainment of the DO standards throughout the CAWS while at the same time achieving similar energy use at the aeration stations on the Calumet River system,greatly lowered energy use on the Chicago River system,and greatly lowered discretionary diversion from Lake Michigan,meeting the recently enacted lower amount of allowed annual discretionary diversion.This case study indicates that emission-based real-time control developed from a well calibrated model holds potential to help many receiving water bodies achieve high attainment of water quality standards.

基于分布式潮流控制器的海上风电系统谐波治理方法和控制策略

由于电力电缆的电容效应,海上风电经电缆汇集系统极易出现谐波谐振放大的现象,造成电能质量的下降。分布式潮流控制器属于基于电压源换流器的装置,在进行潮流调节的同时也能进行谐波治理。文中首先构建了海上风电系统的频域相关模型,基于该模型分析了谐波谐振放大的原因;随后,采用了将分布式潮流控制器串入海上风电系统的谐波治理方式,推导并得到了含分布式潮流控制器的海上风电系统的谐波特性。基于该谐波特性,设计了一种控制策略。该策略通过控制分布式潮流控制器实时跟踪使并网点谐波电压幅值为零的谐波补偿电压,从而降低并网点的谐波电压含量。仿真结果表明,所提出的基于分布式潮流控制器的海上风电系统谐波治理方法和控制策略能够有效地降低并网点的谐波电压,改善电能质量。

基于PI-BBI的高铁沿线秒级风速质量控制算法研究

由于高铁超声波测风仪碍于安装环境限制易受外部干扰产生秒级异常风速,而现有的基本质量控制方法与气象领域分钟级时距质量控制算法无法准确识别秒级异常风速,导致监测风速不能很好地满足高铁秒级风速监测预警需求。为了解决该问题,基于高铁沿线风速监测异常值数据特征,提出一种基于PI-BBI的秒级风速监测数据质量控制算法。该方法首先利用基于物理信息的双向长短期记忆网络对风速异常值进行预测,并得到预测误差;接着通过改进的指数加权移动平均法对预测误差进行平滑;最后使用孤立森林检测平滑误差序列中的异常值,从而能够识别原始风速序列中的异常值。实验结果显示,该质量控制算法能有效改善高铁沿线风速监测数据的质量,从而提高监测预警的准确性。

岩溶凹陷式露天矿山大流量涌水治理技术

我国岩溶地质分布广泛,岩溶突涌水已成为石灰石矿山安全生产的巨大灾害与挑战。以广西某岩溶凹陷式露天矿山大流量涌水为研究对象,针对该矿山地质条件复杂、集中涌水量大、流速高等特点,利用岩溶发育特征、资料分析与地球物理探查等方法初步圈定矿山径流带区域;进一步通过钻探、跨孔CT和示踪联通试验等精准查找到矿山Y01特大涌水点岩溶管道的具体位置,在此基础上研究并实施了矿山涌水治理技术与工艺。研究表明:(1)针对复杂岩溶凹陷式露天矿山大流量、高流速的涌水特征,提出并实施了“非连续帷幕截流+关键通道探查与封堵+止浆垫控流降速”的岩溶矿山涌水综合治理体系。依据岩溶发育的不均匀性,提出了非连续帷幕封堵裂隙型涌水区域的思想;对大流量岩溶管道型集中涌水设计采用止浆垫控流装置,通过控流能有效降低关键过水通道内水流速度,为注浆材料的有效留存沉积和工程的成功封堵提供了重要条件。(2)关键孔联合注浆工艺是岩溶管道型涌水成功封堵的保证,关键孔是指直接揭露岩溶涌水管道或与涌水管道联通性极强并对注浆堵水起主要作用的钻孔。针对矿山Y01岩溶管道型特大涌水精准查找到2个关键孔,均在矿坑南部:一个是距涌水点直线距离约50 m的近距离钻孔(以下简称“近孔”),另一个是距涌水点直线距离约150 m的远距离钻孔(以下简称“远孔”)。现场采用近孔、远孔2个关键孔联合注浆工艺:近孔以粗骨料和自主研发的可控凝结新型材料进行注浆,远孔仅注水泥浆液;近孔粗骨料和新型材料既能降低管道内的水流速度为远孔浆液起到更好的留存沉积作用,又能作为封堵材料起到增强的功能,远孔因其离涌水点距离长、辐射范围广、浆液扩散充分而能确保封堵长度和效果。近孔、远孔协同配合同步注浆是封堵管道型大流量涌水的有效组合工艺。(3)涌水口止浆垫控流降速装置的合理有效调控,配合关键孔联合注浆工艺的同步实施,进一步确保了注浆浆液的有效快速留存和沉积,是岩溶地区封堵管道型大流量涌水的创新性技术和方法。项目实施后,彻底封堵矿坑内集中涌水量达7.12万m^(3)/d的Y01特大涌水点,实现总减水量8.43万m3/d(含非连续帷幕注浆封堵),保证了矿山的正常安全开采,大幅降低了抽排水费用,同时保护了周边环境和地下水资源,具有显著的经济效益和社会效益。研究成果可为我国矿山涌水灾害治理提供理论价值和经验借鉴。

ML组合的CYGNSS海面风速反演质量控制模型

卷积神经网络(CNN)可用于气旋全球导航卫星系统(CYGNSS)的海面风速反演。虽然在模型训练前设置了质量控制指标来检测和削弱CYGNSS的异常观测数据,但CYGNSS观测数据中仍存在异常值导致模型反演精度降低,甚至出现错误反演结果。因此,提出一种基于机器学习(ML)组合的海面风速反演模型。在基于CNN回归模型的CYGNSS反演海面风速基础上,ML分类模型生成CNN回归结果的质量标志位,该标志位可以检测并删除CNN回归结果的异常值,进一步提高风速反演结果的数据质量,ML分类模型能够更好地考虑各种数据误差之间的相互作用,而不是单独使用每个条件的阈值,以达到更优的海面风速反演精度的效果。实验对比了Logistic回归(LR)、决策树(DT)、朴素贝叶斯模型、K最邻近(KNN)算法、神经网络(NN)模型、支持向量机(SVM)算法等6个分类模型,其中,基于KNN算法的分类模型对风速反演质量控制的效果最优。所提风速反演组合模型显著提高了反演结果的精度,在0~20 m/s区间内,异常样本过滤率为81.27%,在所有被过滤的数据中,过滤正确率为86.03%;风速反演误差的均方根误差从无ML分类模型的1.7 m/s降低到有ML分类模型的1.44 m/s,其中,训练样本为0~10 m/s的反演结果精度提升效果较为明显,证明了所提风速反演组合模型对风速质量控制的有效性。

综掘工作面风流调控下风速及瓦斯粉尘浓度融合预测模型研究

针对综掘工作面传统的通风总量控制管理模式不能根据实际需求进行风流调控,造成瓦斯及粉尘聚集和污染隐患等问题,对风流调控下的风速及瓦斯粉尘浓度多源数据融合神经网络预测模型进行了研究。采用欧拉-拉格朗日法建立了风流调控下的瓦斯及粉尘气固耦合模型并进行了测试验证,模拟分析瓦斯和粉尘颗粒在综掘巷道的分布情况,获取大量不同风流调控方案下的风速及瓦斯粉尘浓度样本数据。采用多层感知器神经网络技术建立预测模型结构,选取对瓦斯及粉尘浓度具有较大影响的风流调控等参数作为输入层,根据风速及瓦斯粉尘的隐患位置确定输出层,对样本数据进行预处理,通过引入差分进化算法搜索最佳隐藏层节点数和学习率,利用TensorFlow框架搭建多源数据融合神经网络预测模型。以陕北某矿综掘工作面为研究对象,对不同风流调控方案进行预测和井下实测验证。结果表明:该模型相对误差最大值为9.7%,具有较高的准确性;选取出风口距端头最短距离5 m和最远距离10 m这2种工况下的最佳调控方案,与调控前相比,风速符合规范要求,端头死角区瓦斯体积分数分别降低34%和35%,回风侧人行处平均粉尘质量浓度分别降低40%和41%,司机处粉尘质量浓度分别降低38%和36%,研究可为风流调控提供参考。

目标检测下的车型对交通流速度影响研究

针对传统目标检测跟踪算法识别精度低,实时性差等缺点,提出了一种基于YOLOv5s和DeepSort算法模型的视频车辆实时车流量和速度检测方法。构建了包含25 877个目标样本的数据集,采用YOLOv5s算法模型实现视频车辆的检测,利用DeepSort算法对车辆进行跟踪计数与测速,实现了路段监控对车辆的实时检测。基于深度学习获取的速度与交通量数据,构建了不同车型对交通流速度影响模型,探究畅通状态、稳定状态、拥挤状态下车型的速度与交通量之间的关系,结果表明:算法模型对视频车辆的检测效果良好,平均准确度达到91.4%;不同状态下,车型对交通量速度的影响程度不同;畅通状态和稳定状态下,出租车的速度对交通量影响较大;拥挤状态下,私家车的车速受交通量影响较大。

受控制律影响的电传运输机飞行品质试飞技术

针对电传运输机控制律设计特点,该文分析保护功能、自动配平功能等飞控功能对飞行品质试飞科目的影响,梳理受影响的关键试飞科目,并根据影响情况,适应性提出受控制律影响的运输机失速特性、抖振边界、空中最小操纵速度、高速特性等科目改进的试飞方法,总结试飞过程中的问题和经验,突破受电传控制律影响的飞机飞行品质关键科目试飞技术,为后续电传运输机飞行品质试飞提供参考。

RFID技术在服装单件流生产流水线的应用研究

在全球化和信息化快速发展的背景下,服装制造业正面临效率提升和智能化管理的双重挑战。RFID技术以其在实时数据采集、自动化管理等方面的显著优势,逐渐成为服装单件流生产流水线的关键应用技术。本文探讨RFID技术在服装单件流生产中的应用,分析其在提升生产效率、质量控制和信息化管理方面的具体作用,并提出解决实际应用中遇到技术挑战的策略,为行业提供科学依据和实践指导。

高速列车包间噪声特性及降噪方案设计验证

针对高速列车包间噪声问题及降噪措施进行了相关研究。首先,通过线路试验分析了高速列车包间噪声特性,包括噪声频谱、声源识别和声品质,掌握了包间中心与铺面上方测点的噪声差异,明确了包间噪声控制目标;其次,基于统计能量分析方法建立了高速列车包间噪声预测模型,并进行了试验验证,开展了包间声能量贡献分析,确定了降噪方案设计指标,进而对车体进行了隔声方案优化设计;最后,通过包间噪声的迭代预测,确定了车体降噪方案的可行性,并进行了线路试验验证。结果表明,采用笔者设计的降噪措施,包间噪声总值降低了3.2 dB(A),包间原本较高的响度和粗糙度得到明显控制,尖锐度也略有降低,声品质得到了优化。

高速列车开闭机构涡流发生器的气动减阻设计

为了降低列车高速运行受到的气动阻力,采用基于SST(shear stress transport)k−ω湍流模型的雷诺时均法研究高速列车尾车开闭机构位置安装涡流发生器对尾部流动特征以及列车气动载荷的影响。研究结果表明:涡流发生器能显著改变尾车周围的流场,产生一对与原涡流旋向相反的涡流结构,降低尾流涡强度和范围,在尾车安装涡流发生器后,气流流动受到涡流发生器的阻碍产生积聚,从而在尾车表面形成较大的正压区域,降低尾车压差阻力和气动升力;随着涡流发生器安装位置向尾车鼻尖靠近,减升效果逐渐降低,尾车最大减升率为36.8%;尾车阻力随着涡流发生器安装位置向后移动呈现出先减小后增大的趋势,尾车气动阻力最大减阻幅度为4.54%。合理的开闭机构涡流发生器能有效控制尾流结构,进而控制尾车气动力,为高速列车气动减阻提供新思路。