聚丙烯非织造布拒水整理对葡萄套袋微环境的影响

为提高普通聚丙烯(PP)非织造布拒水性以及获取果实套袋对生长微环境影响状况等信息,以水性聚氨酯(PU)为交联剂,用氟系拒水剂对PP非织造布进行拒水整理,通过正交试验分析拒水剂质量浓度、交联剂质量浓度、浸润时间、焙烘温度对整理后拒水效果、透气率、透光率、断裂强力的影响,并得出最优整理工艺。用非织造布制袋并进行葡萄套袋下田试验,测量果袋内外日均光照强度、温度、湿度,探究拒水PP套袋对果袋内微环境和葡萄果实品质的影响。结果表明,影响拒水整理的因素主次排序及最佳工艺分别为:焙烘温度130℃;拒水剂质量浓度40 g/L;浸润时间10 min;水性PU质量浓度3 g/L。整理后PP果袋拒水性提高60%。     

Reducing chemical vapour infiltration time for ceramic matrix composites

Conventional routes to producing ceramic matrix composites (CMCs) require the use of high temperatures to sinter the individual ceramic particles of the matrix together. Sintering temperatures are typically much higher than the upper temperature limits of the fibres. This paper details preliminary work carried out on producing a CMC via chemical vapour infiltration (CVI), a process that involves lower processing temperatures, thus avoiding fibre degradation. The CVI process has been modified and supplemented in an attempt to reduce the CVI process time and to lower the cost of this typically expensive process. To this end microwave-enhanced CVI (MECVI) has been chosen, along with two alternative pre-infiltration steps: electrophoretic infiltration and vacuum bagging. The system under investigation is based on silicon carbide fibres within a silicon carbide matrix (SiC_f/SiC).
The results demonstrate that both approaches result in an enhanced initial density and a consequent significant reduction in the time required for the MECVI processing step. Dual energy X-ray absorptiometry was used as a non-destructive, density evaluation technique. Initial results indicate that the presence of the SiC powder in the pre-form changes the deposition profile during the MECVI process.     

Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers

We study the leave-one-out and generalization errors of voting combinations of learning machines. A special case considered is a variant of bagging. We analyze in detail combinations of kernel machines, such as support vector machines, and present theoretical estimates of their leave-one-out error. We also derive novel bounds on the stability of combinations of any classifiers. These bounds can be used to formally show that, for example, bagging increases the stability of unstable learning machines. We report experiments supporting the theoretical findings.     

Ensembles of Neural Networks for Fault Diagnosis in Analog Circuits

A new neural network-based analog fault diagnosis strategy is introduced. Ensemble of neural networks is constructed and trained for efficient and accurate fault classification of the circuit under test (CUT). In the testing phase, the outputs of the individual ensemble members are combined to isolate the actual CUT fault. Prominent techniques for producing the ensemble are utilized, analyzed and compared. The created ensemble exhibit high classification accuracy even if the CUT has overlapping fault classes which cannot be isolated using a unitary neural network. Each neural classifier of the ensemble focuses on a particular region in the CUT measurement space. As a result, significantly better generalization performance is achieved by the ensemble as compared to any of its individual neural nets. Moreover, the selection of the proper architecture of the neural classifiers is simplified. Experimental results demonstrate the superior performance of the developed approach.     

Comparative assessment of statistical and machine learning techniques towards estimating the risk of developing type 2 diabetes and cardiovascular complications

The aim of the present study is to comparatively assess the performance of different machine learning and statistical techniques with regard to their ability to estimate the risk of developing type 2 diabetes mellitus (Case 1) and cardiovascular disease complications (Case 2). This is the first work investigating the application of ensembles of artificial neural networks (EANN) towards producing the 5‐year risk of developing type 2 diabetes mellitus and cardiovascular disease as a long‐term diabetes complication. The performance of the proposed models has been comparatively assessed with the performance obtained by applying logistic regression, Bayesian‐based approaches, and decision trees. The models' discrimination and calibration have been evaluated using the classification accuracy (ACC), the area under the curve (AUC) criterion, and the Hosmer–Lemeshow goodness of fit test. The obtained results demonstrate the superiority of the proposed models (EANN) over the other models. In Case 1, EANN with different topologies has achieved high discrimination and good calibration performance (ACC = 80.20%, AUC = 0.849, p value = .886). In Case 2, EANN based on bagging has resulted in good discrimination and calibration performance (ACC = 92.86%, AUC = 0.739, p value = .755).     

一种新型灌包装车工艺

在秦皇岛港丙码头散化肥装卸系统的建设过程中，设计了一种由普通装载机(散装化肥)至火车车厢(袋装化肥)的灌包装车工艺，具有自动化程度高、设备移动方便、效率高等优点，值得推广。     

实现动态称量的包装自动线设计

介绍一种能实现颗粒、粉末物料动态称量、包装和输送的全自动包装生产线。分析了颗粒、粉末物料包装线的特点，给出了生产线的组成及工艺流程，介绍了主要机械装置及控制系统的设计。     

Statistical learning for wind power: A modeling and stability study towards forecasting

We focus on wind power modeling using machine learning techniques. We show on real data provided by the wind energy company Maïa Eolis that parametric models even following closely the physical equation relating wind production to wind speed are outperformed by intelligent learning algorithms. In particular, the CART‐Bagging algorithm gives very stable and promising results. Besides, as a step towards forecast, we quantify the impact of using deteriorated wind measures on the performances. We show also on this application that the default methodology to select a subset of predictors provided in the standard random forest package can be refined, especially when there exists among the predictors one variable, which has a major impact.     

基于TRIZ理论的套袋机套袋装置优化设计

目的解决现有套袋机套袋装置在套袋过程中薄膜内袋容易产生折角的问题。方法利用TRZI理论中功能模型及因果链分析对初始问题进行全面分析,找到根本问题后,再将根本问题转化为TRIZ问题模型,然后利用TRIZ中解决问题的工具找到多个解决方案模型,并对方案模型进行可用性评估。结果将评估所得的最优方案进行实施,薄膜内袋折角的问题被解决,双层袋合格率达到99.5%。结论利用TRIZ理论中的一系列工具对薄膜内袋折角问题进行转化,建立了解决方案模型,选取了最优方案进行实施,成功解决了薄膜内袋折角问题。     

筒子纱包装自动整列系统的设计与实现

目的 筒子纱的自动化包装是提高纺织自动化程度的重要手段,其中筒子纱的自动整列装袋是将筒子纱从离散到整包的关键,为了实现筒子纱的自动整列装袋,提出并设计一套筒子纱自动整列系统。方法 在控制方面,以西门子S7-1200系列PLC为控制核心,分析功能实现的顺序流程,采用TIA portal v14软件进行程序编写;在机械设计方面,根据工艺要求,设计一种带有吊臂的新型筒纱自动整列装置。结果 该系统能够在横、纵、竖等3个方向协同工作,并对筒子纱进行自动化整列,且具有一定的缓存功能。结论 该系统适用于大部分的筒纱自动包装生产线,可大幅提高筒子纱包装效率。