Estimation of break location and size for loss of coolant accidents using neural networks

In this work, a probabilistic neural network (PNN) that has been applied well to the classification problems is used in order to identify the break locations of loss of coolant accidents (LOCA) such as hot-leg, cold-leg and steam generator tubes. Also, a fuzzy neural network (FNN) is designed to estimate the break size. The inputs to PNN and FNN are time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. An automatic structure constructor for the fuzzy neural network automatically selects the input variables from the time-integrated values of many measured signals, and optimizes the number of rules and its related parameters. It is verified that the proposed algorithm identifies very well the break locations of LOCAs and also, estimate their break size accurately.     

Effect of Rare Earths on Corrosion Resisting Properties of Carbon-Manganese Clean Steels

Rareearthelementshavesignificantactionsinsteels ,includingwipingoffimpurityelements ,trans modifyinginclusions ,andimprovingmicrostructureetal,soaddingappropriaterareearthsintosteelscanef fectivelyimprovetheircorrosionresistingproper ties[1,2 ] .Todaypuri…     

Object detection using feature subset selection

Past work on object detection has emphasized the issues of feature extraction and classification, however, relatively less attention has been given to the critical issue of feature selection. The main trend in feature extraction has been representing the data in a lower dimensional space, for example, using principal component analysis (PCA). Without using an effective scheme to select an appropriate set of features in this space, however, these methods rely mostly on powerful classification algorithms to deal with redundant and irrelevant features. In this paper, we argue that feature selection is an important problem in object detection and demonstrate that genetic algorithms (GAs) provide a simple, general, and powerful framework for selecting good subsets of features, leading to improved detection rates. As a case study, we have considered PCA for feature extraction and support vector machines (SVMs) for classification. The goal is searching the PCA space using GAs to select a subset of eigenvectors encoding important information about the target concept of interest. This is in contrast to traditional methods selecting some percentage of the top eigenvectors to represent the target concept, independently of the classification task. We have tested the proposed framework on two challenging applications: vehicle detection and face detection. Our experimental results illustrate significant performance improvements in both cases.     

Tribological behavior of sialon ceramics sliding against steel lubricated by fluorine-containing oils

The friction and wear behavior of sialon ceramics sliding against steel and lubricated by perfluoropolyethers (PFPE), tetrakis (3-trifluoromethylphenoxy)-bis(4-fluoro-phenoxy)-cyclotriphosphazene (X-1P) and ionic liquid (1-methyl-3-octylimidazolium tetrafluoroborate, coded as L108) were investigated. It was found that the three fluorine-containing lubricants reduced friction coefficient and wear volume effectively. The effectiveness of the three lubricants in reducing wear volume could be ranked as L108>X-1P>PFPE. The antiwear films mainly consisting of organic oxyfluoride or carbonfluoride species and silicon fluoride are all observed for the three lubricants, while the degradation of PFPE during friction might account for the higher wear volume therewith. The lowest friction coefficient 0.065 was recorded for L108 under load of 0.5–400 N. This is dependent on the physically adsorbed ionic liquid on the rubbing surface and the formation of BN under the harsh conditions.     

线阵CCD在安瓶三径在线自动检测分选系统中的应用

阐述了用线阵CCD检测系统通过变速扫描实现安瓶三径在线检测与控制的应用研究。文中用变速扫描方案，使在满足系统测量精度和高速的条件下，大大降低了对线阵CCD器件和扫描伺服系统性能的要求，使系统更具有实用价值。     

采用径向射流冲击与钎焊砂轮解决磨削烧伤的研究

在分析高效磨削烧伤机理的基础上，提出了两项对策：一是采用高压径向射流冲击强化磨削弧区换热，以最大限度地疏导已经产生的积聚在弧区的磨削热；二是采用钎焊超硬磨料砂轮取代传统电镀砂轮，以提高砂轮的锋利度降低磨削比能，减少磨削热的产生。缓进给断续磨削试验结果表明，该两项对策对解决难加工材料磨削烧伤问题效果十分明显，具有广阔的应用前景。     

原盐水力粉碎影响因素正交试验

以正交分析的方法研究了水射流粉碎原盐过程中各种因素对粉碎效果的影响，确定出粉碎过程的最佳工艺操作参数，为进一步研究高压水射流原盐粉碎技术奠定了基础。     

An acoustic aneurysm-detector

Intracranial aneurysms have a high prevalence in the adult population; and if they rupture, significant morbidity almost always ensues. However, pulsatile blood flow through aneurysms produces vibrational sound patterns that may be detected extracranially. Thus, an acoustic aneurysm-detector has been developed to detect the sounds produced by intracranial aneurysms prior to rupture. The design is based on the utilization of a hydrophone for signal detection and computational signal processing for signal extraction. Data are examined in the time domain, the frequency domain, and the time-frequency plane. Examples are presented from an animal model and from a patient with a known aneurysm.     

Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>@PAM@NTA-Ni<Superscript>2+</Superscript> Magnetic Composite Nanoparticles for Highly Specific Separation of His-tagged Proteins

A facile approach has been developed to synthesize Fe₃O₄@PAM (polyacrylamide) nanoparticles (NPs) with carboxyl groups on the surfaces by copolymerization with acrylamide and acrylic acid in Fe₃O₄ NPs aqueous suspension. Nitrilotriacetic acid (NTA) was conjugated to the magnetic NPs via well-known carboniimide chemistry using EDC and NHS. The Ni²⁺ ions loaded on the surface of NPs provide abundant docking sites for immobilization of His-tagged green fluorescent proteins (His-tagged GFP). The high magnetic property of Fe₃O₄@PAM@NTA-Ni²⁺ allows an easy separation of the NPs from solution under an external magnetic field, with high His-tagged protein binding capacity (42 μg protein/mg of NPs). The NPs can be recycled for at least four times without significant loss of binding capacity to proteins. These materials show great potential to separate His-tagged protein with low-cost purification at industrial scale.