Sn-Cu系无铅钎料的研究现状与发展

介绍了无铅钎料应用时应该满足的基本要求和Sn-Cu系无铅钎料的国内外研究和应用现状,概述了Sn-Cu系无铅钎料润湿性能、物理性能、力学性能等方面的一些特点,分析探讨了Sn-Cu系无铅钎料存在的不足,详细阐述了添加不同合金元素(如Bi、Ag、Ni、RE等元素)对Sn-Cu系无铅钎料性能的影响规律,并对Sn-Cu系无铅钎料的应用前景和发展方向进行了展望.     

BP神经网络在液压试验台故障诊断中的应用

分析了BP神经网络的结构及算法，并对液压试验台的故障模式用BP神经网络来进行诊断，从而提出了一种新的解决液压试验台故障诊断的方法。     

稀燃车用催化剂的研究进展

稀燃车用催化剂是汽车尾气净化催化剂今后发展的方向，在稀燃条件下如何处理NOx是稀燃车用催化剂面临的巨大挑战。本文详细地评述了近年来国内外在这方面的研究工作，包括选择催化还原催化剂、存储还原催化剂和组合多功能催化剂的研究进展。     

Thermodynamic assessment of the Fe-U binary system

The Fe-U system is one of the binaries of the U-Fe-Zr-O quaternary system that is important for a safe nuclear program. A new thermodynamic assessment of Fe-U is presented, taking into account some recent thermodynamic measurements: enthalpy of formation and of melting as well as heat capacities for both intermetallic compounds Fe₂U and FeU₆. The calculated phase diagram and thermodynamic data generally agree very well with the experimental values. The calculated temperature of the peritectic transformation [FeU₆ ↔ liquid + bcc-U] is equal to 1104 K, which is higher than in the previous assessments, but in agreement with Labroche’s value. However, the experimental melting enthalpy of FeU₆ is not reproduced by the present set of thermodynamic parameters.     

The Structure Stability of Carbide-Free Bainite Wheel Steel

Metallographic structures of carbide-free bainite steel wheel rim are mainly composed of supersaturated lath ferrite and retained austenite film among bainitic ferrite laths. It is suspected that supersaturated ferrite and retained austenite are likely to decompose under the influence of temperature change and mechanical stress. Stability of wheel rim structure is studied by means of x-ray diffraction, dye microscopy, and micro-hardness test. When the samples are tempered in the range of 150-350 °C, the retained austenite films are at the state of relative stability. Fifty percent of retained austenite is decomposed when the sample is tempered at 400 °C. Microhardness increases when the sample is tempered at 150 °C. The decrease in hardness is mild when the samples are tempered from 200 to 500 °C. The mechanical stability of retained austenite film is studied with tensile sample under the effect of tensile stress. The retained austenite appears to be stable in low and middle degree of deformation, and decomposition occurs at great amount of deformation. Diffraction peak of carbide is not found in all above experiments. The steel enriched silicon prevents the carbide precipitation during the transformation. It indicates the carbide-free bainite wheel steels have an excellent thermal and mechanical stability.     

大颗粒煤燃烧传递动力学破碎理论模型

研究了大颗粒煤燃烧中的颗粒破碎现象，理论分析了大颗粒煤的着火过程和颗粒破碎过程，建立了大颗粒煤燃烧传递动力学破碎模型，对褐煤、烟煤和无烟煤三个典型煤种进行了燃烧初期数值模拟，指出了大颗粒煤燃烧时着火和颗粒破碎的内在联系。     

TPR处理剂的研究

利用活性单体苯乙烯与氯丁橡胶、高苯乙烯热塑弹性体接枝聚合，所得产物稀释后用于ＴＰＲ（ＴｈｅｒｍａｌＰｌａｓｔｉｃＲｕｂｂｅｒ）粘接前的预处理，可明显提高剥离强度。     

VARI工艺在建筑物加固修复上的应用

本文叙述了VAR I工艺特点及其用于建筑物加固修复的重要性、优越性和应用前景。自制了一套简易实验装置,归纳并阐述了建筑物加固修复用VAR I技术的主要内容。针对国内的情况,提出了该领域亟待开展的研究工作。     

Optimizing ranking method using social annotations based on language model

Recent research has shown that more and more web users utilize social annotations to manage and organize their interested resources. Therefore, with the growing popularity of social annotations, it is becoming more and more important to utilize such social annotations to achieve effective web search. However, using a statistical model, there are no previous studies that examine the relationships between queries and social annotations. Motivated by this observation, we use social annotations to re-rank search results. We intend to optimize retrieval ranking method by using the ranking strategy of integrating the query-annotation similarity into query-document similarity. Specifically, we calculate the query-annotation similarity by using a statistical language model, which in a shorter form we call simply a language model. Then the initial search results are re-ranked according to the computational weighted score of the query-document similarity score and the query-annotation similarity score. Experimental results show that the proposed method can improve the NDCG score by 8.13%. We further conduct an empirical evaluation of the method by using a query set including about 300 popular social annotations and constructed phrases. More generally, the optimized results with social annotations based on a language model can be of significant benefit to web search.     

Increasing recommended effectiveness with markov chains and purchase intervals

Recommendation system is an important component of many websites and has brought huge economic benefits and challenges for online shoppers and e-commerce companies. Existing recommendation systems focus on producing a list of products which users may be interested to purchase, while overlooking the purchase chain and temporal diversity which may increase the likelihood of a purchase decision. In this paper, we propose to utilize the Markov chain to track the chain of users’ purchase behaviors and utilize the purchase intervals to improve the temporal diversity for e-commerce recommender. We design and implement several algorithms and integrate these into our recommendation model. We evaluate our system on a real-world e-commerce dataset. Experimental results demonstrate that our approach significantly improves the accuracy, conversion rate and temporal diversity compared to the state-of-the-art algorithms.