巨型工程机械子午线轮胎高强度、低生热胎面基部胶配方开发

通过对国外知名品牌37.00R57和40.00R57规格巨型工程机械子午线轮胎胎面基部胶组成分析和物理性能测试,对我公司巨型工程机械子午线轮胎胎面基部胶配方进行优化设计。新开发配方半成品和成品胶料动态损耗因子分别降低37.9%和26.6%,胶料物理性能达到竞品水平,成品轮胎TKPH提升13.6%。     

汽车路况网的进一步研究

汽车路况网的概念源于数字城市的概念,通过研究网络、实时数据库和汽车智能,实现安全的交通网络。研究的语言一般应用Lisp语言,数据库为实时数据库。     

初创型团队异质性与团队创新的关系:基于团队外部知识网络的视角

目的探索基于团队外部知识网络视角来考察年龄异质性和专业异质性对初创型异质性团队创新的作用。方法采用问卷调查的方法。对102个初创型团队进行调查。结果在初创型团队中,年龄异质性和专业异质性均能提升团队创新,外部知识网络利用强度和广度在年龄异质性促进团队创新的过程中承担中介作用,外部知识网络利用强度在专业异质性促进团队创新的过程中承担中介作用。结论在初创型团队中,年龄异质性通过提升外部知识网络利用促进团队创新,专业异质性通过提升外部知识网络利用强度促进团队创新。     

Integrating Variable Reduction Strategy With Evolutionary Algorithms for Solving Nonlinear Equations Systems

Nonlinear equations systems (NESs) are widely used in real-world problems and they are difficult to solve due to their nonlinearity and multiple roots. Evolutionary algorithms (EAs) are one of the methods for solving NESs, given their global search capabilities and ability to locate multiple roots of a NES simultaneously within one run. Currently, the majority of research on using EAs to solve NESs focuses on transformation techniques and improving the performance of the used EAs. By contrast, problem domain knowledge of NESs is investigated in this study, where we propose the incorporation of a variable reduction strategy (VRS) into EAs to solve NESs. The VRS makes full use of the systems of expressing a NES and uses some variables (i.e., core variable) to represent other variables (i.e., reduced variables) through variable relationships that exist in the equation systems. It enables the reduction of partial variables and equations and shrinks the decision space, thereby reducing the complexity of the problem and improving the search efficiency of the EAs. To test the effectiveness of VRS in dealing with NESs, this paper mainly integrates the VRS into two existing state-of-the-art EA methods (i.e., MONES and DR-JADE) according to the integration framework of the VRS and EA, respectively. Experimental results show that, with the assistance of the VRS, the EA methods can produce better results than the original methods and other compared methods. Furthermore, extensive experiments regarding the influence of different reduction schemes and EAs substantiate that a better EA for solving a NES with more reduced variables tends to provide better performance.      

Regional characteristics and the decision to innovate in a developing country: A multilevel analysis of Ecuadorian firms

This is the first study that uses multilevel modelling to analyse regional influence on the decision to invest in innovation activities of firms in a single developing country, Ecuador. Our results indicate that the decision to invest in R&D and in other innovation activities are conditioned by the region in which the firm is located. Regional loan volume, orientation towards knowledge exploitation and intra-regional-sectorial R&D spillovers are positively associated with both types of innovation activities, while regional levels of co-operation and inter-regional R&D spillovers are only positively associated with the probability of investing in other innovation activities.     

Comparison of the dynamic responses of monopiles and gravity base foundations for offshore wind turbines in sand using centrifuge modelling

Monopiles and gravity base foundations (GBF) are two of the most commonly used foundations for offshore wind turbines. As resonance can cause damage and even failure of wind turbines, understanding the difference between the dynamic responses of monopiles and GBFs under free vibration is important. However there is little experimental data regarding their natural frequency, especially from model tests carried out at correct stress levels. This paper presents the results of novel monopile and GBF tests using a centrifuge to directly determine the natural frequency (f_n) of the foundation-soil system. The natural frequencies of wind turbine monopiles and GBFs in centrifuge models were measured during harmonic loading using a piezo-actuator, with the results confirming that soil-structure interaction must be considered to obtain the system’s natural frequency as this frequency reduces substantially from fixed-base values. These results will contribute in preventing resonance induced damage in wind-turbines.     

Synthesis of polymer supported Ni (II)-Schiff Base complex and its usage as a catalyst in sodium borohydride hydrolysis

Influence of using as catalysis, Ni-Schiff Base complex which we previously synthesized [1] used to support with amberzyme oxirane resin (A.O.R.) polymer for increasing the catalytic activity in NaBH₄ hydrolysis reaction, to hydrogen generation was studied. The prepared catalyst was characterized by using SEM, XRD, BET, FT-IR analyze technique. Polymer supported Ni-Schiff Base complex catalyzed NaBH₄ hydrolysis reaction was investigated depending on concentration of NaBH₄, concentration of NaOH, temperature, percentage of Ni complex in total polymer supported Ni-Schiff Base complex and amount of catalyst factors. The maximum hydrogen production rate from hydrolysis of sodium borohydride with nickel-based complex catalyst compared to the pure nickel catalyst is increased from 772 mL H₂·g^?1 cat.·min^?1 to 2240 mL H₂ g^?1 cat.·min^?1 [1], and with supported amberzyme oxirane resin polymer this nickel based complex catalyst was increased to 13000 mL H₂·g^?1 cat.·min^?1 at 30 °C. The activation energy of complex catalyzed NaBH₄ hydrolysis reaction was found as 25.377 kJ/mol. This work also includes kinetic information for the hydrolysis of NaBH₄.     

面向可解释性的物体拓扑结构骨架表征方法

目的 模式识别中，通常使用大量标注数据和有效的机器学习算法训练分类器应对不确定性问题。然而，这一过程缺乏知识表征和可解释性。认知心理学和实验心理学的研究表明，人类往往不使用代价如此巨大的机制，而是使用表征、归纳、推理、解释和约束传播等与符号主义人工智能方法类似的手段来应对物体识别中的不确定性并提供可解释性。因此本文旨在从传统的符号计算出发，利用骨架拓扑结构表征提供一种可解释性的思路。方法 以骨架树为基本手段来形成物体拓扑结构特征和几何特征的形式化表征，并基于泛化框架对少量同类表征进行知识抽取来形成关于物体类别的知识概括显式化表征。结果 在形成物体类别的概括表征实验中，通过路径重建直观展示了同类属物体上得到的最一般表征的几何物理意义。在可解释性验证实验中，通过跨数据的拓扑应用展示了新测试样本相对于概括表征的特定差异，表明该表征具有良好的可解释性。最后在形状补全的不确定性推理实验中，不仅可以得到识别结论，而且清晰展示了识别背后做出的判断依据，进一步验证了该表征的可解释性。结论 实验表明一般化的形式表征能够应对尺寸、颜色和形状等不确定性问题，本文方法避免了基于纹理特征所带来的不确定性，适用于任意基于基元的表征方式，具有更好的鲁棒性、普适性和可解释性，计算代价更小。