Electrochemical investigation of La0.4Sr0.6TiO3 synthesized in air for SOFC application

Journal of Applied Electrochemistry - La-doped titanate materials have been widely investigated as alternative Ni-free anodes for solid oxide fuel cells (SOFCs). In this study, La0.4Sr0.6TiO3 (LST)...     

在ASP.NET 2.0中自动化构建数据访问层

使用ASP.NET2.0所提供的BuildProvider类,将自动化构建的数据访问层源代码编译到程序集中,使得开发者利用Ob-jectDataSource控件,可以简单、快速地实现三层架构的Web应用。     

远程作业技术中公式编辑问题的解决方案

随着远程教育的不断发展,远程作业技术的研究与开发被提到越来越重要的位置。对于理工科专业的基础课来讲,学生在作业中需要输入大量的数学表达式,这些数学表达式最终必须由计算机自动进行识别和批改。针对这种情况,提出了适合于计算机自动识别的数据结构以及特殊结构的数据逻辑关系等,在此基础上对作业系统中的公式编辑器进行了设计和开发。     

基于Struts的Web开发

Struts是目前比较流行的一个基于MVC设计模式的JavaWeb应用框架,文章详细地阐述了Struts框架实现MVC的构架机制及其核心组件和框架特点,介绍了集成在Struts框架内部的Validator框架在具体Web系统中的开发应用,比较了基于该验证框架的两种验证的优缺点。     

Adaptive Clustered Federated Learning for Heterogeneous Data in Edge Computing

Mobile Networks and Applications - Although federated learning has been widely used in collaborative training of machine learning models, its practical uses are still challenged by heterogeneous...     

Low-rank tensor completion via combined Tucker and Tensor Train for color image recovery

Applied Intelligence - In recent years, low-rank tensor completion has been widely used in color image recovery. Tensor Train (TT), as a balanced tensor rank minimization method, has achieved good...     

ADAPTIVE RANKS CLONE AND k‐NEAREST NEIGHBOR LIST–BASED IMMUNE MULTI‐OBJECTIVE OPTIMIZATION

Artificial immune systems (AIS) are computational systems inspired by the principles and processes of the vertebrate immune system. The AIS‐based algorithms typically exploit the immune system's characteristics of learning and adaptability to solve some complicated problems. Although, several AIS‐based algorithms have proposed to solve multi‐objective optimization problems (MOPs), little focus have been placed on the issues that adaptively use the online discovered solutions. Here, we proposed an adaptive selection scheme and an adaptive ranks clone scheme by the online discovered solutions in different ranks. Accordingly, the dynamic information of the online antibody population is efficiently exploited, which is beneficial to the search process. Furthermore, it has been widely approved that one‐off deletion could not obtain excellent diversity in the final population; therefore, a k‐nearest neighbor list (where k is the number of objectives) is established and maintained to eliminate the solutions in the archive population. The k‐nearest neighbors of each antibody are founded and stored in a list memory. Once an antibody with minimal product of k‐nearest neighbors is deleted, the neighborhood relations of the remaining antibodies in the list memory are updated. Finally, the proposed algorithm is tested on 10 well‐known and frequently used multi‐objective problems and two many‐objective problems with 4, 6, and 8 objectives. Compared with five other state‐of‐the‐art multi‐objective algorithms, namely NSGA‐II, SPEA2, IBEA, HYPE, and NNIA, our method achieves comparable results in terms of convergence, diversity metrics, and computational time.     

Using jump-diffusion modeling for valuing real options in infrastructure projects

In infrastructure financed projects, in order to attract private investors, host governments often provide some guarantees. This paper develops a value model of minimum revenue guarantee with multiple-exercise real options under the impact of the emergency incident. The model is applied to infrastructure financed projects using the minimum revenue guarantee under simulation. The simulation results indicate that, before quantifying the value of the minimum revenue guarantee, it is necessary to forecast the jump degree and intensity of the emergency incident, as well as prevent and control risks arising from such emergencies. Otherwise, underestimation of the guarantee value will occur and the government will have to bear huge debt in this condition. We also analyze the dependence of the guaranteed value on the minimum guaranteed revenue level, initial revenue and number of exercise rights. For various conditions, the diagrams of the guaranteed value are also presented.