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.     

Similarity-based image organization and browsing using multi-resolution self-organizing map

An algorithm is presented in this paper to facilitate the exploration of large image collections based on visual similarities. Starting with an unordered and unannotated set of images, the algorithm first extracts the salient details into feature vectors using both color and gradient information. The feature vectors are then used to train a self-organizing map which maps high-dimensional feature vectors onto a 2D canvas so that images with similar feature vectors are grouped together. When users browse the image collection, an image collage is generated that selects and displays the most pertinent set of images based on which portion of the 2D canvas is currently in view. Flowing from an overview to details is a seamless operation controlled simply by pan and zoom, with representative images selected in a consistent and predictable way. To make organizing larger image collections practical in interactive time, the organization algorithm is designed to run in parallel on graphics processing units. Overall this paper presents an end-to-end solution that facilitates the surfing of image collections in a fresh way.     

砂土的剪胀方程及其塑性势(Ⅰ):发展现状

以能量守恒原理为主线,在各向同性前提下,对Taylor剪胀方程、Cam-clay剪胀方程、修正Cam-clay剪胀方程、Rowe剪胀方程和扩展的Rowe剪胀方程等进行了较全面的综述.论证了剪胀方程和塑性势函数之间的相互转化关系.指出了Lade-Kim塑性势函数和Nova塑性势函数的缺陷之处,即这两个塑性势函数均没有合理耦合临界状态这一概念.     

聚合物在离子选择电极上的应用

本文概述了聚合物膜离子选择电极的发展,制备、应用等方面的研究情况;将聚合物膜离子选择电极分为固态膜类和液态膜类,分别对其优缺点和发展前景加以分析;并讨论了聚合物在敏感膜中的作用,以及聚合物结构对敏感膜性能的可能影响。