将硬件引入“面向对象程序设计”课程实验教学

针对“面向对象程序设计”课程实验内容的设置容易使学生产生学之无用的思想及学后不会用的问题,结合电子信息专业培养特色,压缩了传统的、基本的实验内容,增加了应用性强的实验项目,并将硬件引入实验教学。实践表明,改进后的实验教学模式效果良好。     

浅谈政府公文交换系统的发展

在社会信息化的不断推进过程中,各级政府的办公自动化需求也在不断升级,公文交换系统多样化且技术更新加速,随着改革的深入和我国加入WTO,公文交换系统的建设已经成为当前我国信息化建设的首要任务.     

Supervised classification of share price trends

Share price trends can be recognized by using data clustering methods. However, the accuracy of these methods may be rather low. This paper presents a novel supervised classification scheme for the recognition and prediction of share price trends. We first produce a smooth time series using zero-phase filtering and singular spectrum analysis from the original share price data. We train pattern classifiers using the classification results of both original and filtered time series and then use these classifiers to predict the future share price trends. Experiment results obtained from both synthetic data and real share prices show that the proposed method is effective and outperforms the well-known K-means clustering algorithm.     

Cracking the walnut: Using a computer game to impact cognition,emotion, and behavior of highly aggressive fifth grade students

Three fifth grade highly aggressive students participated in a study examining effects of an aggression intervention game. Using single-subject multiple baseline research design, the effect of the game was measured across three domains: attribution of peer intent (cognitive), emotional response (affective) and behavior response (behavioral). The results indicate that, while there were observable individual differences, the game had an immediate impact on attribution of peer behavior across all participants, had a less predictable impact on reported behavioral reactions, and had no discernable impact on reported emotional response. Theoretical and practical implications of the study are discussed.     

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。     

Lightweight deep learning methods for panoramic dental X-ray image segmentation

Neural Computing and Applications - Dental X-ray image segmentation is helpful for assisting clinicians to examine tooth conditions and identify dental diseases. Fast and lightweight segmentation...     

Editorial: Machine Learning and Intelligent Communications (MLICOM 2018)

Mobile Networks and Applications -     

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...     

Confidence regions of two-stage stochastic linear complementarity problems

Two-stage stochastic linear complementarity problems (TSLCP) model a large class of equilibrium problems subject to data uncertainty, and are closely related to two-stage stochastic optimization problems. The sample average approximation (SAA) method is one of the basic approaches for solving TSLCP and the consistency of the SAA solutions has been well studied. This paper focuses on building confidence regions of the solution to TSLCP when SAA is implemented. We first establish the error-bound condition of TSLCP and then build the asymptotic and nonasymptotic confidence regions of the solutions to TSLCP by error-bound approach, which is to combine the error-bound condition with central limit theory, empirical likelihood theory, and large deviation theory.     

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...