独立学院学生计算机基础学习兴趣的培养

独立学院计算机基础课程教学多会出现学生学习兴趣不浓的问题,结合计算机基础的课程特点,分析目前计算机基础教学的现状,阐述学生学习兴趣不浓的原因,经教学实践提出增强学生学习兴趣的若干方法,为提高学生计算机基础课程学习兴趣提供新的思路。     

面向微博平台的产品市场分析模型研究

通过对面向微博平台的产品市场分析过程进行抽象,提出了3层分析模型。第一层实现了数据准备模块,为兴趣分析提供规范化的数据。第二层通过情感分析提取微博平台上与产品相关的用户兴趣。第三层利用用户兴趣信息计算产品的满意度和关注度来表现产品市场形势。整个模型提供了面向微博平台搭建产品市场分析系统的快速解决方案。     

FLASH动画制作课程教学心得

Flash动画制作课程的教学目的是使学生在掌握动画制作基本原理的基础上,融会自己的思维及创意,制作出一部部优秀的Flash作品。本文主要从学生、教师和学校角度探讨如何提高该门课程的教学质量。     

A minimum Hellinger distance estimator for stochastic differential equations: An application to statistical inference for continuous time interest rate models

A minimum disparity estimator minimizes a φ-divergence between the marginal density of a parametric model and its non-parametric estimate. This principle is applied to the estimation of stochastic differential equation models, choosing the Hellinger distance as particular φ-divergence. Under an hypothesis of stationarity, the parametric marginal density is provided by solving the Kolmogorov forward equation. A particular emphasis is put on the non-parametric estimation of the sample marginal density which has to take into account sample dependence and kurtosis. A new window size determination is provided. The classical estimator is presented alternatively as a distance minimizer and as a pseudo-likelihood maximizer. The latter presentation opens the way to Bayesian inference. The method is applied to continuous time models of the interest rate. In particular, various models are tested using alternatively tests and their results are discussed.     

感兴趣区域的非线性变换多描述编码

介绍一种基于感兴趣区域的非线性变换的多描述图像编码,能够与目前的标准图像压缩算法兼容,对图像的感兴趣区域进行更好的保护。由感兴趣区域的非线性几何变换产生冗余,对图像进行采样形成多描述编码。通过仿真实验,证实当图像在差错信道下传输而丢失描述时,该算法能够使图像感兴趣区域得到更好的恢复。     

IVDQP—物联网内基于兴趣向量的分布式查询处理方法

物联网内资源按需检索是构建高效率物联网应用的必备功能。实现一种基于兴趣的数据单播查询处理方法IVDQP,采用一种单播的方式对任意物联网节点提出的数据检索请求进行节点间传递,并以一种累积的方式将中间节点上的检索结果按照查询单播传递路径返回给查询节点。与Flooding算法的对比实验表明,提出的这种物联网内单播查询处理方法不仅能够迅速定位尽可能多的符合查询要求的数据,而且能够保证引入尽可能少的节点间的消息交换,从而为高效物联网应用的实现提供技术支持。     

Learning Fast Emulators of Binary Decision Processes

Computation time is an important performance characteristic of computer vision algorithms. The paper shows how existing (slow) binary decision algorithms can be approximated by a (fast) trained WaldBoost classifier. WaldBoost learning minimises the decision time of the classifier while guaranteeing predefined precision. We show that the WaldBoost algorithm together with bootstrapping is able to efficiently handle an effectively unlimited number of training examples provided by the implementation of the approximated algorithm. Two interest point detectors, the Hessian-Laplace and the Kadir-Brady saliency detectors, are emulated to demonstrate the approach. Experiments show that while the repeatability and matching scores are similar for the original and emulated algorithms, a 9-fold speed-up for the Hessian-Laplace detector and a 142-fold speed-up for the Kadir-Brady detector is achieved. For the Hessian-Laplace detector, the achieved speed is similar to SURF, a popular and very fast handcrafted modification of Hessian-Laplace; the WaldBoost emulator approximates the output of the Hessian-Laplace detector more precisely.     

基于感兴趣区梯度方向直方图的行人检测

针对以梯度方向直方图作为人体特征的行人检测存在向量维数较大、检测时间较长的问题,提出基于感兴趣区梯度方向直方图的行人检测方法,分别在头部及四肢等重点区域计算梯度方向直方图,有效地减少了向量维数。实验结果表明,该方法在检测率基本不变的情况下提高了检测速度。     

浅谈社会实践中的专业兴趣培养

社会实践是让学生了解、激发、培养自己的专业兴趣爱好,为将来更好地投身社会打下坚实基础的重要途径。在社会实践中,了解行业背景,激发职业自豪感是培养专业兴趣的基础;直面实践对象,激发科学好奇心理是培养专业兴趣的重要途径;参与具体实践,体验科学技术在生产中的力量是培养专业兴趣的强大动力。     

Design and development of a fuzzy agent-based model to measure interest rate expectations

The financial system, which has been investigated by various researchers, is a rather complicated environment. Most research has only been concerned with quantitative factors (technical indexes), though qualitative factors (e.g., political situation, social conditions, international events, government policies, among others) play a critical role in the financial system environment, determining the regulatory policies within an economy. This paper presents a fuzzy knowledge-based model to measure the qualitative aspects related to one of the most important financial instruments used to regulate an economy, the base interest rate. The development and assessment of the proposed model was based on the Brazilian economy. Evaluation of the results obtained indicates that our approach gives good results when compared with real data and statistical-based forecasting tools. The main advantage of our approach is its capability to forecast long term interest rate expectations when combined with a powerful econometric model.