设计中重引导体验中促优化——“用乘法分配律进行简便计算”的实践体会

案例背景: 当前,“以生为本”的课堂教学理念早已被教师们推崇与实践.以计算教学来说,课堂上已不再像过去那样,教师只教学教材上的算法,甚至要求学生只能按某种算法去算.现在经常可以看见这样的现象:一道计算题出来后,教师常常鼓励、引导学生思考采用不同的算法.很多教师会对学生说:“可以用你自己喜欢的方法计算.”于是问题就出现了,学生用的方法往往不是教师事先估计的“基本方法”或比较好的方法(即教师心里希望学生用的方法).教师的疑问也由此产生,如要不要对多样的算法进行优化、怎样进行算法优化等等.我在教学实践中也同样有过这样的情况和疑问,为此,专门针对算法优化的问题进行了课题研究.     

FARMER: A novel approach to file access correlation mining and evaluation reference model

File semantic has proven effective in optimizing large scale distributed file system. As a consequence of the elaborate and rich I/O interfaces between upper layer applications and file systems, file system can provide useful and insightful information about semantic. Hence, file semantic mining has become an increasingly important practice in both engineering and research community. Unfortunately, it is a challenge to exploit file semantic knowledge because a variety of factors could affect this information exploration process. Even worse, the challenges are exacerbated due to the intricate interdependency between these factors, and make it difficult to fully exploit the potentially important correlation among various semantic knowledges. This article proposes a file access correlation miming and evaluation reference (FARMER) model, where file is treated as a multivariate vector space, and each item within the vector corresponds a separate factor of the given file. The selection of factor depends on the application, examples of factors are file path, creator and executing program. If one particular factor occurs in both files, its value is non-zero. It is clear that the extent of inter-file relationships can be measured based on the likeness of their factor values in the semantic vectors. Benefit from this model, FARMER represents files as structured vectors of identifiers, and basic vector operations can be leveraged to quantify file correlation between two file vectors. FARMER model leverages linear regression model to estimate the strength of the relationship between file correlation and a set of influencing factors so that the “bad knowledge” can be filtered out. To demonstrate the ability of new FARMER model, FARMER is incorporated into a real large-scale object-based storage system as a case study to dynamically infer file correlations. In addition FARMER-enabled optimize service for metadata prefetching algorithm and object data layout algorithm is implemented. Experimental results show that is FARMER-enabled prefetching algorithm is shown to reduce the metadata operations latency by approximately 30%–40% when compared to a state-of-the-art metadata prefetching algorithm and a commonly used replacement policy.     

CORDIC algorithm based on FPGA

It is an important problem that we implement floating point trigonometric functions of high precision with suitable hardware cost for high performance in digit image processing.The coordinate rotational digital computer (CORDIC) arithmetic to is used to solve the above problem in this paper.In order to increase the speed of operation,it chooses the pipeline architecture.The results are disposed by IEEE-754 standard.The CORDIC architecture is modeled by using the verilog HDL and verified with MATLAB program ...     

Adaptive early termination of fast mode decision in MVC based on inter-view correlation

Variable size motion estimation (ME) and disparity estimation (DE) are employed to select the best coding mode for each macroblock (MB) in the current joint multiview video model (JMVM).This technique achieves the highest possible coding efficiency,but it results in extremely large computation complexity which obstructs the multiview video coding (MVC) from practical application.This paper proposes an adaptive early termination of fast mode decision algorithm for MVC.It makes use of the coding information o...     

关于高中数学必修模块教学顺序的建议

2009年秋季开始,赤峰市红山区高中进入了新一轮课改,选用了人教B版作为数学教材。并且规定沿着自然顺序教学,即按照1→2→3→4→5的顺序。经过了一个学年的     

Apriori算法的改进算法设计与分析

提出采用事务压缩和哈希技术相结合方式的改进算法.该算法通过备份数据库Dk生成候选项目集Ck,在生成Ck的同时计算支持度.针对生成频繁2-项目集L2的瓶颈,在生成L2的时候使用DHP算法.从时间复杂度上对Apriori算法和改进算法进行比较,说明改进算法在效率上优于Apriori算法.     

基于区域增长的连通域标记算法的优化

与以往基于区域增长的连通域标记算法用目标点作为种子不同,优化算法将游程作为种子,结合游程和种子算法的优点,减少种子的数量和目标点邻域的搜索次数.实验表明,本算法能有效地减少算法冗余操作,明显提高效率,且性能优于其它算法.     

浅谈算法学习报告在高职计算机专业数学教学中的应用

算法是数学及其应用的重要组成部分,是计算科学的重要基础,在现代社会发挥着越来越大的作用。对于高职计算机专业的学生来说,算法的学刁尤为重要,因为它是学习程序设计语言等专业课的基础。可是,现在的高职数学教材没有这一内容,并且在实际教学中数学理论与专业课程之间严重脱节,让学生觉得数学学习学之无用。因此在高职计算机专业的数学教学中加入算法内容,可以让学生在初步感受算法思想的基础上,结合对具体数学实例的分析,撰写算法学习报告,体验程序框图在解决问题中的作用,为学习程序设计语言等专业课程打下坚实的基础。     

趣味课堂,优化计算——如何实现低年级数学计算教学的有效性

真实的课堂教学应是面对学生真实的认知起点,展现学生真实的学习过程,让每一个学生都有所发展。只有让学生从爱计算,到会计算,再到巧计算,由浅入深,逐步提高,才能真正地提高课堂教学的效率。     

求解矩阵Penrose广义逆的混合智能算法

有效求解矩阵Penrose广义逆是一个困难的问题．首先将求解Penrose广义逆转化为求最小极值问题,结合粒子群算法和差分算法的优点,设计了混合智能算法．仿真实验结果表明：混合智能算法求解Penrose广义逆是有效的和可行的．算法易于计算机实现,计算精度高．