一种基于颜色特征的感兴趣目标提取方法

针对现有的感兴趣区域(ROI)提取方法边缘不清晰、区域不完整等问题,提出一种ROI提取方法.首先采用颜色局部特征的信息量大小衡量兴趣度的大小,然后融合颜色特征信息量图获得图像的显著图(SM),再进行阈值分割,得到显著值大的区域,即ROI.实验结果表明,该方法能有效地提取出感兴趣的对象,SM中目标区域的显著值均匀、边缘清晰;与人工标记的ROI比较,该方法召回率为79.71％,精度为78.53％,优于已有的ROI提取方法.     

构建微博用户兴趣模型的主题模型的分析

分析了不同的主题模型,通过实验比较了3种主题模型构建的微博用户兴趣模型的性能。实验结果表明:TwitterLDA适用于新文档或新用户的预测,AuthorLDA产生的主题具有较高的区分度,而UserLDA和AuthorLDA能更好地反映出用户的社交网络关系。上述工作为进一步研究主题模型如何应用于微博的个性化信息推荐、情感分析和话题检测与跟踪等文本挖掘应用奠定了基础。     

高职电子技术课程的兴趣教学法

高职院校学生学习基础相对较差,对于传统的课堂教育难以适应,提出在电子技术教学中实施兴趣教学法,提高学生主动学习的积极性,也有助于提高教学质量。电子技术课实践性强,几乎每堂课都会涉及到实验,这样可以长期在实验室上课或者在教室做演示实验,每次课前教师列一个清单让学生提前到实验室准备好实验器材,学生在准备器材的过程中就会带着疑问：这是做什么用的呢？学生有了疑问就会有学习的好奇心,进而也就激发了对该课程的学习兴趣。     

谈高校艺术设计专业的色彩教学改革

如何探索一套适用于艺术设计专业特点的基础教学方法,利用有限的时间,通过有效的训练,为专业设计建立联系,打下基础,一直是艺术设计教育者应该思考和探索的问题。     

浅谈Visual Basic的教学

Visual Basic是一种面向对象的、采用事件驱动运行机制的可视化的高级程序设计语言。作为普通高校非计算机专业的一门基础课,实践性较强,学生不易掌握。本文结合教学实践从激发学生学习兴趣、改变教学方法、加强实践教学等方面探讨了如何更好的完成Visual Basic的教学。     

从《Visual Basic程序设计》谈课堂教学改革

从计算机二级等级考试出发,根据《Visual Basic程序设计》课程自身的特点,对《Visual Basic程序设计》的教学方法进行改革。改革的基本原则:课堂上应以学生为本,注重激发学生的学习兴趣,帮助学生体验成功,增强自信。具体做法:不拘泥于课本,从顺序上对教学内容进行大胆地调整,将教学内容进行有机分解、组合,应用案例教学法。     

Leveraging online communities in fostering adaptive schools

There has long been a call for schools to prepare students for the twenty-first century where skills and dispositions differ significantly from much of what has historically characterized formal education. The knowledge based economy calls for policy and pedagogical efforts that would transform schools. Schools are to foster communities of learners. This paper suggests that para-communities may be points of leverage in the fostering of adaptive schools. A critical analysis is done on the differences between para-communities (such as online communities) and schools; and an argument is made that they each serve differing goals and should be left distinct because they achieve different societal and economic demands.     

Robust Estimation of GARMA Model Parameters with an Application to Cointegration among Interest Rates of Industrialized Countries

We review the literature on long memory ARFIMA and GARMA models andintroduce a new efficient estimator for GARMA models, which we show to berobust. Next we conduct a Monte Carlo study to demonstate the power of theDickie–Fuller test when the data are generated from a stationary GARMAprocess. We conclude with a brief discussion of cointegration in the contextof GARMA models with an application to international interest rates.     

静态图像编码研究进展

多媒体及Internet的迅速发展导致了对图像编码技术更高的要求。首先以波形编码、第二代编码技术和分形编码技术为线索对静态图像编码技术的发展及编码技术中所存在的一些问题进行了讨论,并从图像编解码的观点讨论了图像在有噪信道上传输的误码率情况和适应于传输的一些图像编码技术;同时对即将成为新的静态图像编码标准的JPEG－2000的目标、编码机制、POI编码的Maxshift方法以及对码流的直接操作等情况进行了讨论。尽管压缩效果一直是任何编码方案所追求的目标,但其它特性,像基于内容的编码、可分级性编码以及鲁棒性编码等也是选择一个好的编码方案时应该考虑的,据此最后对图像编码技术的发展方向进行了展望。     

Spatial interest pixels (SIPs): useful low-level features of visual media data

Visual media data such as an image is the raw data representation for many important applications. Reducing the dimensionality of raw visual media data is desirable since high dimensionality degrades not only the effectiveness but also the efficiency of visual recognition algorithms. We present a comparative study on spatial interest pixels (SIPs), including eight-way (a novel SIP detector), Harris, and Lucas‐Kanade, whose extraction is considered as an important step in reducing the dimensionality of visual media data. With extensive case studies, we have shown the usefulness of SIPs as low-level features of visual media data. A class-preserving dimension reduction algorithm (using GSVD) is applied to further reduce the dimension of feature vectors based on SIPs. The experiments showed its superiority over PCA.