Vegetation becomes sparse higher up the mountains.

He considered a sparsely populated region most suitable, but such regions were few in crowded China.

他认为人烟稀少的地方最合适, 可是这样的地方在人口稠密的中国是不容易找到的.

The mountain villages are lived sparsely. They treat all the who pass by occasionally as guest.

山里人在大山里都住得很稀松, 偶尔路过一个人,全部都当客人.

The fact is the universe is very sparsely peopled.

事实是世界没有足够的地方让人类居住了.

Particularly in business card printing and membership card making transparent near, there is a obvious sparsely.

出格在制卡和会员卡制作透明物时,不离会呈现澄辉的着不朱不匀.

However , It'should not be promoted in the minority nationality areas or in sparsely populated regions.

少数民族地区不要去推广, 人少的地方也不要去推广.

Many slopes are rock fields with sparse vegetation...

许多山坡都是石头地，植被稀疏。

He was a tubby little man in his fifties, with sparse hair...

他50来岁，头发稀疏，身材矮胖。

The Sahara desert is a district sparsely inhabited.

撒哈拉沙漠是个人烟稀少的地区.

This sparsely populated area has no freeway.

这个人口稀少的地区连高速公路都没有.

Surrounded by gigantic rocks and sparsely populated deep valleys, the paintings look dignified and awesome.

这里巨石兀立,深谷苍凉, 容易使人产生敬畏感.

John and Cindy McCain arriving at a sparsely attended Florida rally in January 2008.

一月份的佛罗里达州,麦凯恩和他妻子参加很少人出现的拉力大会.

The river was sparsely lined with willow trees.

河边疏疏落落有几棵柳树.

It was sparsely wooded and desolate.

这里树木稀少,荒无人烟.

Such as: condensed, sparsely, viscosimetry, viscosity, Business card printing and membership production performance, and so on.

如: 颜色 、 稀稠 、 粘度 、 粘性 、 制卡和会员卡制作性能等.

Rural areas in the U . S are more sparsely settled than in Europe or China.

美国的农村地区居民较欧洲和中国稀少.

Plants from equatorial regions have large, thin sparsely hairy leaves.

在赤道地区其植物叶片大而薄,并被以稀毛.

This paper proposes a method of digital literature image compression based on sparsity and synchronization.

提出基于稀疏性与同步性的数字文献图像压缩方法.

It is necessary and possible to lead the concept of sparsity into of labor value.

将稀少性的概念引入劳动价值论既有必要,也有可能.

It discusses the exploitation of sparsity in large LP problems as used in practice.

对高阶线性规划问题实际应用的稀疏技术的开发作了探讨.

We tackle the sparsity problem in two ways-by feature augmentation and switched method.

我们采用了两种方法来提高数据稀疏时预测的准确性,即属于特征递增型的PearAftersvd方法和属于转换型的LCM_STI方法.