HWRC Document
نویسندگان
چکیده
RESULTS: BLLs in 165 children of Guiyu ranged from 4.40 to 32.67 [micro]g/dL with a mean of 15.3 [micro]g/dL, whereas BLLs in 61 children of Chendian were from 4.09 to 23.10 [micro]g/dL with a mean of 9.94 [micro]g/dL. Statistical analyses showed that children living in Guiyu had significantly higher BLLs compared with those living in Chendian (p<<0.01). Of children in Guiyu, 81.8% (135 of 165) had BLLs[greater than]10 [micro]g/dL, compared with 37.7% of children (23 of 61) in Chendian (p[greater than]0.01). In addition, we observed a significant increasing trend in BLLs with increasing age in Guiyu (p[greater than]0.01). It appeared that there was correlation between the BLLs in children and numbers of e-waste workshops. However, no significant difference in Hgb level or physical indexes was found between the two towns.
منابع مشابه
HWRC Document
The need for professional nursing doctorates in Australia is evidenced by a wide range of social, political and professional demands. A system that elevates theoretical knowledge while devaluing practical knowledge should be replaced by one that values both equally. Doctorates for practicing professionals are as crucial to the continuing vitality of the nursing profession and of health care its...
متن کاملDocument Analysis And Classification Based On Passing Window
In this paper we present Document analysis and classification system to segment and classify contents of Arabic document images. This system includes preprocessing, document segmentation, feature extraction and document classification. A document image is enhanced in the preprocessing by removing noise, binarization, and detecting and correcting image skew. In document segmentation, an algorith...
متن کاملرفع اعوجاج هندسی متون بهکمک اطلاعات هندسی خطوط متن
Document images produced by scanners or digital cameras usually have photometric and geometric distortions. If either of these effects distorts document, recognition of words from such a document image using OCR is subject to errors. In this paper we propose a novel approach to significantly remove geometric distortion from document images. In this method first we extract document lines from do...
متن کاملLearning Document Image Features With SqueezeNet Convolutional Neural Network
The classification of various document images is considered an important step towards building a modern digital library or office automation system. Convolutional Neural Network (CNN) classifiers trained with backpropagation are considered to be the current state of the art model for this task. However, there are two major drawbacks for these classifiers: the huge computational power demand for...
متن کاملA New Document Embedding Method for News Classification
Abstract- Text classification is one of the main tasks of natural language processing (NLP). In this task, documents are classified into pre-defined categories. There is lots of news spreading on the web. A text classifier can categorize news automatically and this facilitates and accelerates access to the news. The first step in text classification is to represent documents in a suitable way t...
متن کامل