Formation cross sections of nuclei with (n,2n) reactions

Ｆｏｒｍａｔｉｏｎｃｒｏｓｓｅｃｔｉｏｎｓｏｆｎｕｃｌｅｉｗｉｔｈ（ｎ，２ｎ）ｒｅａｃｔｉｏｎｓＣｈｅｎＸｕｅＳｈｉ，ＸｉｅＫｕａｎＺｈｏｎｇ，ＺｈｏｕＳｈｅｎｇＭｏ，ＹａｎＱｉｎｇＱｕａｎ（ＳｈａｎｇｈａｉＩｎｓｔｉｔｕｔｅｏｆＮｕｃｌｅ...     

基于小波分析的听觉滤波器组模型

对听觉滤波器组模型进行了研究。比较分析了伽马通(Gammatone)听觉滤波器组模型和基于小波分析的高斯小波听觉滤波器组模型,分别给出了预测听阈曲线并且与标准听闻曲线进行了比较,结果表明高斯小波听觉滤波器组模型更接近实际人耳滤波效果。将高斯小波听觉滤波器组模型的预测特征响度与德国朗德(Head Acoustics)公司的Artemis软件计算出的特征响度进行分析比较,结果表明,每个特征频带的响度差值都小于0.6 sone。     

Stereo effect of image converted from planar

Research on planar-to-stereo image conversion has significant theoretical and practical implications for image processing. In this paper we use a method which segments an image into sub-blocks to perform this kind of conversion; parameters such as random variables are used for conversion control. We use two quantitative criteria, cross-entropy and root-mean-square error, to evaluate the stereo effect. Furthermore, the stereo effect that the random variables create is discussed. The results of the experiment show that, (i) when all random variables have the same distribution, different values of these random variables only slightly affect the stereo effect; and (ii) when different distributions are applied to the random variables, the cross-entropies or root-mean-square errors are slightly different, which indicates different distributions have a small influence on the stereo effect. Generally, we recommend normal distribution for better stereo effect in most cases.     

主题数据库技术的亲合性分析方法研究

企业信息化的本质是企业数据环境的改造,信息化过程必须以主题数据库为主线,逐步建立高档次数据环境。文章对主题数据库技术中的亲合性分析方法进行分析和改进,给出了亲合性分析的改进单向性模型和计算公式;并通过实例对企业活动之间的相关性进行分析,形成聚合性矩阵来建立主题数据库。     

Pathological lung segmentation based on random forest combined with deep model and multi-scale superpixels

Accurate segmentation of lungs in pathological thoracic computed tomography (CT) scans plays an important role in pulmonary disease diagnosis. However, it is still a challenging task due to the variability of pathological lung appearances and shapes. In this paper, we proposed a novel segmentation algorithm based on random forest (RF), deep convolutional network, and multi-scale superpixels for segmenting pathological lungs from thoracic CT images accurately. A pathological thoracic CT image is first segmented based on multi-scale superpixels, and deep features, texture, and intensity features extracted from superpixels are taken as inputs of a group of RF classifiers. With the fusion of classification results of RFs by a fractional-order gray correlation approach, we capture an initial segmentation of pathological lungs. We finally utilize a divide-and-conquer strategy to deal with segmentation refinement combining contour correction of left lungs and region repairing of right lungs. Our algorithm is tested on a group of thoracic CT images affected with interstitial lung diseases. Experiments show that our algorithm can achieve a high segmentation accuracy with an average DSC of 96.45% and PPV of 95.07%. Compared with several existing lung segmentation methods, our algorithm exhibits a robust performance on pathological lung segmentation. Our algorithm can be employed reliably for lung field segmentation of pathologic thoracic CT images with a high accuracy, which is helpful to assist radiologists to detect the presence of pulmonary diseases and quantify its shape and size in regular clinical practices.

     

A novel intelligent verification platform based on a structured analysis model

An intelligent verification platform based on a structured analysis model is presented.Using an abstract model mechanism with specific signal interfaces for user callback,the unified structured analysis data,shared by the electronic system level design,functional verification,and performance evaluation,enables efficient management review,auto-generation of code,and modeling in the transaction level.We introduce the class tree,flow parameter diagram,structured flow chart,and event-driven finite state machine as structured analysis models.As a sand table to carry maps from different perspectives and levels via an engine,this highly reusable platform provides the mapping topology to search for unintended consequences and the graph theory for comprehensive coverage and smart test cases.Experimental results show that the engine generates efficient test sequences,with a sharp increase in coverage for the same vector count compared with a random test.     

低温核供热堆保护系统的研究

高可靠性的保护系统是核供热堆安全可靠运行的重要保证。本文介绍了围绕核供热堆保护系统所开展的设计和研究工作。着重讨论了核供热堆的安全特性;保护系统的功能,保护参数的选择以及保护系统的基本结构。最后简要介绍了目前正在进行的一种新型保护系统的设计方案。     

碱性氨基酸辐射保护机理的电子自旋共振研究

本文研究了组氨酸和精氨酸对胸腺嘧啶的辐射保护机理。用ESR方法和分子轨道计算确证其辐射保护是由于电子清除和从胸腺嘧啶阴离子向碱性氨基酸的转移。碱性氨基酸的亲电子性能随质子化程度而异,在pH=7的条件下,组氨酸对胸腺嘧啶的辐射保护机理可能是电子转移与氢原子转移的协同过程。