BaFX：Eu（X：Cl,Br）中电子陷阱的研究

Ｘ线影像板需要近红外光激励。掺入Ｃａ＾２＋,Ｓｒ＾２＋,Ｍｇ＾２＋后,用６５０￣７００ｎｍ光激励ＢａＦＸ：Ｅｕ＾２＋,可以更为灵敏。用正电子湮没寿命谱,电子顺磁共振谱,加热发光谱和光激励发光谱,研究了Ｘ射线辐照后ＢａＦｘ：Ｅｕ（Ｘ：Ｃｌ,Ｂｒ）电子陷阱的性质、状态、密度和转换。     

高温氧化膜Cr2O3和NiO中应力松弛过程

用Ｘ射线原位应力测定了高温氧化膜Ｃｒ２Ｏ３和ＮｉＯ中的应力．结果表明,Ｃｒ２Ｏ３／Ｃｒ和ＮｉＯ／Ｎｉ体系氧化膜的生长应力分别为－１．９４９ＧＰａ和６５２ＭＰａ．在冷却过程中,Ｃｒ２Ｏ３／Ｃｒ体系发生很大的应力松弛过程,其主要表现形式为氧化膜翘曲和开裂;而在ＮｉＯ／Ｎｉ体系中,由于ＮｉＯ薄膜具有双层结构承受不同应力状态而获得松弛．     

WO3粉在高速层间剪切条件下的颗粒破碎特征

研究了WO3粉和W粉的剪切破碎时间对WO3粉和W粉的沉降曲线、平均粒度、BET比表面及松装密度的影响.用TEM和SEM对剪切破碎前后的粉末进行了直接观察.结果表明:新型剪切破碎机能有效地粉碎微米级WO3等脆性粉末,同时可以破坏超细W粉中的桥接团粒,使W粉和WO3粉的松装密度增加1倍以上,但对比表面积影响不大.     

X射线数字化仪在弹道研究中的应用

该文研制了采用CCD逐行扫描技术的X射线数字化仪，与Scandiflash射线源构成瞬态脉冲X射线诊断系统，并将之应用于弹道研究。该数字化仪采用光电成像器件，将光信号转换成电信号，通过A／D转换，图像复原等技术，可以同时捕捉到弹道过程中4个时刻的弹道轨迹图像。     

软X射线多层膜透射式起偏器和检偏器设计

叙述了软X射线波段多层膜透射式起偏器和检偏器的设计原理，提出了设计准则，通过该准则设计的多层膜偏振元件能够同时满足具有较大的光通量和偏振度要求．同时还优化了不同膜厚比情况下软X射线多层膜偏振元件的性能，讨论了在多层膜制作过程中，由于表界面粗糙度和扩散的不同对元件性能的影响，这些工作为制作软X射线多层膜透射式起偏器和检偏器提供了设计基础。     

体表测量定位小针刀治疗第三腰椎横突综合征

第三腰椎横突综合征是以第三腰椎横突尖部明显压痛为特征的常见慢性腰腿痛。传统的封闭、按摩、理疗、口服药物等非手术疗法可使症状缓解或暂时消除，但经常反复，难以治愈，严重影响患者工作和生活。我院自2002年以来，采用小针刀疗法治疗第三腰椎横突综合征，疗效显著，现报告如下。     

应用软X射线对林木种子生活力检验的探讨

应用软X射线检验林木种子活力 ,可以快速、准确地判断林木种子的活力 ,从而快速得到林木种子的播种品质 ,为林木种子检验提供了一个全新的检验方法     

使用IEEE802.1X技术优化校园网计费管理

通过对IEEE 80 2 .1X技术的认证计费系统的分析 ,论述如何用其解决校园网计费管理中现存的问题 ,优化校园网的计费管理     

Vibration Analysis of Digital Radiography System for Large Container Inspection

The cantilever vibration characteristics of a digital radiography system were analyzed to predict the effect of vibration on the performance of a mobile container inspection system. The static deformation,vibration mode and natural frequency of the cantilever of the digital radiography system were calculated with the ALGOR Finite Element System to verify the strength and rigidity of the cantilever. The maximum amplitude of the cantilever vibration occurs as it starts accelerating. The predictions show good agreement with test results, indicating that the finite element model of the cantilever structure accurately models the mechanical characteristics.     

Classification of Medical Brain Images

Since brain tumors endanger people‘s living quality and even their lives, the accuracy of classification becomes more important. Conventional classifying techniques are used to deal with thosedatasets with characters and numbers. It is difficult, however, to apply them to datasets that include brain images and medical history (alphanumeric data), especially to guarantee the accuracy.For these datasets, this paper combines the knowledge of medical field and improves the traditional decision tree. The new classification algorithm with the direction of the medical knowledge not only adds the interaction with the doctors, but also enhances the quality of classification. The algorithm has been used on real brain CT images and a precious rule has been gained from the experiments. This oaoer shows that the ahzorithm works well for real CT data.