基于WebServer 的移动应用结构分析与系统建设

移动学习通过便携式移动计算设备能够在任何时间、任何地点进行学习,在移动应用系统的建设过程中,利用SSH整合框架进行Web Server程序的开发,把表现逻辑和控制逻辑分离开来,分别由表现层、业务逻辑层来处理,降低了系统总架构的耦合性,使软件结构清晰,可扩展性和可维护性更高。     

入侵检测系统研究进展

入侵检测系统是重要的信息安全措施.本文对目前入侵检测系统的研究进展进行了详尽的总结分析,指出了入侵检测系统的最新发展及动态呈现的新特点,重点分析了智能算法的应用、数据融合和报警关联技术的引入、检测对象变化情况及与其它安全技术的协作性;阐述了对入侵检测系统的测试评估方面的最新发展情况以及目前入侵检测标准化的现状;最后,展望了入侵检测系统发展的方向.     

Robust semi-supervised discriminant embedding method with soft label in kernel space

Neural Computing and Applications - Considering some problems of local linear embedding methods in semi-supervised scenarios, a robust scheme for generating soft labels is designed and a...     

稀疏图像内容情况下显微镜自动聚焦算法

自动聚焦是全自动显微成像中的关键技术.为了解决在极低内容密度(稀疏内容)情况下传统聚焦方法无法成功找到焦平面的问题提出一种基于图像内容重要度加权的聚焦函数增强算法.该算法利用聚焦过程中当前图像和参考图像中对应像素沿光轴方向的梯度变化规律对像素进行分类,并根据不同像素对图像清晰程度判决的贡献大小自适应调整当前像素的重要度因子,通过这种方式增强了图像内容像素的计算权重并有效抑制了镜头杂质及背景噪声,极大地增强了聚焦曲线的陡峭度在此基础上,采用图像分块的方式来克服显微镜Z轴机械系统误差对算法性能的影响并降低算法复杂度.实验结果表明,在图像内容非常稀疏的情况下,该算法的聚焦成功率高达90％,而传统聚焦算法的成功率仅为24％.     

Preparation of ~(67)Ga-EDTMP and its biodistribution studies

67Ga-EDTMP was synthesized in a single step by adding 67GaCl3 to EDTMP solution. Dependences of the radiolabeling yield of 67Ga-EDTMP on EDTMP concentration, pH and reaction time were examined. Under the optimum conditions, the radiolabeling yield of 67Ga-EDTMP was more than 97%. A biodistribution experiment in mice showed that 67Ga-EDTMP was mainly absorbed by skeleton and reached 13.25% at 0.5 h after injecting, then kept a high level in 72 h with a maximum value of 16.82% at 48 h. The results suggest that 67Ga-EDTMP might be a potential bone pain palliation radiopharmaceutical due to its high skeletal uptake, rapid blood clearance and relatively low soft-tissue absorption. But further work must be done to determine whether 67Ga-EDTMP is useful in the treatment of painful osseous metastases.     

基于Unix环境的3G移动数据业务平台的开发与研究

针对移动数据业务发展和运营过程中出现的问题,本文给出了一种基于Unix环境下的3G移动数据业务平台（MDSP）的解决方案,同时本平台可应用于现有传统2G、2.5G数据网络应用环境下.提出了该平台的体系结构和实现的关键技术.该平台使得数据业务发布迅速、统一、可管理、杜绝和防止了SP欺诈、提高了运营商的综合竞争力、取得了极大的商业价值和社会效益.     

Ba1-xLaxTiO3陶瓷的晶界再氧化机理研究

不同La施主掺杂浓度的BaTiO3陶瓷在H2／Ar的还原气氛下烧结后，再在氧分压PO2=260Pa的气氛（Ar和O2的混合气体）下进行氧化，通过氧流量计检测还原样品在再氧化过程的吸氧行为；用TEM分析样品氧化后显微结构的变化，测定了在不同最高氧化温度下氧化样品的PTCR效应以及复阻抗图谱．结果表明；氧流量计在升温阶段检测到三个不同行为的吸氧峰，峰Ⅰ（起始温度-250℃）为氧空位的填充过程；峰Ⅱ（起始温度-800℃）和峰Ⅲ（起始温度-1250℃）为还原相的氧化过程，具体来说，峰Ⅱ是通过晶界扩散提供氧使靠近晶界附近的区域被氧化；而峰Ⅲ是由晶格扩散过程控制，氧化过程从晶界逐渐向晶粒内部区域扩展，并伴随着富Ti的Ba6Ti17O40相的沉淀．在还原相向氧化相的转变过程中，于晶界处形成了两个具有晶界势牟的电结构单元而使陶瓷旱现强PTCR效应．     

基于变分的图像恢复算法及收敛性

提出了一种保持边缘的正则化图像恢复算法,该方法可有效地用于求解线性逆问题的 非凸优化过程.通过对正则化函数及相应泛函性质的理论分析,得出了使泛函达到最小的正则 化函数表达式;引入一个与原非凸泛函相应的二元泛函,将非凸优化问题转化为本质上的凸优 化问题,采用松弛迭代算法获得非凸优化问题的局部极小解;证明了所提出的算法是全局收敛 的.通过实验验证了算法的有效性.     

中文问答系统中基于主题和焦点的问题理解

问答系统应该能够用准确、简洁的语言回答用户提出的问题.问题理解是问答系统的首要的分析工作,分析的结果的正确率直接影响后续处理.提出了一种基于用户问题的主题和焦点的问题理解的方法,该方法以问题的疑问词、句法分析、问题焦点、问题主题在知网中的首义原作为问题分类特征.实验结果证明,该方法对提高分类的准确率有较好的效果.     

Pruning least objective contribution in KMSE

Although kernel minimum squared error (KMSE) is computationally simple, i.e., it only needs solving a linear equation set, it suffers from the drawback that in the testing phase the computational efficiency decreases seriously as the training samples increase. The underlying reason is that the solution of Naïve KMSE is represented by all the training samples in the feature space. Hence, in this paper, a method of selecting significant nodes for KMSE is proposed. During each calculation round, the presented algorithm prunes the training sample making least contribution to the objective function, hence called as PLOC-KMSE. To accelerate the training procedure, a batch of so-called nonsignificant nodes is pruned instead of one by one in PLOC-KMSE, and this speedup algorithm is named MPLOC-KMSE for short. To show the efficacy and feasibility of the proposed PLOC-KMSE and MPLOC-KMSE, the experiments on benchmark data sets and real-world instances are reported. The experimental results demonstrate that PLOC-KMSE and MPLOC-KMSE require the fewest significant nodes compared with other algorithms. That is to say, their computational efficiency in the testing phase is best, thus suitable for environments having a strict demand of computational efficiency. In addition, from the performed experiments, it is easily known that the proposed MPLOC-KMSE accelerates the training procedure without sacrificing the computational efficiency of testing phase to reach the almost same generalization performance. Finally, although PLOC and MPLOC are proposed in regression domain, they can be easily extended to classification problem and other algorithms such as kernel ridge regression.