动态自学习的入侵检测模型研究

针对目前常见的入侵检测的模型的一些结构性的缺点,提出了基本数据挖掘的动态自学习入侵检测模型DMIDS,给出了动态自学习的正常行为库的更新机制,克服了传统静态检测模型必须完全重新学习才能更新模型甚至无法重新学习的缺陷.通过基于KDD'99数据集的实验,表明其相对于传统的异常检测方法在保证较高检测率的前提下,有效地降低了误报率.     

基于Gossip协议的流媒体播放机制的研究与改进

针对Gossip协议数据传播随机性与不确定性问题,提出了一种混合结构方式.该方式将非结构化P2P网络和结构化P2P网络相结合,通过增加数据片预取调度算法,弥补了Gossip协议数据传输的随意性.实验结果表明,此方式提高了节点成功播放率,降低了系统开销.     

基于遗传算法的污水处理模糊控制方法

模糊控制中的模糊推理规则和隶属函数的选取往往依据相关专家或技术人员的实际经验,对具有较强的非线性系统和未知动态环境条件下,其控制性能往往达不到很好的效果.使用遗传算法同时对隶属函数和模糊规则进行优化,从而使模糊推理规则和隶属函数的确定摆脱了人为经验的局限,提高了模糊控制的自适应能力.在此基础上设计出模糊控制器,并将其应用于污水处理溶解氧的控制中.实验结果表明,该控制器能够使溶解氧快速、准确地达到期望的要求.     

提高计算机基础实践教学质量的途径研究

本文分析了高校非计算机专业计算机基础实践教学中存在的问题,结合从教学过程中得到的经验与思考,分别从师资力量、教学理念、教学内容、教学方法、上机实践、网络资源和监督评价方面,对提高计算机基础实践教学质量的途径做了一些研究与探索。     

基于矩阵输入的ERP系统订单改进方案

本文在传统ERP系统的基础上,针对服饰、鞋帽、拉链等具有多属性产品的制造行业,提出一种运用矩阵输入对销售订单的改进方案。它从订单的特点出发,建立一般订单模型,详细介绍了矩阵式订单的设计,实现方法,论述了其适用范围和使用特点,最后分析了矩阵式录入订单的执行效率和可扩展性。     

Dijkstra算法在肾脏移植交换系统中的应用

在肾脏移植过程中,经常存在一个病人的亲属愿意将自己的一个肾脏捐赠给此病人,但是他们的肾脏匹配不够好,只能放弃的情况,这明显是一种资源的浪费.一个可行的方案就是肾脏交换系统.在这篇论文中,我们提出了两种解决方法,分别代表了解决此问题的两个解决方向.给一些相应的组织,如美国的OPTN,一定的改进建议,并对其他国家建立类似的组织起到一定的指导作用.     

An automatic docking method for large-scale sections based on real-time pose measuring and assembly deviation control

Aiming at the problem of poor accuracy consistency of large sections’ docking assembly, an automatic docking method using multiple laser trackers to measure the position and posture of the docking sections in real time was proposed. In the solution of the pose of the docking section, real-time pose measurement of the docking section was realized by establishing a global coordinate system and a coordinate fusion method of three or more laser trackers. In the automatic control of the docking process, the real-time communication protocol and the circular negative feedback control strategy of measurement-adjustment-re-measurement are adopted, and the fully-automated docking of large sections is realized. Finally, an experimental verification system was set up, and the docking of the large-scale section reduction models was realized under the requirements of docking accuracy, and the effectiveness of the automatic docking scheme was successfully verified.     

Neural Machine Translation by Fusing Key Information of Text

When the Transformer proposed by Google in 2017, it was first used for machine translation tasks and achieved the state of the art at that time. Although the current neural machine translation model can generate high quality translation results, there are still mistranslations and omissions in the translation of key information of long sentences. On the other hand, the most important part in traditional translation tasks is the translation of key information. In the translation results, as long as the key information is translated accurately and completely, even if other parts of the results are translated incorrect, the final translation results’ quality can still be guaranteed. In order to solve the problem of mistranslation and missed translation effectively, and improve the accuracy and completeness of long sentence translation in machine translation, this paper proposes a key information fused neural machine translation model based on Transformer. The model proposed in this paper extracts the keywords of the source language text separately as the input of the encoder. After the same encoding as the source language text, it is fused with the output of the source language text encoded by the encoder, then the key information is processed and input into the decoder. With incorporating keyword information from the source language sentence, the model’s performance in the task of translating long sentences is very reliable. In order to verify the effectiveness of the method of fusion of key information proposed in this paper, a series of experiments were carried out on the verification set. The experimental results show that the Bilingual Evaluation Understudy (BLEU) score of the model proposed in this paper on the Workshop on Machine Translation (WMT) 2017 test dataset is higher than the BLEU score of Transformer proposed by Google on the WMT2017 test dataset. The experimental results show the advantages of the model proposed in this paper.     

基于激光超声表面波检测的瓦斯检测研究

利用SnO2/Pt气敏薄膜对瓦斯气体的选择性吸附作用将引起声表面波在其表面的传播速度发生相应改变的性质,并结合激光超声检测技术,提出了一种新的瓦斯检测方法.采用激光在覆有选择性气体吸附薄膜的抛光铝材表面激发出声表面波,用单芯光纤耦合的反射式光束偏转法对所激发声表面波信息进行采集,进而通过合理的算法可以准确检测出环境中瓦斯气体的体积分数.为瓦斯监测方法提供了一种新途径.     

机房监控系统中数据网关服务器的设计

针对机房监控系统中底层设备与上层软件因紧密耦合导致系统维护困难的问题,采用适配器模式和桥接模式设计了底层数据采集接口,实现现场设备、远程监控端、数据网关之间的松散耦合,将DCOM技术作为数据处理的模型,使网关服务器可以提供远程分布式监控服务。实验结果表明,该设计方式实现了底层设备的多型号多协议兼容,降低维护成本,具有较好的可复用性和可扩展性。