基于排列熵和支持向量机的癫痫发作预测研究

针对癫痫发作给病人带来的巨大伤害,为临床治疗留下足够空余时间,提出一个可以预测癫痫发作的系统模型。对21名癫痫病人进行研究,提取具有较低算法复杂度的排列熵构成特征向量,将其输入支持向量机（support vector machine,SVM）训练出学习模型,用来识别发作期样本,利用投票机制充分考虑病人差异来判断所处状态,最终实现癫痫的实时预测。结果表明,其中81%的发作可以提前平均50多分钟预测到,且具有较低的误报率。为癫痫发作预测系统的理论研究打下坚实基础。     

高效液相色谱法在氟铃脲标准样品制备中的应用研究

标准样品是农残分析巾的必要条件。应用高效液相色谱法进行氟铃脲的纯化、制得氟铃脲标准样品，用DELTA PAK C18柱，以乙腈-水(68：32)为流动相，在波长254nm，室温下进行了保留值定性、定值分析、均匀性及稳定性考察，效果良好。     

水轮发电机组蠕动处理实践

水轮发电机组随着运行时间的增长,机组蠕动现象频出,每次出现的原因和处理方法并不一样。如水布垭水电站出现的接力器行程反馈信号器固定螺钉松动导致的机组蠕动;洞坪水电站推拉杆调整螺母松动,造成接力器行程不同步;晒谷坪电站压紧行程不合适属于导叶立面间隙过大引起的机组蠕动。可见机组蠕动最常见的原因还是导叶立面密封出现问题引起的。在处理过程中一定要针对具体问题做分析,把握问题的关键,并非凡是导叶立面密封有问题就通过捆绑导叶,调整偏心销来解决,费时费力;要做到有针对性的处理,才能从根本上解决问题。     

药用中间体苯丙酮含量的气相色谱/质谱分析

苯丙酮是合成利胆药苯丙醇的重要中间体。本文建立了用气相色谱 /质谱法 (GC/MS)测定苯丙酮含量的方法。组分的定性依靠GC/MS联用技术和NIST谱库标准质谱图对照分析。以苯乙酮为内标 ,苯丙酮含量在 1.0× 10 -5～ 2 .0× 10 -4g/mL范围内呈线性 ,线性相关系数r =0 .994 9,苯丙酮最低检测浓度为 1.0× 10 -8g/mL。该法操作简便、快速 ,结果准确可靠 ,且具有很好的实用价值     

Secure and robust image hashing via compressive sensing

Image hash functions find extensive applications in content authentication, database search. This paper develops a novel algorithm for generating a secure and robust image hash based on compressive sensing and Fourier-Mellin transform. Firstly, we incorporate Fourier-Mellin transform into our method to improve its performance under rotation, scale, transition attacks. Secondly, we exploit the property of dimension reduction inherent in compressive sensing for hash design. The statistic structure and sparse of the wavelet coefficients assure efficient compression in situation of including maximum the image features. The hashing method is computationally secure without additional randomization process. Such a combined approach is capable of tackling all types of attacks and thus can yield a better overall performance in multimedia identification. To demonstrate the superior performance of the proposed schemes, receiver operating characteristics analysis over a large image database is performed. Experimental results show that the proposed image hashing is robust to a wide range of distortions and attacks. When compared with the current state-of-the-art methods, the proposed method yields better identification performances under geometric attacks such as rotation attacks and brightness changes.     

XML keyword search with promising result type recommendations

Keyword search enables inexperienced users to easily search XML database with no specific knowledge of complex structured query languages and XML data schemas. Existing work has addressed the problem of selecting data nodes that match keywords and connecting them in a meaningful way, e.g., SLCA and ELCA. However, it is time-consuming and unnecessary to serve all the connected subtrees to the users because in general the users are only interested in part of the relevant results. In this paper, we propose a new keyword search approach which basically utilizes the statistics of underlying XML data to decide the promising result types and then quickly retrieves the corresponding results with the help of selected promising result types. To guarantee the quality of the selected promising result types, we measure the correlations between result types and a keyword query by analyzing the distribution of relevant keywords and their structures within the XML data to be searched. In addition, relevant result types can be efficiently computed without keyword query evaluation and any schema information. To directly return top-k keyword search results that conform to the suggested promising result types, we design two new algorithms to adapt to the structural sensitivity of the keyword nodes over the keyword search results. Lastly, we implement all proposed approaches and present the relevant experimental results to show the effectiveness of our approach.     

The min-dist location selection and facility replacement queries

We propose and study a new type of location optimization problem, the min-dist location selection problem: given a set of clients and a set of existing facilities, we select a location from a given set of potential locations for establishing a new facility, so that the average distance between a client and her nearest facility is minimized. The problem has a wide range of applications in urban development simulation, massively multiplayer online games, and decision support systems. We also investigate a variant of the problem, where we consider replacing (instead of adding) a facility while achieving the same optimization goal. We call this variant the min-dist facility replacement problem. We explore two common approaches to location optimization problems and present methods based on those approaches for solving the min-dist location selection problem. However, those methods either need to maintain an extra index or fall short in efficiency. To address their drawbacks, we propose a novel method (named MND), which has very close performance to the fastest method but does not need an extra index. We then utilize the key idea behind MND to approach the min-dist facility replacement problem, which results in two algorithms names MSND and RID. We provide a detailed comparative cost analysis and conduct extensive experiments on the various algorithms. The results show that MND and RID outperform their competitors by orders of magnitude.     

基于多特征融合和SVM分类器的植物病虫害检测方法

针对农业领域植物病虫害检测问题,提出一种基于高清视频图像融合特征的支持向量机(SVM)的检测方法,实现农业生产中植物病虫害的快速检测。对每幅植物叶片图像的颜色、HSV、纹理和方向梯度直方图四种特征采用基于特征包的多特征融合方法,形成特征向量,并利用SVM分类器进行训练分类。对单特征与融合特征的SVM分类器性能进行试验比较,所提出的方法具有较高的准确率。     

新闻传播中动画语言的应用

随着数字时代的到来,数字技术不仅使动画在传统影视和游戏领域如虎添翼,其特有的仿真能力使得动画逐渐在电视新闻与网络新闻中也频繁运用,不仅为动画在新闻传播领域开辟了新的应用范围,也打通了各领域间的界限,一方面成为动画本身多元化的拓展,另一方面也为新闻传播方式的多样化提供了一种新的可能。文章旨在梳理动画在新闻传播中的历史沿革,研究数字时代下动画在新闻传播中的应用,并在此基础上思考动画在新闻传播中亟待解决的诸多问题。     

多台机器下的最小期望延误的随机排序问题

论文针对多台机器下,任务的预期时间为随机变量的排序问题,首先用LPT排序方法把任务安排到不同的机器上,然后用简单的随机方法来确定任务在机器上的特殊加工次序。由于随机预期时间是相互独立的并且服从指数分布,考虑将参数进行最大延误。