引入迁移学习的癫痫EEG信号自适应识别

在脑电图( EEG)信号识别中,EEG信号的采样环境、病人状态的多样性导致分类器训练所用的源域与分类器测试所用的目标域不匹配,分类器在目标域上表现不佳。为此,引入邻域适应策略,提出一种基于子空间相似度的改进主成分分析特征提取方法( SSM-PCA),在选择主成分时,考虑源域和目标域数据的几何和统计特性,并结合迁移学习分类器大间隔投射迁移支持向量机( LMPROJ),给出以SSM-PCA为基础的LMPROJ分类识别方法。实验结果表明,与结合PCA特征抽取技术和K近邻分类器实现的识别方法相比,该方法在识别正确率方面得到较大提升。     

BOD微生物传感器关键技术及其发展

生化需氧量(BOD)是表征水中有机污染物含量的重要指标,对水质监测和生化过程控制具有重要意义.总结了构成BOD检测系统的各环节,阐述了BOD微生物传感器中微生物选取、固定化以及换能器等关键技术,分析了不同方法的特点,讨论了目前BOD微生物传感器在研究中遇到的主要问题,并对其发展方向进行了展望.     

A3菌产絮凝剂培养动力学及靛蓝废水脱色研究

从土壤中筛选出1株产微生物絮凝剂的菌株A3,利用均匀设计安排试验,用曲线拟合创建数学模型的方法研究了其产絮凝剂的培养基条件和利用A3菌产絮凝剂对靛蓝废水进行脱色处理,获得A3菌最佳絮凝剂生产条件和最佳靛蓝废水脱色工艺.结果表明,A3菌产絮凝剂的最佳培养条件为葡萄糖添加量2.2%、酵母膏添加量0.51%、pH 7.6、温...     

Fair relay selection in decode-and-forward cooperation based on outage priority

The opportunistic cooperation schemes,where only the "best" relay is selected to forward the message,have been widely investigated recently for their good performance in terms of outage probability.However,the unfair selections of relays may cause unbalance power consumptions among relays,which reduces the lifetime of energy constrained networks.In this paper,we introduce a novel concept of outage priority based fairness(OPF),aiming at improving the selection fairness among relays appropriately without outage performance deterioration.Then,a cooperation scheme is proposed to meet this concept,and corresponding theoretical analysis is also provided.Afterward,based on OPF,the achievable upper bound of the fairness is derived,and an optimal cross-layer designed scheme is also provided to achieve the bound.Numerical simulations are carried out finally,which not only validate the theoretical analysis,but also show that taking advantages of the proposed schemes,the fairness among all relays,as well as the network lifetime,can be greatly improved without any loss of outage performance,especially in high SNR regime.     

优化的BP网络在抽油井故障诊断中的应用研究

抽油井故障诊断系统是油井系统产量的关键,为了更好更快地对当前油井系统进行诊断以保证石油的产量,人们利用各种各样的技术来完成这一目标。BP神经网络技术就是新兴的油井故障诊断手段之一,但是由于其容易陷于局部最优解、收敛速度慢以及泛化能力差等缺点,运用融入免疫算法浓度概念的遗传算法对BP神经网络进行优化,并将优化后的BP神经网络算法应用于抽油机现场的故障诊断过程中,结果显示优化后的BP算法有更高的诊断率,更快的运行速度,因而优化后的BP算法的寻找全局最优点的能力更强,收敛速度更快。     

基于网格相邻关系的离异点识别算法

离异点是偏离部分观察对象的数据点,根据离异点所在单元的密度与相邻单元的密度相比可能偏高或偏低的特点,本文提出了基于网格相邻关系的离异点识别算法GAO。该算法用单元间的相对密度和单元质心距离来衡量单元间的离异度,根据离异度确定离异单元和离异点。实验结果表明,该算法能有效地识别出多密度数据集的离异点,算法的效率优于Cell-based算法,且适合大数据集的离异点识别。     

一种改进的降尺寸视频转码算法

在Diversity &; Importance架构的基础上提出一种改进的空间降尺度视频转码算法,利用方差作为转码目标宏块的运动矢量测度因子,并通过自适应阈值的分类方法对不同视频序列选择合适的重编码模式。该算法比传统的运动矢量合成方法提高了约1dB的PSNR,在保持较高转码图像质量的同时有效地控制了编码长度,其转码后码流长度只相当于AMVR-DIM方法产生码流的40%~95%。     

一种求解Shubert函数优化问题的演化算法

综合国内外演化计算研究现状,基于热力学中的自由能极小化原理, 设计了一个全新的热力学演化算法,并通过对于Shubert函数优化问题求解的数值试验,测试了热力学演化算法的优良性能,实验结果表明了热力学演化算法求出的解比一般演化算法求出的解更加接近于全局最优。     

A hybrid clustering and graph based algorithm for tagSNP selection

TagSNP selection, which aims to select a small subset of informative single nucleotide polymorphisms (SNPs) to represent the whole large SNP set, has played an important role in current genomic research. Not only can this cut down the cost of genotyping by filtering a large number of redundant SNPs, but also it can accelerate the study of genome-wide disease association. In this paper, we propose a new hybrid method called CMDStagger that combines the ideas of the clustering and the graph algorithm, to find the minimum set of tagSNPs. The proposed algorithm uses the information of the linkage disequilibrium association and the haplotype diversity to reduce the information loss in tagSNP selection, and has no limit of block partition. The approach is tested on eight benchmark datasets from Hapmap and chromosome 5q31. Experimental results show that the algorithm in this paper can reduce the selection time and obtain less tagSNPs with high prediction accuracy. It indicates that this method has better performance than previous ones.     

公选课教学改革的研究和实践

公共选修课设置的目的是为了拓宽学生的知识面,培养学生的多种技能,从而提高学生的综合素质,以期适应社会发展的要求。本文就公共选修课在教学上存在的问题,以"网络实用技术"公共选修课为例,提出具体的改革措施,实践证明,该措施有效地提高公共选修课教学质量。