基于1D CNN与XGBoost的恶意代码纹理检测

恶意代码数量已经呈现爆炸式增长,对于恶意代码的检测防护显得尤为重要.近几年,基于深度学习的恶意代码检测方法开始出现,基于此,提出一种新的检测方法,将恶意代码二进制文件转化为十进制数组,并利用一维卷积神经网络(1 Dimention Convolutional Neural Networks,1D CNN)对数组进行分类和识别.针对代码家族之间数量不平衡的现象,该算法选择在分类预测上表现良好的XGBoost,并对Vision Research Lab中的25个不同恶意软件家族的9458个恶意软件样本进行了实验.实验结果表明,所提的方法分类预测精度达到了97％.     

“电工学”国家级一流课程建设与实践

根据新时代新工科人才需求特点和电工学课程特点,分析非电专业学生的电类实践需求,提出构建电工学课程为核心的电工电子实践创新能力培养新体系。通过优化教学内容、开展教学模式和考核模式改革、构建教学资源体系和进行教师队伍建设,使我校电工学课程教学质量提升、学生工程实践和创新能力提高、学生满意度增加、一流课程建设成效显著。     

土壤中有机污染物的检测技术研究进展

土壤污染防治法的实施促进了国内土壤监测业务的发展.对比分析了目前土壤中有机污染物的采样、前处理技术.挥发性有机污染物(VOCs)对采样环节的要求较高,需使用采样器和保存剂来减少挥发损失,进样前提取过程宜选用吹扫捕集等具有封闭系统的高效自动化方式.半挥发性有机污染物(SVOCs)的回收率主要受萃取、净化方式的影响,二氯甲烷和加速溶剂萃取的组合方式既快速又节约溶剂;净化材料宜选择弗罗里硅土、氧化铝类物质.选择合适的采样、前处理方法才能保证回收率、质量控制的要求.     

蛋类礼盒包装结构的缓冲性能研究

目的研究蛋类礼盒包装结构的缓冲性能。方法以蛋类尺寸为基础,建立可发性聚乙烯(expandable polyethylene. EPE)缓冲单元结构和组合结构,进行静态仿真分析和实验验证,比较结构在形状、叠合层数、组合形式等参数变化时的载荷与位移。结果结构层数变化相同时,单元结构的极限载荷从143N增加到236 N,组合结构的极限载荷从224 N增加到476 N,均呈近线性增长。结论蛋类礼盒包装中,组合结构的承载能力优于单元结构,通过单元结构的组合,可满足不同蛋类的包装要求。     

Reconstructing gene regulatory networks with a memetic-neural hybrid based on fuzzy cognitive maps

Reconstructing gene regulatory networks (GRNs) plays an important role in identifying the complicated regulatory relationships, uncovering regulatory patterns in cells, and gaining a systematic view for biological processes. In order to reconstruct large-scale GRNs accurately, in this paper, we first use fuzzy cognitive maps (FCMs), which are a kind of cognition fuzzy influence graphs based on fuzzy logic and neural networks, to model GRNs. Then, a novel hybrid method is proposed to reconstruct GRNs from time series expression profiles using memetic algorithm (MA) combined with neural network (NN), which is labeled as MANN_FCM-GRN. In MANN_FCM-GRN, the MA is used to determine regulatory connections in GRNs and the NN is used to determine the interaction strength of the regulatory connections. In the experiments, the performance of MANN_FCM-GRN is validated on both synthetic data and the benchmark dataset DREAM3 and DREAM4. The experimental results demonstrate the efficacy of MANN_FCM-GRN and show that MANN_FCM-GRN can reconstruct GRNs with high accuracy without expert knowledge. The comparison with existing algorithms also shows that MANN_FCM-GRN outperforms ant colony optimization, non-linear Hebbian learning, and real-coded genetic algorithms.

     

无线电综合测试仪校准装置的研究及其不确定度分析

This calibration device of radio comprehensive tester is studied and established in this paper. It solves the verification and calibration of a large number of general-purpose radio comprehensive testers. The calibration device consists of four calibration sub- systems and calibration software system, including RF generator, audio generator, audio analyzer and RF analyzer. It also researches on the configuration of standard equipment and analyzes the uncertainty of the calibration devices, ensuring accurate and reliable val- ue transfer.     

烟道流量计量标准装置

为了解决我国烟道流量计的量值溯源问题,中国计量科学研究院建立了烟道流量计量标准装置。装置使用可溯源至标准转盘的激光多普勒测速仪作为原级标准器,采用激光多普勒流速剖面扫描和超声流量计波动修正的方式测量标准流量,经校准的8声道超声流量计为工作级标准表,具备了908~104840m3/h的测量能力,扩展不确定度为0.62%(k=2),可对最大口径为1m的流量计进行校准。装置下游测试段包括圆形管段和矩形管段,能够开展烟道流量计测量性能的研究。