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％.     

基于禁忌搜索的晶体位置谱分割与校准方法

为满足不同规格晶体探测器对分割校准晶体条响应事件位置数据的需求，开发了一种以禁忌搜索算法为核心，结合UDP数据帧、二维高斯模型及光导折射率的位置信息分割校准方法。实验结果表明，本方法在溢出率为5%时，峰谷比可达1218，空间分辨率达17 mm，晶体条响应位置识别准确度高达99%，滤除了引发伪峰的噪声，避免了过分割问题。在面对多种规格晶体阵列的位置谱时，本方法能依照阵列规格将晶体条区域的响应自动校准编号并输出晶体位置查找表，实现响应事件的精确校准。     

基于NTP的网络时间服务器校准方法探讨

为了解决基于NTP的网络时间服务器校准问题,对其展开校准项目和校准方法的探讨,给出了NTP同步偏差、定时准确度和定时稳定度等校准项目并结合实验详细阐述了两种NTP同步偏差的校准方法,实验结果表明,采用直接测量法的NTP同步偏差为10.25μs,不确定度为62.08μs(k=2);采用比较法的NTP同步偏差为139.75μs,不确定度为6.36ms(k=2).     

The effect of alkali metal oxide on the properties of borosilicate fireproof glass: Structure,thermal properties,viscosity, chemical stability

The purpose of the current work was to research the effect of alkali metal oxide on the structure, thermal properties, viscosity and chemical stability in the glass system (R₂O–CaO–B₂O₃–SiO₂) systematically. Because the glass would emulsify when Li₂O was added to the glass batch, this article did not discuss Li₂O. The results showed that when the amount of Na₂O was less than 4 mol.%, there was a higher interconnectivity of borate and silicate sub-networks in glass, as more mixed Si–O–B bonds were present in glass. The glass samples exhibited excellent thermal properties and chemical stabilities. As the amount of Na₂O exceeded 4 mol.%, the interconnectivity of borate and silicate sub-networks was weakened. The thermal properties and chemical stabilities of the glass samples were reduced. The connectivity of the silicate sub-network was weakened slightly as the Na/K ratio varied, and the coefficient of thermal expansion (CTE) of the glass samples gradually increased, and the resistance to thermal shock (RTS) value gradually decreased. Moreover, the viscosity of the glass samples decreased with the ratio of Na/Si and Na/K increased.     

Enhanced electrochemical performance of LiNi0.8Co0.1Mn0.1O2 via titanium and boron co-doping

Titanium and boron are simultaneously introduced into LiNi_0.8Co_0.1Mn_0.1O₂ to improve the structural stability and electrochemical performance of the material. X-ray diffraction studies reveal that Ti⁴⁺ ion replaces Li⁺ ion and reduces the cation mixing; B³⁺ ion enters the tetrahedron of the transition metal layers and enlarges the distance of the [LiO₆] layers. The co-doped sample has spherical secondary particles with elongated and enlarged primary particles, in which Ti and B elements distribute uniformly. Electrochemical studies reveal the co-doped sample has improved rate performance (183.1 mAh·g^-1 at 1 C and 155.5 mAh·g^-1 at 10 C) and cycle stability (capacity retention of 94.7% after 100 cycles at 1 C). EIS and CV disclose that Ti and B co-doping reduces charge transfer impedance and suppresses phase change of LiNi_0.8Co_0.1Mn_0.1O_2.     

一种大量元素水溶肥料的制备及其在玉米上的喷施效果

根据玉米需肥特性设计氮磷钾比例,制备了含中微量元素的大量元素水溶肥料,产品氮、磷、钾比例为2∶1∶4,属于高钾中氮低磷型.在河北省安平县前子文村和浙江省新昌县孟家塘村玉米上开展了叶面喷施试验.结果表明:玉米生物学性能得到改善,玉米产量、出籽率、百粒重与容重得到提高;与空白对照相比,平均增产率为5.45％,平均纯增收896.40元/公顷,平均产投比为5.43∶1.     

负极添加NMP对电池性能的影响

锂离子电池负极浆料中添加N-甲基吡咯烷酮(NMP),在极片加热干燥时不能完全除去.残留的NMP吸附在石墨表面,使得SEI膜与石墨结合不牢固.研究了其对电池性能的影响,结果显示,在电池的循环过程中,SEI膜逐渐脱落,导致电池循环寿命缩短,但对电池的容量、内阻、倍率、存储等初期性能不影响.     

基于熵权TOPSIS的工程咨询机构BIM技术应用能力评价

构建工程咨询机构BIM技术应用能力评价的指标体系,提出改进的熵权TOPSIS评价模型,以4个典型的工程咨询单位为例,进行BIM技术运用能力评价。研究表明,BIM行业的整体水平已经有了明显的提升,但是区域间的发展还存在一定差距。