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％.     

Pricing and personal data collection strategies of online platforms in the face of privacy concerns

Electronic Commerce Research - We consider a platform providing free content for users and earning profit from the sale of advertising. The platform can collect and analyze personal data to...     

Revealing cracking and breakage behaviours of gibbsite particles

Mitigating gibbsite particle cracking and breakage during industrial alumina production can increase the quality of smelter grade alumina product by reducing the ultrafine particle content. Therefore, it is essential to investigate the particle cracking during static calcination and the breakage of calcined gibbsite particles under external force. In this work, we investigated the impact of the calcination ramping rate and the crystallite size on gibbsite particle cracking during static calcination. A slow ramping rate and a large pristine crystallite size tend to increase particle cracking. Apart from the study of particle cracking behaviour, we also investigated the breakage of calcined gibbsite particle under external force. Cracks on the particle surface can initiate breakage within the crystallite and along the grain boundary under external force. The breakage within crystallite occurs as the cleavage of the crystallite, while the breakage along the grain boundary leads to the shedding of a whole crystallite. We further explored the factors influencing the strength of calcined gibbsite particles. With increasing calcination temperature, the strength of particle increases when gibbsite converts to boehmite, and then decreases when boehmite converts into amorphous alumina. Particles containing smaller crystallites and calcined with fast ramping rates exhibit higher resistance to breakage.     

关于材料化学专业英语教学的几点思考

材料化学专业英语是材料化学专业最重要的专业课程之一，专业英语的学习可为学生的专业论文写作和国际交流奠定坚实的基础。该研究对当前材料化学专业英语教学中存在的一些问题进行了分析，并从教学内容、教学方法、教师素质等方面就如何提高材料化学专业英语的教学效果进行了探讨，以期对改善教学质量和提高学生学习兴趣等方面有所促进。     

区域导航对流层延迟误差修正模型研究

本文研究了电波大气折射理论，分析了传播误差因素，阐述了区域导航信号的传播路径与 GNSS 卫星导航的不同，论述了对流层延迟对区域导航信号测量精度的影响，设计了满足区域导航系统应用需求的对流层延迟误差修正模型，并通过仿真研究，验证了所设计区域导航对流层延迟误差修正模型的可行性，并给出了该模型在远距离低仰角和近距离高仰角下的误差修正能力。     

Room Temperature Ferromagnetism in Co-doped CuAlO2 Nanofibers Fabricated by Electrospinning

One-dimensional, diluted magnetic semiconductor nanofibers have attracted increasing attention for their unique magnetic properties, large specific surface area, and high porosity. These qualities lead to excellent performance in magneto-optical devices, magnetic resonance imaging, ferrofluids and magnetic separation. The purpose of this study is to fabricate P-type one dimensional CuAlO2-based diluted magnetic semiconductor nanofibers. First, we fabricated Cu Al0.95Co0.05O2 nanofibers with an average diameter of 1 μm with the electrospinning method. The annealed nanofibers were thermally treated at a temperature of 1 100 ℃ and then shrunk to a diameter of about 650 nm. We used X-ray diffraction measurements and Raman spectra to confirm that the Cu Al0.95Co0.05O2 nanofibers had a single impurity free delafossite phase. The X-ray photoelectron spectroscopy analysis indicates that Co was present in the +2 oxidation state, resulting in an room temperature ferromagnetism in the Cu Al0.95Co0.05O2 fiber. This contrasts with nonmagnetism in pristine CuAlO2 fiber. The coercivity(Hc) value of 65.26 Oe and approximate saturation magnetization(Ms) of 0.012 emu/g demonstrate good evidence of ferromagnetism at room temperature for Cu Al0.95Co0.05O2 nanofibers.     

Polyethylene oxide-polypropylene oxide -polyethylene oxide derived porous carbon materials with different molecular weights as ORR catalyst in alkaline electrolytes

Polyethylene oxide (PEO)-polypropylene oxide (PPO)-polyethylene oxide block copolymer having different molecular weights are used as precursors of carbon materials to prepare Hollow -Derivatives carbon material as an electrocatalyst through block copolymer self-assembly. The composition and microstructure of the prepared catalysts are shown by Raman spectroscopy, X-ray diffraction (XRD), Test of nitrogen adsorption and desorption curves, High resolution transmission electron microscopy (HR-TEM) and scanning electron microscopy (HR-SEM). Oxygen was passed into alkaline electrolyte solution until the solution reached saturation state. With molecular weight increasing, the obtained sample gradually changed from block to hollow and spherical. When the molecular weight was 12600 g mol^?1, the evenly hollow carbon nanocages was acquired (C-12600). In O₂ saturated alkaline electrolyte (0.1 M KOH solution), C-12600's limited current density，half-wave potential and initial potential are 5.23 mA cm^?2@0.4 V, 0.72 V and 0.81 V, respectively. And most important is that half-wave potential and onset potential have barely change after 2000 cycles of cyclic voltammetry. As a result, the porous carbon materials exhibited excellent electrocatalytic activity while maintaining high stability in alkaline KOH solution.     

基于随机光栅的可调谐随机光纤激光器

提出一种基于随机光栅与高反射布拉格光栅(FBG)相结合的可调谐随机光纤激光器。利用980nm泵浦光源泵浦一段7m长的掺铒光纤(EDF)进行增益放大,由随机光栅提供随机反馈。随机光栅长7cm,具有约10000个折射率修改点,这些点由飞秒激光逐点写入,并沿光纤方向随机分布,两点相邻间隔小于10μm。同时,利用中心波长为1548nm的高反射FBG来组成半开放腔结构,实现了随机激光的输出。实验测得的泵浦阈值功率仅为18mW,斜率效率高达13.2%,并通过改变FBG的中心波长,实现了输出激光波长的可调谐,调谐范围为4.45nm(1548.04~1552.49nm)。得益于半开放式激光腔的设计和EDF的高增益,整个系统具有阈值低、效率高、结构简单等优点。