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Studies on the roles of vanadyl sulfate and sodium nitrite in catalytic oxidation of benzyl alcohol with molecular oxygen

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Science China Chemistry 2015年第1期58卷 114-122页

作者： Zhongtian Du Junxia Liu tianliang lu Yangyang Ma Jie Xu State Key Laboratory of Catalysis Dalian Institute of Chemical Physics Chinese Academy of SciencesDalian National Laboratory for Clean Energy University of Chinese Academy of Sciences

An efficient catalytic system consisting of vanadyl sulfate/sodium nitrite was disclosed previously for the oxidation of benzylic alcohols into aldehydes with molecular ***,the roles of catalyst components were not *** this paper,we examined catalytic oxidation of benzyl alcohol as a model reaction,especially by infrared *** role of each component is discussed including nitrite,vanadyl,sulphate,and *** nitrite could be converted into nitrate and nitric *** vanadium(IV)could be smoothly oxidized into vanadium(V)under mild and acidic conditions without any organic *** transformation of sulfate and bisulfate,the cessation of an induction period,and the oxidation of benzyl alcohol were closely *** multiple roles of water are discussed,including reduction of the induction period,participation in redox cycles of nitric compounds,deactivation of vanadium,and as a byproduct of *** study contributes to further development of aerobic oxidation using vanadium based catalysts.

关键词： catalytic oxidation alcohol infrared spectroscopy nitrite vanadium

Multi-Branch Deepfake Detection Algorithm Based on Fine-Grained Features

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Computers, Materials & Continua 2023年第10期77卷 467-490页

作者： Wenkai Qin tianliang lu lu Zhang Shufan Peng Da Wan School of Information Network Security People’s Public Security University of ChinaBeijing100038China Department of Investigation Shandong Police CollegeJinan250200China

With the rapid development of deepfake technology,the authenticity of various types of fake synthetic content is increasing rapidly,which brings potential security threats to people’s daily life and social ***,most algorithms define deepfake detection as a binary classification problem,i.e.,global features are first extracted using a backbone network and then fed into a binary classifier to discriminate true or ***,the differences between real and fake samples are often subtle and local,and such global feature-based detection algorithms are not optimal in efficiency and *** this end,to enhance the extraction of forgery details in deep forgery samples,we propose a multi-branch deepfake detection algorithm based on fine-grained features from the perspective of fine-grained ***,to address the critical problem in locating discriminative feature regions in fine-grained classification tasks,we investigate a method for locating multiple different discriminative regions and design a lightweight feature localization module to obtain crucial feature representations by augmenting the most significant parts of the feature ***,using information complementation,we introduce a correlation-guided fusion module to enhance the discriminative feature information of different ***,we use the global attention module in the multi-branch model to improve the cross-dimensional interaction of spatial domain and channel domain information and increase the weights of crucial feature regions and feature *** conduct sufficient ablation experiments and comparative *** experimental results show that the algorithm outperforms the detection accuracy and effectiveness on the FaceForensics++and Celeb-DF-v2 datasets compared with the representative detection algorithms in recent years,which can achieve better detection results.

关键词： Deepfake detection fine-grained classification multi-branch global attention

Mining Fine-Grain Face Forgery Cues with Fusion Modality

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Computers, Materials & Continua 2023年第5期75卷 4025-4045页

作者： Shufan Peng Manchun Cai tianliang lu Xiaowen Liu People’s Public Security University of China Beijing 100038China

Face forgery detection is drawing ever-increasing attention in the academic community owing to security *** the considerable progress in existing methods,we note that:Previous works overlooked finegrain forgery cues with high *** cues positively impact the model’s accuracy and ***,single-modality often causes overfitting of the model,and Red-Green-Blue(RGB)modal-only is not conducive to extracting the more detailed forgery *** propose a novel framework for fine-grain forgery cues mining with fusion modality to cope with these ***,we propose two functional modules to reveal and locate the deeper forged *** method locates deeper forgery cues through a dual-modality progressive fusion module and a noise adaptive enhancement module,which can excavate the association between dualmodal space and channels and enhance the learning of subtle noise features.A sensitive patch branch is introduced on this foundation to enhance the mining of subtle forgery traces under fusion *** experimental results demonstrate that our proposed framework can desirably explore the differences between authentic and forged images with supervised *** evaluations of several mainstream datasets show that our method outperforms the state-of-the-art detection methods with remarkable detection ability and generalizability.

关键词： Face forgery detection fine-grain forgery cues fusion modality adaptive enhancement

Smartphone Malware Detection Model Based on Artificial Immune System

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China Communications 2014年第A1期11卷 86-92页

作者： WU Bin lu tianliang ZHENG Kangfeng ZHANG Dongmei LIN Xing InformationSecurityLaboratory NationalDisasterRecoveryTechnologyEngineeringLaboratoryBeijingUniversityofPostsandTelecommunicationsBeijing100876P.R.China People'sPublicSecurityUniversityofChina Beijing100038P.R.China

In order to solve the problem that me traditional signature-based detection technology cannot effectively detect unknown malware, we propose in this study a smartphone malware detection model （SP-MDM） based on artificial immune system, in which static malware analysis and dynamic malware analysis techniques are combined, and antigens are generated by encoding the characteristics extracted from the malware. Based on negative selection algorithm, the mature detectors are generated. By introducing clonal selection algorithm, the detectors with higher affinity are selected to undergo a proliferation and somatic hyper-mutation process, so that more excellent detector offspring can be generated. Experimental result shows that the detection model has a higher detection rate for unknown smartphone malware, and better detection performance can be achieved by increasing the clone generation.

关键词： artificial immune system smartphonemalware detection negative selection clonalselection

Hydrolysis of cellobiose catalyzed by zeolites—the role of acidity and micropore structure

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Journal of Energy Chemistry 2016年第1期25卷 141-145页

作者： Lipeng Zhou Zhen Liu Yuqi Bai tianliang lu Xiaomei Yang Jie Xu College of Chemistry and Molecular Engineering Zhengzhou University School of Chemical Engineering and Energy Zhengzhou University State Key Laboratory of Catalysis Dalian National Laboratory for Clean Energy Dalian Institute of Chemical Physics Chinese Academy of Sciences

The roles of acidity and micropore structure of zeolite were studied in the hydrolysis of the model oligosaccharide of cellulose–cellobiose. HZSM-5, HY, HMOR and Hβ zeolites were selected as model catalysts for the hydrolysis of cellobiose. The effect of acidity of zeolite, including the strength, type and location, on its catalytic activity was investigated. The strong Br？nsted acid sites located in micropores are the active sites for the hydrolysis of cellobiose to glucose. Meanwhile, the catalytic performance of zeolite is also dependent on the micropore size of zeolite.

关键词： Zeolites Biomass Cellulose Hydrolysis Acidity

Synthesis of Mesoporous Anatase TiO2 Sphere with High Surface Area and Enhanced Photocatalytic Activity

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Journal of Materials Science & Technology 2017年第3期33卷 300-304页

作者： tianliang lu Youqiang Wang Yingli Wang Lipeng Zhou Xiaomei Yang Yunlai Su School of Chemical Engineering and Energy Zhengzhou University Zhengzhou 450001 China College of Chemistry and Molecular Engineering Zhengzhou University Zhengzhou 450001 China

Mesoporous anatase TiO2 spheres with high surface area（119 m^2g^（-1）） were successfully synthesized via a facile and green template-free method. The prepared TiO2 was characterized by X-ray diffraction（XRD）,N2 adsorption, scanning electron microscopy（SEM）, transmission electron microscopy（TEM） and UV–vis absorbance spectra. It was found that the prepared TiO2 is characterized by pure anatase phase, which shows uniform spheres and has a typical mesostructure with a high specific surface area and a large pore volume. The effects of complexant（acetylacetone） amount, crystallization temperature and calcination temperature were also investigated. Based on the results, a sketch for the preparation of mesoporous TiO2 was proposed. First, complex formed between tetrabutyl titanate and acetylacetone in ethanol. After introduction of aqueous of ammonia sulfate and urea, hydrolysis of tetrabutyl titanate would occur slowly,and sol of TiO2 was formed. Then, crystallization proceeded under hydrothermal conditions. Calcination process favored the formation of bigger TiO2 crystal through combining of the small crystals in *** led to the formation of bigger mesopores between TiO2 crystals. Photocatalytic activity of the prepared TiO2 was evaluated by decomposition of methyl orange.

关键词： TiO2 Mesoporous Template-free method Photocatalysis

Highly efficient isomerization of glucose to fructose over Sn-doped silica nanotube

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Resources Chemicals and Materials 2024年第2期3卷 159-165页

作者： Yajiao Cui Zhi Yang Xiongtao Hu Shufei Yang Armin Rezayan tianliang lu Zhiyong Chen Yongsheng Zhang School of Chemical Engineering Zhengzhou UniversityZhengzhou 450001China School of Mechanical and Power Engineering Zhengzhou UniversityZhengzhou 450001China Henan Key Laboratory of Green Manufacturing of Biobased Chemicals Hongye Biological Technology Co.Ltd.Puyang457000China

Isomerization of glucose to fructose is a fundamental and key intermediate process commonly included in the production of valuable chemicals from carbohydrates in *** of fructose yield is a *** this work,Sn-doped silica nanotube(Sn-SNT)was developed as a highly efficient Lewis acid catalyst for the selective isomerization of glucose to *** Sn-SNT,69.1%fructose yield with 78.5%selectivity was obtained after reaction at 110◦C for 6 *** sole presence of a large amount of Lewis acid sites in Sn-SNT without Brønsted acid site is one of the reasons for the high fructose yield and ***,high density of Si􀀀OH groups in Sn-SNT can ensure the presence of Si􀀀OH groups near the Sn sites,which is important for the isomerization of glucose to fructose,leading to the high fructose yield and ***,the Sn-SNT is recyclable.

关键词： Glucose Fructose Lewis acid Isomerization

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人脸视频深度伪造检测方法综述

计算机科学与探索 2023年第1期17卷 1-26页

作者：张璐芦天亮杜彦辉中国人民公安大学信息网络安全学院北京100038 山东警察学院侦查系济南250200

深度伪造(deepfake)技术的非法应用会对社会稳定、个人名誉甚至国家安全造成恶劣影响,因此针对人脸视频的深度伪造检测成为计算机视觉领域中的难点与研究热点。目前该领域的研究建立在传统人脸识别与图像分类技术基础上,通过搭建深度学... 详细信息

深度伪造(deepfake)技术的非法应用会对社会稳定、个人名誉甚至国家安全造成恶劣影响,因此针对人脸视频的深度伪造检测成为计算机视觉领域中的难点与研究热点。目前该领域的研究建立在传统人脸识别与图像分类技术基础上,通过搭建深度学习网络判别真伪,但存在数据集质量不一、多模态特征如何有效结合、模型泛化能力较差等问题。为进一步促进深度伪造检测技术的发展,对当前各类人脸视频深度伪造算法进行了全面总结,并对已有算法进行了归类、分析、比较。首先,主要介绍人脸视频深度伪造检测数据集;其次,对近三年主要的伪造视频检测方法进行总结,以特征选择为切入点,从空间特征、时空融合特征、生物特征的角度对各项检测技术进行分类整理,并对基于水印与区块链等非主流检测方法进行介绍;然后,从特征选择、迁移学习、模型设计与训练思路等方面介绍了各类检测方法所呈现出的主流趋势;最后,对全文进行总结并对未来技术发展进行展望。

关键词：深度学习多媒体取证深度伪造视频检测人脸篡改

GRU和Involution改进的深度伪造视频检测方法

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计算机工程与应用 2023年第22期59卷 276-283页

作者：刘亚琳芦天亮中国人民公安大学信息网络安全学院北京 100038

近年来深度伪造视频在网络上广泛传播,造成了负面影响。针对现有检测模型准确率低和信息提取不够充分和全面的问题,提出了一种GRU(gated recurrent unit)和Involution改进的深度伪造视频检测方法。首先使用VGG19作为主干网络提取空间特... 详细信息

近年来深度伪造视频在网络上广泛传播,造成了负面影响。针对现有检测模型准确率低和信息提取不够充分和全面的问题,提出了一种GRU(gated recurrent unit)和Involution改进的深度伪造视频检测方法。首先使用VGG19作为主干网络提取空间特征,并将Involution算子嵌入主干网络,从空间和通道信息两方面加强了人脸图像的空间建模能力。然后通过主胶囊层关注特征的位置信息和使用GRU提取帧间的时序特征。最后在训练模型阶段使用focalloss作为损失函数来平衡样本。在Deepfakes、FaceSwap和Celeb-DF数据集中进行测试,实验结果表明该方法优于主流检测方法,改进对比实验进一步证明了检测方法的有效性。

关键词：深度伪造门控循环单元(GRU) Involution 胶囊网络 focalloss