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Multiscale stochastic hierarchical image segmentation by spectral clustering

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Science in China(Series F) 2007年第2期50卷 198-211页

作者： LI XiaoBin tian zheng Department of Applied Mathematics Northwestern Polytechnical University Xi'an 710072 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Science Beijing 100080 China

This paper proposes a sampling based hierarchical approach for solving the computational demands of the spectral clustering methods when applied to the problem of image segmentation. The authors first define the distance between a pixel and a cluster, and then derive a new theorem to estimate the number of samples needed for clustering. Finally, by introducing a scale parameter into the similarity function, a novel spectral clustering based image segmentation method has been developed. An important characteristic of the approach is that in the course of image segmentation one needs not only to tune the scale parameter to merge the small size clusters or split the large size clusters but also take samples from the data set at the different scales. The multiscale and stochastic nature makes it feasible to apply the method to very large grouping problem. In addition, it also makes the segmentation compute in time that is linear in the size of the image. The experimental results on various synthetic and real world images show the effectiveness of the approach.

关键词： spectral clustering graph multiscale random tree image segmentation

Photo-induced grease/oil switched lubricant for friction regulation

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Friction 2024年第8期12卷 1696-1706页

作者： zheng ZHANG Shuangxi TANG Liran MA Yu tian State Key Laboratory of Tribology in Advanced Equipment Department of Mechanical EngineeringTsinghua UniversityBeijing 100084China

Controllable friction regulation has drawn much interest in both scientific and industrial *** there have been many researches on friction regulation by many physical fields and chemical ***-sensitive materials are promising because it is relatively easy to change their properties compared with ***,a new kind of photo-induced grease/oil switched lubricant is designed and shows great reversibility under ultraviolet(UV)and visible(Vis)*** viscosity can change more than 50 times under different irradiation,and the coefficients of friction(COFs)obviously increase under Vis irradiation and decrease under UV irradiation,which performs better than those of the common *** to the experimental results,the phenomena are contributed to the break and reconstruction of the three-dimensional network inside the *** a switchable grease/oil state under different irradiation,this work provides a new principle for designing a smart lubricant with controllable friction regulation.

关键词： photo-induced spiropyran switched lubricant friction regulation

Plausible Heterogeneous Graph k-Anonymization for Social Networks

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Tsinghua Science and Technology 2022年第6期27卷 912-924页

作者： Kaiyang Li Ling tian Xu zheng Bei Hui School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu 610054China Trusted Cloud Computing and Big Data Key Laboratory of Sichuan Province Chengdu 610000China

The inefficient utilization of ubiquitous graph data with combinatorial structures necessitates graph embedding methods,aiming at learning a continuous vector space for the graph which is amenable to be adopted in traditional machine learning algorithms in favor of vector *** embedding methods build an important bridge between social network analysis and data analytics as social networks naturally generate an unprecedented volume of graph data *** social network data not only bring benefit for public health,disaster response,commercial promotion,and many other applications,but also give birth to threats that jeopardize each individual’s privacy and ***,most existing works in publishing social graph embedding data only focus on preserving social graph structure with less attention paid to the privacy issues inherited from social *** be specific,attackers can infer the presence of a sensitive relationship between two individuals by training a predictive model with the exposed social network *** this paper,we propose a novel link-privacy preserved graph embedding framework using adversarial learning,which can reduce adversary’s prediction accuracy on sensitive links while persevering sufficient non-sensitive information such as graph topology and node attributes in graph *** experiments are conducted to evaluate the proposed framework using ground truth social network datasets.

关键词： social network graph embedding privacy preservation adversarial learning

Analyzing topics in social media for improving digital twinning based product development

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Digital Communications and Networks 2024年第2期10卷 273-281页

作者： wenyi Tang Ling tian Xu zheng Ke Yan School of Computer Science and Engineering University of Electronic Science and Technology of ChinaChengdu611731China

Digital twinning enables manufacturers to create digital representations of physical entities,thus implementing virtual simulations for product *** efforts of digital twinning neglect the decisive consumer feedback in product development stages,failing to cover the gap between physical and digital *** work mines real-world consumer feedbacks through social media topics,which is significant to product *** specifically analyze the prevalent time of a product topic,giving an insight into both consumer attention and the widely-discussed time of a *** primary body of current studies regards the prevalent time prediction as an accompanying task or assumes the existence of a preset ***,these proposed solutions are either biased in focused objectives and underlying patterns or weak in the capability of generalization towards diverse *** this end,this work combines deep learning and survival analysis to predict the prevalent time of *** propose a specialized deep survival model which consists of two *** first module enriches input covariates by incorporating latent features of the time-varying text,and the second module fully captures the temporal pattern of a rumor by a recurrent network ***,a specific loss function different from regular survival models is proposed to achieve a more reasonable *** experiments on real-world datasets demonstrate that our model significantly outperforms the state-of-the-art methods.

关键词： Digital twinning Product development Topic analysis Social media

Construction of Two Coordination Polymers Based on Two New 5-Substitued Tetrazole-based Ligands: Structures and Luminescent Properties

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Chinese Journal of Structural Chemistry 2019年第2期38卷 308-316,169页

作者： LI tian-tian zheng Sheng-Run Guiyang College of Traditional Chinese Medicine Institute of Special Materials & School of Chemistry and Environment South China Normal University

Two new coordination polymers(CPs) based on two new tetrazole-based ligands, namely, [Cu(TPP)]n(HTTP = 4-(3-(2 H-tetrazol-5-yl)phenyl)pyridine, 1) and {[Cd_2(TBCA)_2(H_2O)_2]·-H_2O}n(H_2TBCA = 3?-(2 H-tetrazol-5-yl)biphenyl-4-carboxylic acid, 2), were synthesized via solvothermal reactions. Single-crystal X-ray diffraction analysis reveals that compound 1 exhibits a(3,6)-connected rtl network topology based on binuclear secondary building units(SBUs). Compound 2 presents a 2D framework composed of 1D SUBs formed by both carboxyl and tetrazole groups. The 2D network is linked into a 3D framework via various hydrogen bonds. They represent two examples of CPs construct from rigid 5-substitued tetrazole-based ligands with relatively longer spacer. The thermal stabilities and luminescent properties of compounds 1 and 2 were also explored.

关键词： tetrazole-based ligand coordination polymer crystal structure solid-state luminescence

Traffic Sign Recognition Using an Attentive Context Region-Based Detection Framework

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Chinese Journal of Electronics 2021年第6期30卷 1080-1086页

作者： LIU Zhigang DU Juan tian Feng wen Jiazheng School of Computer and Information Technology Northeast Petroleum University Postdoctoral Workstation on Applied Technology Research Institute Northeast Petroleum University Department of Computer Science for Artificial Intelligence University of Nottingham Ningbo

Accurate small traffic sign recognition is more important for the safety of intelligent transportation systems. A recognition framework named attentive context region-based detection framework(AC-RDF) is proposed in this paper. We construct the attentive context feature for the recognition of small traffic signs,which combines the target information and the contextual information by the concatenation operation following a pointwise convolutional layer. The proposed attentive context feature exploits the surrounding information for a given object proposal. Next, we propose a novel attentive loss function to replace the original crossentropy function. It distinguishes hard negative samples from easy positive ones in the total loss, allows the proposed framework to obtain enough training, and further improve the recognition accuracy. The proposed method is evaluated on the challenging Tsinghua-Tencent 100 K dataset. The experimental results indicate that the attentive context region-based detection framework is superior at detecting small traffic signs and achieves stateof-the-art performance compared with other methods.

关键词： attentive context region-based detection framework intelligent transportation systems convolutional neural nets attentive context feature AC-RDF framework attentive loss function traffic signs learning (artificial intelligence) Tsinghua-Tencent 100K dataset object recognition feature extraction traffic sign recognition object detection entropy recognition framework

Special topic on strategies for developing energy-related physical chemistry

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Science China Chemistry 2017年第11期60卷 1377-1378页

作者： Zhong-Qun tian Nanfeng zheng Collaborative Innovation Center of Chemistry for Energy Materials State Key Laboratory for Physical Chemistry of Solid Surfacesand Department of ChemistryCollege of Chemistry and Chemical EngineeringXiamen UniversityXiamen 361005China

Increasing global energy demand and environment issue have pushed us to develop technologies for efficient utiliza- tion of fossil fuels and also seek for renewable energy re- sources. Chemistry plays a crucial role in the acquisition, generation, distribution, and utilization of energy in differ- ent forms although it is not the only contributing subject. Currently, fossil fuels are the primary source to provide the majority of the world＇s energy. While the efficient utiliza- tion of fossil fuels requires deep understanding of the ener- gy transformation processes associated with the breaking and reorganization of chemical bonds, the use of many re- newable energy resources often involves chemical trans- formations with electron transfer. For these reasons, energy chemistry has been recently emerging as a new interdisci- plinary area to address chemistry issues associated with energy technologies.

关键词：可再生能源化学战专题物理化石燃料高效利用重组技术环境问题

A Multi Moving Target Recognition Algorithm Based on Remote Sensing Video

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 585-597页

作者： Huanhuan zheng Yuxiu Bai Yurun tian School of Information Engineering Yulin UniversityYulinChina ZTE Communication Co. Ltd.Xi’anChina

The Earth observation remote sensing images can display ground activities and status intuitively,which plays an important role in civil and military ***,the information obtained from the research only from the perspective of images is limited,so in this paper we conduct research from the perspective of *** present,the main problems faced when using a computer to identify remote sensing images are:They are difficult to build a fixed regular model of the target due to their weak moving ***,the number of pixels occupied by the target is not enough for accurate ***,the number of moving targets is large at the same *** this case,the main targets cannot be recognized *** paper studies from the perspective of Gestalt vision,transforms the problem ofmoving target detection into the problem of salient region probability,and forms a Saliency map algorithm to extract moving *** this basis,a convolutional neural network with global information is constructed to identify and label the *** the experimental results show that the algorithm can extract moving targets and realize moving target recognition under many complex conditions such as target’s long-term stay and small-amplitude movement.

关键词： Deep learning remote sensing images moving target recognition salient

Natural killer cells in liver diseases

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Frontiers of Medicine 2018年第3期12卷 269-279页

作者： Meijuan zheng Haoyu Sun Zhigang tian Department of Clinical Laboratory First Affiliated Hospital of Anhui Medical University Hefei 230022 China Institute of Immunology Key Laboratory of Innate Immunity and Chronic Disease of Chinese Academy of Sciences School of Life Sciences and Medical Center University of Science and Technology of China Hefei 230027 China Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases State Key Laboratory for Diagnosis and Treatment of Infectious Diseases First Affiliated Hospital College of Medicine Zhejiang University Hangzhou 310003 China

The liver has been characterized as a frontline lymphoid organ with complex immunological features such as liver immunity and liver tolerance. Liver tolerance plays an important role in liver diseases including acute inflammation, chronic infection, autoimmune disease, and tumors. The liver contains a large proportion of natural killer （NK） cells, which exhibit heterogeneity in phenotypic and functional characteristics. NK cell activation, well known for its role in the immune surveillance against tumor and pathogen-infected cells, depends on the balance between numerous activating and inhibitory signals. In addition to the innate direct ＂killer＂ functions, NK cell activity contributes to regulate innate and adaptive immunity （helper or regulator）. Under the setting of liver diseases, NK cells are of great importance for stimulating or inhibiting immune responses, leading to either immune activation or immune tolerance. Here, we focus on the relationship between NK cell biology, such as their phenotypic features and functional diversity, and liver diseases.

关键词： natural killer cell phenotype immune activation immune tolerance liver diseases