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An Advanced Quantum-Resistant Signature Scheme for Cloud Based on Eisenstein Ring

Computers, Materials & Continua 2018年第7期56卷 19-34页

作者： Faguo Wu Xiao Zhang Wang Yao Zhiming Zheng Lipeng Xiang Wanpeng Li Key Laboratory of Mathematics Informatics and Behavioral SemanticsMinistry of EducationSchool of Mathematics and Systems ScienceBeihang UniversityBeijing100191China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang UniversityBeijing100191China The Fifth Electronics Research Institute of Ministry of Industry and Information Technology Guangzhou510610China Department of Electrical and Electronic Engineering City University of LondonUK

Signature,widely used in cloud environment,describes the work as readily identifying its *** existing signature schemes in the literature mostly rely on the Hardness assumption which can be easily solved by quantum *** this paper,we proposed an advanced quantum-resistant signature scheme for Cloud based on Eisenstein Ring(ETRUS)which ensures our signature scheme proceed in a lattice with higher *** proved that ETRUS highly improve the performance of traditional lattice signature ***,the Norm of polynomials decreases significantly in ETRUS which can effectively reduce the amount of polynomials convolution ***,storage complexity of ETRUS is smaller than classical ***,according to all convolution of ETRUS enjoy lower degree polynomials,our scheme appropriately accelerate 56.37%speed without reducing its security level.

关键词： Signature quantum-resistant Eisenstein Ring ETRUS

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China’s NTB Market: A Liquidity Dilemma

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Journal of Systems Science & Complexity 2018年第2期31卷 493-507页

作者： LI Yumeng MENG Xiangying ZHANG Yueyan WEI Xianhua School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China Key Laborutory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China Sino-Danish Center for Education and Research University of Chinese Academy of Sciences Beijing 100190 China The State Key Laboratory of Automotive Safety and Energy Tsinghua University Beijing 100084 China Department of Automotive Engineering Tsinghua University Beijing 100084 China

This paper introduces China＇s New Third Board Market（the NTB market） and tests the market-making system in the role of improving market liquidity. The NTB Market is the main part of China＇s OTC market, established in 2006. In comparing with China＇s Main Board Market and the Second Board Market, it attracts a lot of start-up companies that need financing with less strict listing requirements. Meanwhile, it is full of opportunities and challenges that appeal to numerous securities traders and investors with the rapid development momentum. Since its establishment, the NTB Market has been stuck in the lack of liquidity. The authority of the NTB Market introduced market maker system, so as to solve the problem of liquidity. Using the difference-in-difference method（DID method）, the market maker system has been proved to make little contribution to improving the stock liquidity. Although the problem of liquidity is difficult to solve in short term, the NTB Market is full of opportunities for all kinds of participants definitely.

关键词： China＇s stock market DID method liquidity market makers.

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On privacy protection of latent dirichlet allocation model training

arXiv

引用

arXiv 2019年

作者： Zhao, Fangyuan Ren, Xuebin Yang, Shusen Yang, Xinyu School of Computer Science and Technology Xi'an Jiaotong University China National Engineering Laboratory for Big Data Analytics Xi'an Jiaotong University China Ministry of Education Key Lab For Intelligent Networks and Network Security Xi'an Jiaotong University China

Latent Dirichlet Allocation (LDA) is a popular topic modeling technique for discovery of hidden semantic architecture of text datasets, and plays a fundamental role in many machine learning applications. However, like many other machine learning algorithms, the process of training a LDA model may leak the sensitive information of the training datasets and bring significant privacy risks. To mitigate the privacy issues in LDA, we focus on studying privacy-preserving algorithms of LDA model training in this paper. In particular, we first develop a privacy monitoring algorithm to investigate the privacy guarantee obtained from the inherent randomness of the collapsed gibbs sampling (CGS) process in a typical LDA training algorithm on centralized curated datasets. Then, we further propose a locally private LDA training algorithm on crowdsourced data to provide local differential privacy for individual data contributors. The experimental results on real-world datasets demonstrate the effectiveness of our proposed algorithms. Copyright © 2019, The Authors. All rights reserved.

关键词： Statistics

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Fabrication of 1D nanometer tungsten trioxide under different solvent system

Fabrication of 1D nanometer tungsten trioxide under differen...

引用

Chinese Materials Conference, 2018

作者： Zhao, Linyan Shen, Yuegang Fan, Youshu Ma, Liwen Xi, Xiaoli National Engineering Laboratory for Industrial Big-data Application Technology Beijing University of Technology Beijing100124 China College of Material Science and Engineering Key Laboratory of Advanced Functional Materials Education Ministry of China Beijing University of Technology Beijing100124 China

ISBN: (纸本)9783035713848

As a cheap and stable transition metal oxide, the tungsten trioxide (WO3) has received extensive attentions due to superior physical and chemical properties and could be used in electronic devices, lithium-ion batteries, gas sensors, dye sensitized solar cells, catalysts. In this study, the well-designed 1D architecture of nanowires and nanorods was successfully synthesized via a simple and facile solvethermal method with no template or additives. It was found that both solvent type and concentration of W raw material could affect the size and morphology of WO3 significantly in a regular way. Different products showed distinct photocatalytic activities during the processing of degradation methylene blue under visible light. And finally the underlying reasons for the different photocatalytic activities were discussed. © 2019 Trans Tech Publications, Switzerland.

关键词： Tungsten compounds

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Block-Structured Optimization for Anomalous Pattern Detection in Interdependent Networks

Block-Structured Optimization for Anomalous Pattern Detectio...

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IEEE International Conference on data Mining (ICDM)

作者： Fei Jie Chunpai Wang Feng Chen Lei Li Xindong Wu Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Hefei China School of Computer Science and Information Engineering Hefei University of Technology Hefei China Department of Computer Science University at Albany – SUNY Albany NY USA Erik Jonsson School of Engineering & Computer Science The University of Texas at Dallas Dallas TX USA Mininglamp Academy of Sciences Mininglamp Technology Beijing China Institute of Big Knowledge Science Hefei University of Technology Hefei China

We propose a generalized optimization framework for detecting anomalous patterns (subgraphs that are interesting or unexpected) in interdependent networks, such as multi-layer networks, temporal networks, networks of networks, and many others. We frame the problem as a non-convex optimization that has a general nonlinear score function and a set of block-structured and non-convex constraints. We develop an effective, efficient, and parallelizable projection-based algorithm, namely Graph Block-structured Gradient Projection (GBGP), to solve the problem. It is proved that our algorithm 1) runs in nearly-linear time on the network size, and 2) enjoys a theoretical approximation guarantee. Moreover, we demonstrate how our framework can be applied to two very practical applications, and we conduct comprehensive experiments to show the effectiveness and efficiency of our proposed algorithm.

关键词：

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Associations of Serum 25-Hydroxyvitamin D Concentrations with Risks of Mortality and Cardiovascular Disease among Individuals with Psoriasis

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Journal of the American Academy of Dermatology 2025年

作者： Kaiqing Lin Ya Miao Lu Gan Bin Zhao Fang Fang Ru Wang Xiang Chen Jiaqi Huang National Clinical Research Center for Metabolic Diseases Metabolic Syndrome Research Center Key Laboratory of Diabetes Immunology Ministry of Education and Department of Metabolism and Endocrinology The Second Xiangya Hospital of Central South University Changsha Hunan 410011 China Xiangya School of Public Health Central South University Changsha China CSU-Sinocare Research Center for Nutrition and Metabolic Health Changsha China Furong Laboratory Changsha China. Electronic address: JIAQI.HUANG@***. Furong Laboratory Changsha China. Institute of Environmental Medicine Karolinska Institutet Stockholm Sweden. School of Exercise and Health Shanghai University of Sport Shanghai China. Electronic address: WANGRU@***. Department of Dermatology Hunan Engineering Research Center of Skin Health and Disease Hunan Key Laboratory of Skin Cancer and Psoriasis Xiangya Clinical Research Center for Cancer Immunotherapy Xiangya Hospital Central South University Changsha Hunan China National Clinical Research Center for Geriatric Disorders Xiangya Hospital Central South University Changsha Hunan China National Engineering Laboratory of Medical Big Data Application Technology (Central South University) Changsha China Furong Laboratory Changsha China. Electronic address: CHENXIANGCK@***.

BACKGROUND:Evidence remains scarce regarding the relationship between serum 25-hydroxyvitamin D (25(OH)D) and the risk of mortality and cardiovascular disease (CVD) in psoriasis. OBJECTIVE:To explore the potential protective effect of serum 25(OH)D on the risk of mortality and CVD among patients with psoriasis. METHODS:This cohort study included 8,947 psoriasis patients and 178,937 controls identified at baseline in the UK Biobank cohort. Serum 25(OH)D levels were prospectively collected at the time of recruitment. Multivariable-adjusted Cox proportional hazards regression models were used to evaluate the associations between levels of serum 25(OH)D and risk of overall mortality and CVD incidence. RESULTS:Compared to the lowest level of serum 25(OH)D (<25 nmol/L), hazard ratios were 0.54 and 0.78 for overall mortality and incident CVD for the highest level of serum 25(OH)D (≥50 nmol/L) among psoriasis patients, respectively (all P<0.05). Psoriasis patients with serum 25(OH)D ≥50 nmol/L appeared to have no excess risk of mortality and CVD incidence, compared with matched controls. LIMITATIONS:Information on psoriasis subtypes was not available. CONCLUSION:A higher level of serum 25(OH)D was associated with a reduced risk of overall mortality and CVD in individuals with psoriasis.

关键词： cardiovascular disease cohort study epidemiology mortality psoriasis vitamin D

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Mapping Heavy Metals in Cultivated Soils Based on Land Use Types and Cokriging 5th

Mapping Heavy Metals in Cultivated Soils Based on Land Use T...

引用

5th International Conference on Geo-Spatial knowledge and Intelligence, GSKI 2017

作者： Zhao, Jinling Liu, Chuang Song, Qixiang Jiang, Yan Hong, Qi Huang, Linsheng Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Anhui Engineering Laboratory of Agro-Ecological Big Data Anhui University Hefei230601 China Information Engineering Institute Suzhou University Suzhou234000 China

ISBN: (纸本)9789811308925

It is extremely important to explore the heavy metal content and spatial distribution in different cultivated soils. In our study, cokriging (COK) method was used to investigate the relationship between heavy metals and land use types. A total of six heavy metals including Zn, Fe, Cu, Mn, B, S were selected to forecast the heavy metals in cultivated soils. Five types of cultivated land were considered in the study area, including vegetable land, irrigated land, irrigated paddy field, dry land, orchard. Test of normality was firstly carried out to assure that higher prediction accuracy can be obtained, and then correlation analysis and analysis of variance (ANOVA) were performed to find out the most sensitive heavy metals for spatial interpolation. The analysis results showed that Zn, Cu and Fe were the primary heavy metals in soil of the study area. It was obvious that the effect of Mn and Fe were much greater caused by land use types, while they were smaller for B and S. Three errors of mean standard (MS), root mean square error (RMSE), and root mean square standardized error (RMSSE) were derived to assess the prediction accuracy. In comparison with ordinary kriging (OK), the MS of COK approached to 1, the RMSE was much smaller and the RMSSE also approached to 1, which showed that COK can make better predictions than OK. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Heavy metals

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Fully-convolutional intensive feature flow neural network for text recognition

arXiv

引用

arXiv 2019年

作者： Zhang, Zhao Tang, Zemin Zhang, Zheng Wang, Yang Qin, Jie Wang, Meng School of Computer Science and Technology Soochow University China Key Laboratory of Knowledge Engineering with Big Data Ministry of Education School of Computer and Information Hefei University of Technology Hefei China Bio-Computing Research Center Harbin Institute of Technology Shenzhen518055 China Inception Institute of Artificial Intelligence Abu Dhabi United Arab Emirates

The Deep Convolutional Neural Networks (CNNs) have obtained a great success for pattern recognition, such as recognizing the texts in images. But existing CNNs based frameworks still have several drawbacks: 1) the traditaional pooling operation may lose important feature information and is unlearnable;2) the traditional convolution operation optimizes slowly and the hierarchical features from different layers are not fully utilized. In this work, we address these problems by developing a novel deep network model called Fully-Convolutional Intensive Feature Flow Neural Network (IntensiveNet). Specifically, we design a further dense block called intensive block to extract the feature information, where the original inputs and two dense blocks are connected tightly. To encode data appropriately, we present the concepts of dense fusion block and further dense fusion operations for our new intensive block. By adding short connections to different layers, the feature flow and coupling between layers are enhanced. We also replace the traditional convolution by depthwise separable convolution to make the operation efficient. To prevent important feature information being lost to a certain extent, we use a convolution operation with stride 2 to replace the original pooling operation in the customary transition layers. The recognition results on large-scale Chinese string and MNIST datasets show that our IntensiveNet can deliver enhanced recognition results, compared with other related deep models. Copyright © 2019, The Authors. All rights reserved.

关键词： Convolution

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A dynamic planning model based on graph theory for product platform and module

引用

International Journal of Manufacturing Technology and Management 2019年第1-2期33卷 53-75页

作者： Wu, Yongming Hou, Liang Huang, Samuel H. Lai, Rongshen Key Laboratory of Advanced Manufacturing Technology of Ministry of Education Guizhou University Guiyang550025 China Public Big Data Key Laboratory Guizhou Province Guizhou Guiyang550025 China Department of Mechanical and Electrical Engineering Xiamen University Xiamen361005 China Department of Mechanical and Materials Engineering University of Cincinnati CincinnatiOH45221 United States Department of Mechanical and Automotive Engineering Xiamen University of Technology Xiamen361005 China

Platform and module planning results using traditional methods are usually not consistent with the actual situation in product family design (PFD). Research was conducted involving modularisation theory and implementation methods to overcome the difficulty of platform and module dynamic planning/re-design for mass customisation (MC). A graph-theoretical approach was also developed in PFD. Firstly, the commonality and the physical structure of the existing product variants were analyzed in a product family. Part commonality and the physical structure of similar products were then modelled using a directed and an undirected graph, respectively. According to market demands, different platform thresholds and boundary parameters of modules were set dynamically. The product platform and modules were then generated in a product family and the potential parts to be used were identified. Finally, the effectiveness of the proposed approach was demonstrated by the dynamic planning of the working devices of small wheel loaders. Copyright © 2019 Inderscience Enterprises Ltd.

关键词： Dynamics

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Multimodal fusion model for prognostic prediction and radiotherapy response assessment in head and neck squamous cell carcinoma

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npj Digital Medicine 2025年第1期8卷 1-14页

作者： Tian, Ruxian Hou, Feng Zhang, Haicheng Yu, Guohua Yang, Ping Li, Jiaxuan Yuan, Ting Chen, Xi Chen, Ying Hao, Yan Yao, Yisong Zhao, Hongfei Yu, Pengyi Fang, Han Song, Liling Li, Anning Liu, Zhonglu Lv, Huaiqing Yu, Dexin Cheng, Hongxia Mao, Ning Song, Xicheng Department of Otorhinolaryngology Head and Neck Surgery Yantai Yuhuangding Hospital Qingdao University Yantai China Department of Pathology Affiliated Hospital of Qingdao University Qingdao China Key Laboratory of Biomedical Information Engineering of Ministry of Education School of Life Science and Technology Xi’an Jiaotong University Xi’an China Department of Pathology Yantai Yuhuangding Hospital Qingdao University Yantai China The Second School of Clinical Medicine of Binzhou Medical University Yantai China Shandong University of Traditional Chinese Medicine Jinan China Department of Radiology Qilu Hospital of Shandong University Jinan China Linyi People’s Hospital Affiliated to Shandong Second Medical University Linyi China Department of Pathology Shandong Provincial Hospital Affiliated to Shandong First Medical University Jinan China Big Data and Artificial Intelligence Laboratory Yantai Yuhuangding Hospital Qingdao University Yantai China Department of Radiology Yantai Yuhuangding Hospital Qingdao University Yantai China Shandong Provincial Key Laboratory of Neuroimmune Interaction and Regulation Yantai China Shandong Provincial Clinical Research Center for Otorhinolaryngologic Diseases Yantai China Yantai Key Laboratory of Otorhinolaryngologic Diseases Yantai China

Accurate prediction of prognosis and postoperative radiotherapy response is critical for personalized treatment in head and neck squamous cell carcinoma (HNSCC). We developed a multimodal deep learning model (MDLM) integrating computed tomography, whole-slide images, and clinical features from 1087 HNSCC patients across multiple centers. The MDLM exhibited good performance in predicting overall survival (OS) and disease-free survival in external test cohorts. Additionally, the MDLM outperformed unimodal models. Patients with a high-risk score who underwent postoperative radiotherapy exhibited prolonged OS compared to those who did not (P = 0.016), whereas no significant improvement in OS was observed among patients with a low-risk score (P = 0.898). Biological exploration indicated that the model may be related to changes in the cytochrome P450 metabolic pathway, tumor microenvironment, and myeloid-derived cell subpopulations. Overall, the MDLM effectively predicts prognosis and postoperative radiotherapy response, offering a promising tool for personalized HNSCC therapy. © The Author(s) 2025.

关键词： Personalized medicine

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