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arXiv 2018年

作者： Lu, Zhiwu Guan, Jiechao Li, Aoxue Xiang, Tao Zhao, An Wen, Ji-Rong Beijing Key Laboratory of Big Data Management and Analysis Methods School of Information Renmin University of China Beijing100872 China School of Electronics Engineering and Computer Science Peking University Beijing100871 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Samsung AI Centre Cambridge United Kingdom

Zero-shot learning (ZSL) is made possible by learning a projection function between a feature space and a semantic space (e.g., an attribute space). key to ZSL is thus to learn a projection that is robust against the often large domain gap between the seen and unseen class domains. In this work, this is achieved by unseen class data synthesis and robust projection function learning. Specifically, a novel semantic data synthesis strategy is proposed, by which semantic class prototypes (e.g., attribute vectors) are used to simply perturb seen class data for generating unseen class ones. As in any data synthesis/hallucination approach, there are ambiguities and uncertainties on how well the synthesised data can capture the targeted unseen class data distribution. To cope with this, the second contribution of this work is a novel projection learning model termed competitive bidirectional projection learning (BPL) designed to best utilise the ambiguous synthesised data. Specifically, we assume that each synthesised data point can belong to any unseen class;and the most likely two class candidates are exploited to learn a robust projection function in a competitive fashion. As a third contribution, we show that the proposed ZSL model can be easily extended to few-shot learning (FSL) by again exploiting semantic (class prototype guided) feature synthesis and competitive BPL. Extensive experiments show that our model achieves the state-of-the-art results on both problems. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantics

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Culture versus Policy: More Global Collaboration to Effectively Combat COVID-19

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The Innovation 2020年第2期1卷 15-16页

作者： Jianping Li Kun Guo Enrique Herrera Viedma Heesoek Lee Jiming Liu Ning Zhong Luiz Flavio Autran Monteiro Gomes Florin Gheorghe Filip Shu-Cherng Fang Mujgan SagirÖzdemir Xiaohui Liu Guoqing Lu Yong Shi School of Economics and Management University of Chinese Academy of SciencesBeijing 100190China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of SciencesBeijing 100190China Research Center on Fictitious Economy&Data Science Chinese Academy of SciencesBeijing 100190China Department of Computer Science and Artificial Intelligence E.T.S.de Ingenieria Informatica y de TelecomunicacionesUniversity of Granada18071 GranadaSpain Department of Information Management Korea Advanced Institute of Science and TechnologySeoul 207-43 Korea Department of Computer Science and HKBU-CSD&NIPD Joint Research Laboratory for Intelligent Disease Surveillance and Control Hong Kong Baptist UniversityHong KongChina Department of Life Science and Informatics Maebashi Institute of TechnologyMaebashi 371-0816Japan Ibmec University Center Av.Presidente Wilson118Office#111020030-020 Rio de JaneiroBrazil The Romanian Academy Bucharest010071Romania Industrial and Systems Engineering Department North Carolina State UniversityRaleighNC 27695USA Department of Industrial Engineering Eskisehir Osmangazi University26480 EskisehirTurkey Department of Computer Science Brunel University LondonLondonUB83PHUK Department of Biology and School of Interdisciplinary Informatics University of Nebraska at OmahaOmahaNE 68182USA College of Information Science and Technology University of Nebraska at OmahaOmahaNE 68182USA

The outbreak of COVID-19 seriously challenges every government with regard to capacity and management of public health systems facing the catastrophic *** and anti-epidemic policy do not necessarily conflict with each *** countries and governments should be more tolerant to each other in seeking cultural and political consensus to overcome this historically tragic pandemic together.

关键词： seeking overcome policy

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Gut microbiota and diabetes: From correlation to causality and mechanism

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World Journal of Diabetes 2020年第7期11卷 293-308页

作者： Wei-Zheng Li Kyle Stirling Jun-Jie Yang Lei Zhang Microbiome-X Beijing Advanced Innovation Center for Big Data-Based Precision MedicineSchool of Medicine and EngineeringKey Laboratory of Big Data-Based Precision MedicineBeihang UniversityBeijing 100191China School of Biological Science and Medical Engineering Beihang UniversityBeijing 100191China Luddy School of Informatics Computing and EngineeringIndiana UniversityBloomingtonIN 47408United States The Crisis Technologies Innovation Lab Indiana UniversityThe Information Technology Services and the Pervasive Technology InstituteBloomingtonIN 47408United States Shandong Institute of Industrial Technology for Health Sciences and Precision Medicine Jinan 250000Shandong ProvinceChina College of Life Science Qilu Normal UniversityJinan 250000Shandong ProvinceChina Microbiome Research Center Shandong Institutes for Food and Drug ControlJinan 250000Shandong ProvinceChina Shandong Children’s Microbiome Center Qilu Children's Hospital of Shandong UniversityJinan 250000Shandong ProvinceChina Microbiological Laboratory Lin Yi People’s HospitalLinyi 276000Shandong ProvinceChina Qingdao Human Microbiome Center The Affiliated Central Hospital of Qingdao UniversityQingdao 266000Shandong ProvinceChina Institute for Medical Dataology Cheeloo College of MedicineShandong UniversityJinan 250000Shandong ProvinceChina Department of Biostatistics School of Public HealthCheeloo College of MedicineShandong UniversityJinan 250000Shandong ProvinceChina Shandong Children’s Microbiome Center Research Institute of PediatricsQilu Children's HospitalCheeloo College of MedicineShandong Universityand Jinan Children's HospitalJinan 250022Shandong ProvinceChina

In this review,we summarize the recent microbiome studies related to diabetes disease and discuss the key findings that show the early emerging potential causal roles for *** a global scale,diabetes causes a significant negative impact to the health status of human *** review covers type 1 diabetes and type 2 *** examine promising studies which lead to a better understanding of the potential mechanism of microbiota in diabetes *** appears that the human oral and gut microbiota are deeply interdigitated with *** is that *** studies of the human microbiome are capturing the attention of scientists and healthcare practitioners worldwide by focusing on the interplay of gut microbiome and *** studies focus on the role and the potential impact of intestinal microflora in *** paint a clear picture of how strongly microbes are linked and associated,both positively and negatively,with the fundamental and essential parts of diabetes in *** microflora seems to have an endless capacity to impact and transform *** conclude that there is clear and growing evidence of a close relationship between the microbiota and diabetes and this is worthy of future investments and research efforts.

关键词： Diabetes Microbiota Causality Mechanism Type 1 diabetes Type 2 diabetes Insulin resistance Inflammation Metabolites

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Eighteen years(2001–2018)of forest habitat loss across the Asian elephant’s range and its drivers

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Science Bulletin 2022年第15期67卷 1513-1516页

作者： Lei Luo Xinyuan Wang Huadong Guo Lanwei Zhu Yuanxu Ma Ruixia Yang Siyuan Wang Guizhou Wang Meng Wang Jie Shao Chuansheng Liu International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China International Centre on Space Technologies for Natural and Cultural Heritage(HIST)under the Auspices of UNESCO Beijing 100094China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China China Satellite Remote Sensing Ground Station Aerospace Information Research InstituteChinese Academy of SciencesBeijing 100094China School of Geospatial Engineering and Science Sun Yat-sen UniversityZhuhai 519082China

The Asian elephant(Elephas maximus)-the largest living land animal in Asia-is categorized as an endangered species according to the International Union for Conservation of Nature(IUCN)Red List and is listed in the Convention on International Trade in Endangered Species of Wild Fauna and Flora(CITES)Appendix I[1].Over the past 100 years,the range of the Asian elephant has declined by as much as 90%[2].At present,the Asian elephant inhabits forest-dominated habitat in only 13 countries across South and Southeast Asia(Fig.S1 online),and the IUCN Species Survival Commission(SSC)Asian Elephant Specialist Group(AsESG)estimated the global wild population size of Asian elephants to number 45,671-49,028 individuals[3].Forest habitat loss,along with human-elephant conflict,poaching and the illegal trade in ivory and elephant body parts,is weakening global conservation efforts towards the recovery of wild Asian elephant populations at local,national and range-wide scales[3,4].

关键词：亚洲象 habitat Species

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Coherent photoproduction of low-pT charmonium in peripheral heavy ion collisions within the color dipole model

arXiv

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arXiv 2021年

作者： Yu, Gongming Cai, Yanbing Fu, Yongping Yang, Haitao Gao, Quangui Hu, Qiang Hu, Liyuan Li, Wei Song, Yushou Fundamental Science on Nuclear Safety and Simulation Technology Laboratory Harbin Engineering University Harbin150000 China Guizhou Key Laboratory in Physics and Related Areas Guizhou Key Laboratory of Big Data Statistic Analysis Guizhou University of Finance and Economics Guiyang550025 China Department of Physics West Yunnan University Lincang677000 China Department of Physics Zhaotong University Zhaotong657000 China Department of Physics Yuxi Normal University Yuxi653100 China Institute of Modern Physics Chinese Academy of Sciences Lanzhou730000 China

We calculate the centrality dependence for coherent photoproduction of very low-pT J/ψ at Relativistic Heavy Ion Collider (RHIC) and Large Hadron Collider (LHC) energies within the impact parameter dependent saturated color dipole model. By using the large equivalent photon fluxes, we present the differential cross section of very low-pT J/ψ produced by coherent photonuclear in peripheral heavy-ion collisions. The numerical results demonstrate that our calculation are agree with J/ψ data in peripheral heavy ion collisions at Relativistic Heavy Ion Collider (RHIC) energies. © 2021, CC BY.

关键词： Colliding beam accelerators

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Applied Experimental Research on In-Situ Online Monitoring Instrument for Soil Radon in Fault Zone

SSRN

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SSRN 2024年

作者： Zhao, Ying Chen, Zhi Wang, Chengnan Hu, Xudong Liu, Zhaofei He, Hongyi Observatory for Geodynamic of the East Yangtze Block in Jiujiang Jiujiang332006 China Jiangxi Earthquake Agency Nanchang330000 China CEA Key Laboratory of Earthquake Forecasting Institute of Earthquake Science China Earthquake Administration Beijing100036 China Geological Survey of Jiangxi Province Nanchang330000 China Jiangxi Engineering Laboratory on Radioactive Geoscience and Big Data Technology East China University of Technology Nanchang330013 China Hubei Subsurface Multi-scale Imaging Key Laboratory School of Geophysics and Geomatics China University of Geosciences Wuhan430074 China

As an emerging method for monitoring and prediction of seismic underground fluid, the reliability and stability of in-situ online monitoring devices for soil radon are crucial performance indicators that are directly related to the successful implementation of continuous monitoring of soil radon in seismic areas. This study conducted laboratory testing and field applications of a new in-situ online monitoring instrument for seismic soil radon, utilizing the experimental testing conditions provided by the radon monitoring instrument detection platform of the China Earthquake Administration and the natural experimental site at Xianshuihe Fault Zone in the China Seismic Experimental Site. The results indicate that laboratory measurement repeatability of the instrument is 5.53%, the relative intrinsic error of radon volume response activity is 1.53%, and the response capability of hourly sampling at high radon volume response activity (greater than 1.0×105 Bq/m3) lags behind the standard instrument by 2 hours, essentially meeting the requirements for seismic observation. Under field conditions, the instruments exhibit good synchronization in response at different depths at the same location. However, further improvements are needed to enhance the consistency of long-term operation in the field, as well as the adaptability to outdoor self-powering, data transmission, and environmental conditions. © 2024, The Authors. All rights reserved.

关键词： Radon

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Capacity analysis of ship-tugging operations in a large container port

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Asian Transport Studies 2020年 6卷

作者： Kang, Liujiang Gao, Song Meng, Qiang Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Ministry of Transport Beijing Jiaotong University 100044 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan 430063 China Department of Civil and Environmental Engineering National University of Singapore Singapore 117576 Singapore

In this study, we deal with the simulation problem of ship-tugging operations in a large container port. First, we build a tugboat-service network using a directed graph, where the nodes consist of tugboat bases, anchorages, and berths while the arcs represent the directed links between nodes. Second, we develop a marine traffic simulation system, which can simulate maritime traffic conditions in restricted waters, such as large container ports and busy straits. The marine traffic simulation system is a customized system. Users are allowed to set their study areas and virtual traffic environment (such as traffic demand and network structure) at will. Finally, we conduct various simulations for a real tugboat-service network of Singapore Port, which includes one anchorage, one tugboat base, two berths, and two channels between the anchorage and berths. A detailed analysis of the tugging capacity is provided based on simulation results. © 2020 The Authors

关键词： Capacity estimation Container ports Simulation system development Tugging operations

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MAINet: Modality-Aware Interaction Network for Medical Image Fusion

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ACM Transactions on Multimedia Computing, Communications, and Applications 1000年

作者： Lisi Wei Libo Zhao Xiaoli Zhang College of Computer Science and Technology Jilin University China College of Artificial Intelligence and Big Data Hulunbuir University China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China College of Computer Science and Technology Jilin University China and Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China

Due to the limitations of imaging sensors, obtaining a medical image that simultaneously captures both functional metabolic data and structural tissue details remains a significant challenge in clinical diagnosis. To address this, Multimodal Medical Image Fusion (MMIF) has emerged as an effective technique for integrating complementary information from multimodal source images, such as CT, PET, and SPECT, which is critical for providing a comprehensive understanding of both anatomical and functional aspects of the human body. One of the key challenges in MMIF is how to exchange and aggregate this multimodal information. This paper rethinks MMIF by addressing the harmony of modality gaps and proposes a novel Modality-Aware Interaction Network (MAINet), which leverages cross-modal feature interaction and progressively fuses multiple features in graph space. Specifically, we introduce two key modules: the Cascade Modality Interaction (CMI) module and the Dual-Graph Learning (DGL) module. The CMI module, integrated within a multi-scale encoder with triple branches, facilitates complementary multimodal feature learning and provides beneficial feedback to enhance discriminative feature learning across modalities. In the decoding process, the DGL module aggregates hierarchical features in two distinct graph spaces, enabling global feature interactions. Moreover, the DGL module incorporates a bottom-up guidance mechanism, where deeper semantic features guide the learning of shallower detail features, thus improving the fusion process by enhancing both scale diversity and modality awareness for visual fidelity results. Experimental results on medical image datasets demonstrate the superiority of the proposed method over existing fusion approaches in both subjective and objective evaluations. We also validated the performance of the proposed method in applications such as infrared-visible image fusion and medical image segmentation.

关键词： Multimodal fusion Medical image fusion Cascade modality interaction Modality-awareness Graph convolutional network

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FASNet: Feature alignment-based method with digital pathology images in assisted diagnosis medical system

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Heliyon 2024年第22期10卷 e40350页

作者： He, Keke Zhu, Jun Li, Limiao Gou, Fangfang Wu, Jia School of Computer Science and Engineering Changsha University Changsha 410003 China Hunan University of Medicine General Hospital Huaihua 418000 China Collaborative Innovation Center for Medical Artificial Intelligence and Big Data Decision Making Assistance Hunan University of Medicine Huaihua 418000 China State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang 550025 China Research Center for Artificial Intelligence Monash University Melbourne Clayton 3800 VIC Australia

Many important information in medical research and clinical diagnosis are obtained from medical images. Among them, digital pathology images can provide detailed tissue structure and cellular information, which has become the gold standard for clinical tumor diagnosis. With the development of neural networks, computer-aided diagnosis presents the identification results of various cell nuclei to doctors, which facilitates the identification of cancerous regions. However, deep learning models require a large amount of annotated data. Pathology images are expensive and difficult to obtain, and insufficient annotation data can easily lead to biased results. In addition, when current models are evaluated on an unknown target domain, there are errors in the predicted boundaries. Based on this, this study proposes a feature alignment-based detail recognition strategy for pathology image segmentation (FASNet). It consists of a preprocessing model and a segmentation network (UNW). The UNW network performs instance normalization and categorical whitening of feature images by inserting semantics-aware normalization and semantics-aware whitening modules into the encoder and decoder, which achieves the compactness of features of the same class and the separation of features of different classes. The FASNet method can identify the feature detail information more efficiently, and thus differentiate between different classes of tissues effectively. The experimental results show that the FASNet method has a Dice Similarity Coefficient (DSC) value of 0.844. It achieves good performance even when faced with test data that does not match the distribution of the training data. Code: https://***/zlf010928/***. © 2024

关键词： Assisted diagnosis Deep learning Digital pathology images Feature alignment Insufficient annotation sets

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On energy-efficient NOMA designs for heterogeneous low-latency downlink transmissions

arXiv

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arXiv 2018年

作者： Xu, Yanqing Shen, Chao Chang, Tsung-Hui Lin, Shih-Chun Zhao, Yajun Zhu, Gang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Science and Engineering Chinese University of Hong Kong Shenzhen China Shenzhen Research Institute of Big Data Shenzhen China Department of Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei Taiwan Algorithm Department Wireless Product RandD Institute ZTE Corporation Shenzhen China

This paper investigates energy-efficient resource allocation for the two-user downlink with strict latency constraints at users. To cope with strict latency constraints, the capacity formula of the finite blocklength codes (FBCs) is adopted, in contrast to the classical Shannon capacity formula. The FBC formula explicitly specifies the trade-off between blocklength and reliability. We first consider the case where the transmitter uses super-position coding based non-orthogonal multiple access (NOMA). However, due to heterogeneous latency constraints and channel conditions at users, the conventional successive interference cancellation may be infeasible. We thus propose to use different interference mitigation schemes according to heterogeneous user conditions and solve the corresponding NOMA design problems. Though the target energy function is non-convex and implicit, optimal user blocklength and power allocation can still be identified for the considered NOMA schemes and checking the problem feasibility is simple. It is observed that when the latency requirements are more heterogeneous, the NOMA scheme cannot achieve the best energy-efficiency of the downlink. In view of this, a hybrid transmission scheme which includes time division multiple access (TDMA) and NOMA as special cases is considered. Although the energy minimization is even challenging than the pure NOMA design problem, we propose a concave approximation of the FBC capacity formula which allows to obtain computationally efficient and high-quality solutions. Simulation results show that the hybrid scheme can benefits from both NOMA and TDMA. Copyright © 2018, The Authors. All rights reserved.

关键词： Energy efficiency

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