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arXiv 2022年

作者： Li, Yang Lin, Qingfeng Liu, Ya-Feng Ai, Bo Wu, Yik-Chung Shenzhen Research Institute of Big Data Shenzhen518172 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong The State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China

Device activity detection in the emerging cell-free massive multiple-input multiple-output (MIMO) systems has been recognized as a crucial task in machine-type communications, in which multiple access points (APs) jointly identify the active devices from a large number of potential devices based on the received signals. Most of the existing works addressing this problem rely on the impractical assumption that different active devices transmit signals synchronously. However, in practice, synchronization cannot be guaranteed due to the low-cost oscillators, which brings additional discontinuous and nonconvex constraints to the detection problem. To address this challenge, this paper reveals an equivalent reformulation to the asynchronous activity detection problem, which facilitates the development of a centralized algorithm and a distributed algorithm that satisfy the highly nonconvex constraints in a gentle fashion as the iteration number increases, so that the sequence generated by the proposed algorithms can get around bad stationary points. To reduce the capacity requirements of the fronthauls, we further design a communication-efficient accelerated distributed algorithm. Simulation results demonstrate that the proposed centralized and distributed algorithms outperform state-of-the-art approaches, and the proposed accelerated distributed algorithm achieves a close detection performance to that of the centralized algorithm but with a much smaller number of bits to be transmitted on the fronthaul links. Copyright © 2022, The Authors. All rights reserved.

关键词： Internet of things

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An Explainable Multi-view Semantic Fusion Model for Multimodal Fake News Detection

An Explainable Multi-view Semantic Fusion Model for Multimod...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Zhi Zeng Mingmin Wu Guodong Li Xiang Li Zhongqiang Huang Ying Sha College of Informatics Huazhong Agricultural University Wuhan China Key Laboratory of Smart Farming for Agricultural Animals Wuhan China Hubei Engineering Technology Research Center of Agricultural Big Data Wuhan China Engineering Research Center of Intelligent Technology for Agriculture Ministry of Education Urumqi China Xinjiang Technical Institute of Physics and Chemistry Chinese Academy of Sciences Wuhan China

The existing models have been achieved great success in capturing and fusing miltimodal semantics of news. However, they paid more attention to the global information, ignoring the interactions of global and local semantics and the inconsistency between different modalities. Therefore, we propose an explainable multi-view semantic fusion model (EMSFM), where we aggregate the important inconsistent semantics from local and global views to compensate the global information. Inspired by various forms of artificial fake news and real news, we summarize four views of multimodal correlation: consistency and inconsistency in the local and global views. Integrating these four views, our EMSFM can interpretatively establish global and local fusion between consistent and inconsistent semantics in multimodal relations for fake news detection. The extensive experimental results show that the EMSFM can improve the performance of multimodal fake news detection and provide a novel paradigm for explainable multi-view semantic fusion.

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Experimental Study on the Zebra Crossing Behavior of Mixed Bicycles and Pedestrians

SSRN

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SSRN 2022年

作者： Ma, Jian Wang, Qiao Chen, Juan Jiang, Rui Song, Weiguo Li, Ruoyu Lian, Liping School of Transportation and Logistics National Engineering Laboratory of Integrated Transportation Big Data Application Technology National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu610031 China Faculty of Geosciences and Environmental Engineering Southwest Jiaotong University Chengdu610031 China Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Ministry of Transport Beijing Jiaotong University Beijing100044 China State Key Laboratory of Fire Science University of Science and Technology of China Hefei230027 China School of Urban Planning and Design Peking University Shenzhen Graduate School School of Architectural Engineering Shenzhen Polytechnic Shenzhen518055 China

Slow transportation mode, consisting of walking and cycling, plays an important role in urban traffic system. Based on the fact that bicycles and pedestrians often share the common road facility, we conducted bicycle-pedestrian mixed flow experiments to investigate the interaction effect among individuals in a 10 m-long, 3 m-wide passageway, mimicking the zebra crossing area. The goal is to explore the influence of bicycles proportion ( p ) on traffic efficiency and investigate the spatial distribution of agents in the mixed flow. Our analyses showed that the increase of bicycle proportion results in longer passing time and less travel time because of large personal space requirements of cyclists. When the bicycle proportion is small or large, the majority pedestrians (bicycles) were divided into several parts by minor bicycles (pedestrians) along the motion direction. We also recorded the following- and lateral- distance between two nearest individuals to calculate the theoretical formula of the passing time for unidirectional bicycle-pedestrian mixed flow based on the existing formula. Comparing the passing time between numerical calculation and experimental data, the effect coefficients for bicycle and pedestrian were obtained. Focusing on the overtaking bicycles, the through gap, lateral and headway distance that decide the overtaking behavior were analyzed. These findings are the first step toward the development of bicycle-pedestrian mixed flow on zebra crossing, which is contribute to provide practical implications for the planning and design of bicycle and pedestrian shared infrastructures. © 2022, The Authors. All rights reserved.

关键词： Travel time

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OverlapMamba: Novel Shift State Space Model for LiDAR-based Place Recognition

arXiv

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arXiv 2024年

作者： Xiang, Qiuchi Cheng, Jintao Luo, Jiehao Wu, Jin Fan, Rui Chen, Xieyuanli Tang, Xiaoyu School of Data Science and Engineering Xingzhi College South China Normal University Shanwei516600 China School of Electronic and Information Engineering South China Normal University Guangdong Foshan528225 China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong College of Intelligence Science and Technology National University of Defense Technology Changsha China College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

Place recognition is the foundation for enabling autonomous systems to achieve independent decision-making and safe operations. It is also crucial in tasks such as loop closure detection and global localization within SLAM. Previous methods utilize mundane point cloud representations as input and deep learning-based LiDAR-based Place Recognition (LPR) approaches employing different point cloud image inputs with convolutional neural networks (CNNs) or transformer architectures. However, the recently proposed Mamba deep learning model, combined with state space models (SSMs), holds great potential for long sequence modeling. Therefore, we developed OverlapMamba, a novel network for place recognition, which represents input range views (RVs) as sequences. In a novel way, we employ a stochastic reconstruction approach to build shift state space models, compressing the visual representation. Evaluated on three different public datasets, our method effectively detects loop closures, showing robustness even when traversing previously visited locations from different directions. Relying on raw range view inputs, it outperforms typical LiDAR and multi-view combination methods in time complexity and speed, indicating strong place recognition capabilities and realtime efficiency. Copyright © 2024, The Authors. All rights reserved.

关键词： Decision making

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Atrachinenins D–S, Novel Meroterpenoids with Geranyl Hydroquinone Moiety from Atractylodes Chinensis by the LC/MS-Based Molecular Decoy and Targeted Isolation

SSRN

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SSRN 2023年

作者： Chen, Fei-Long Liu, Dong-Li Ren, Wen-Jing Xiong, Hao-Ming Bai, Li-Ping Zhang, Wei Hon, Chitin Jiang, Zhi-Hong Zhu, Guo-Yuan Key Laboratory of Quality Research in Chinese Medicines Guangdong-Hong Kong-Macao Joint Laboratory of Respiratory Infectious Disease Macau Institute for Applied Research in Medicine and Health Macau University of Science and Technology China Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications Faculty of Innovation Engineering Macau University of Science and Technology Taipa China

To mine fascinating molecules from the rhizomes of Atractylodes chinensis, the known molecular formula of atrachinenin A was used as a bait to search LC-HRMS data in different subfractions. Sixteen new meroterpenoids, atrachinenins D–S (1–16) including three unprecedented carbon skeletons (1–5) and eleven new oxygen-bridged hybrids (6–16) were obtained by the targeted isolation. Their structures and absolute configurations were elucidated by the spectroscopic data and electronic circular dichroism (ECD) calculations. All of the isolated compounds were evaluated for their inhibitory activity of NO production and compounds 1, 4, and 8 showed moderate anti-inflammatory activity. The proposed biosynthetic pathways of 1–5 were also discussed. © 2023, The Authors. All rights reserved.

关键词： Phenols

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Train Faster, Perform Better: Modular Adaptive Training in Over-Parameterized Models

arXiv

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arXiv 2024年

作者： Shi, Yubin Chen, Yixuan Dong, Mingzhi Yang, Xiaochen Li, Dongsheng Wang, Yujiang Dick, Robert Lv, Qin Zhao, Yingying Yang, Fan Lu, Tun Gu, Ning Shang, Li China and Shanghai Key Laboratory of Data Science School of Computer Science Fudan University China School of Mathematics Statistics University of Glasgow United Kingdom Microsoft Research Asia Shanghai China Department of Engineering Science University of Oxford United Kingdom Department of Electrical Engineering and Computer Science University of Michigan United States Department of Computer Science University of Colorado Boulder United States School of Microelectronics Fudan University China

Despite their prevalence in deep-learning communities, over-parameterized models convey high demands of computational costs for proper training. This work studies the fine-grained, modular-level learning dynamics of over-parameterized models to attain a more efficient and fruitful training strategy. Empirical evidence reveals that when scaling down into network modules, such as heads in self-attention models, we can observe varying learning patterns implicitly associated with each module's trainability. To describe such modular-level learning capabilities, we introduce a novel concept dubbed modular neural tangent kernel (mNTK), and we demonstrate that the quality of a module's learning is tightly associated with its mNTK's principal eigenvalue λmax. A large λmax indicates that the module learns features with better convergence, while those miniature ones may impact generalization negatively. Inspired by the discovery, we propose a novel training strategy termed Modular Adaptive Training (MAT) to update those modules with their λmax exceeding a dynamic threshold selectively, concentrating the model on learning common features and ignoring those superfluous ones. Unlike most existing training schemes with a complete BP cycle across all network modules, MAT can significantly save computations by its partially-updating strategy and can further improve performance. Experiments show that MAT nearly halves the computational cost of model training and outperforms the accuracy of baselines. © 2024, CC BY.

关键词： Eigenvalues and eigenfunctions

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Identifying the Collaborative Areas of Ride-Hailing and Traditional Taxi Services Based on Vehicle Trajectory data

SSRN

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SSRN 2022年

作者： Zhao, Zhiyuan Yao, Wei Wang, Pengzhou Wu, Sheng Wu, Qunyong Fang, Lina Fang, Zhixiang Fuzhou University Fuzhou350108 China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education Fuzhou University Fuzhou350002 China National Engineering Research Centre of Geospatial Information Technology Fuzhou University Fuzhou350002 China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China

Ride-hailing services (RHS) and traditional taxi services (TTS) play important roles in satisfying people’s daily travel demands. In recent years, RHS have experienced rapid growth, making daily travel more convenient and fundamentally changing the vehicle-hailing service market once dominated by traditional taxis. However, the rapid growth of RHS has also raised the general number of empty ride-hailing vehicles, potentially resulting in increasing traffic congestion and pollutant emissions. Finding the collaborative areas of RHS and TTS can effectively improve the efficiency of travel services. Accordingly, we propose a method to identify the collaborative areas of RHS and TTS based on sparsely sampled trajectory data. We first recover sparse trajectories based on a shortest path algorithm. Then, the indicators describing empty vehicles and the travel demand are defined and calculated. Finally, to identify these collaborative areas, rules are adopted to finding the areas with high unloaded vehicles of one vehicle type with a low travel demand to supplement the other vehicle type in high demand. A data set of Xiamen Island is used to validate the effectiveness of the proposed method. We find that (1) the proposed method can improve the usability of sparsely sampled trajectory data and effectively identify the collaborative areas of RHS and TTS. (2) At facilities such as office buildings and Software Park, ride-hailing vehicles are dispatched to supplement taxis on weekday mornings, while the reverse relationship holds on weekend mornings. The collaborative areas where RHS are dispatched to assist TTS are concentrated near large shopping malls on weekdays and weekends at 18:00;additionally, residential areas near scenic spots demand supplementary ride-hailing vehicles at 18:00 on holidays, while supplemental taxis are dispatched at 09:00. © 2022, The Authors. All rights reserved.

关键词： Taxicabs

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Machine learning in diagnosis of coronary artery disease

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Chinese Medical Journal 2021年第4期134卷 401-403页

作者： Hao Ling Zi-Yuan Guo Un-Lin Tan Ren-Chu Guan Jing-Bo Chen Chun-Li Department of Cardiology the Second Hospital of Jilin UniversityChangchunJilin 130012China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and TechnologyJilin UniversityChangchunJilin 130012China

Cardiovascular diseases continue to be the foremost cause of death among both males and females worldwide.[1]Coronary artery disease(CAD)represents a major subtype of cardiovascular *** evidence has highlighted a worldwide increase in incidence of CAD clinical manifestations regardless of geographical region.[2]Despite a steady decline in CAD mortality in western countries over the past few decades,approximately one-third of the population suffering from CAD will succumb to the *** and accurate diagnostic decisions are crucial for patients with CAD and aid in guidance for effective treatment.

关键词： CAD diagnosis continue

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Excess mortality associated with high ozone exposure:A national cohort study in China

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Environmental Science and Ecotechnology 2023年第3期15卷 98-105页

作者： Yang Yuan Kai Wang Haitong Zhe Sun Yu Zhan Zhiming Yang Kejia Hu Yunquan Zhang Institute of Social Development and Health Management Hubei Province Key Laboratory of Occupational Hazard Identification and ControlSchool of Public HealthWuhan University of Science and TechnologyWuhan430065China Centre for Atmospheric Science Yusuf Hamied Department of ChemistryUniversity of CambridgeCambridgeCB21EWUK Department of Earth Sciences University of CambridgeCambridgeCB23EQUK Department of Environmental Science and Engineering Sichuan UniversityChengduSichuan610065China School of Economics and Management University of Science and Technology BeijingBeijing100083China Department of Big Data in Health Science School of Public HealthZhejiang UniversityHangzhou310058China

Emerging epidemiological studies suggest that long-term ozone(O_(3))exposure may increase the risk of mortality,while pre-existing evidence is mixed and has been generated predominantly in North America and *** this study,we investigated the impact of long-term O_(3)exposure on all-cause mortality in a national cohort in China.A dynamic cohort of 20882 participants aged40 years was recruited between 2011 and 2018 from four waves of the China Health and Retirement Longitudinal Study.A Cox proportional hazard regression model with time-varying exposures on an annual scale was used to estimate the mortality risk associated with warm-season(Aprile September)O_(3)*** annual average level of participant exposure to warm-season O_(3)concentrations was 100 mg m^(-3)(range:61 e142 mg m^(-3)).An increase of 10 mg m^(-3)in O_(3)was associated with a hazard ratio(HR)of 1.18(95%confidence interval[CI]:1.13e1.23)for all-cause *** with the first exposure quartile of O_(3),HRs of mortality associated with the second,third,and highest exposure quartiles were 1.09(95%CI:0.95e1.25),1.02(95%CI:0.88e1.19),and 1.56(95%CI:1.34e1.82),respectively.A J-shaped concentration eresponse associationwas observed,revealing a non-significant increase in risk below a concentration of approximately 110 mg m^(-3).Low-temperature-exposure residents had a higher risk of mortality associated with long-term O_(3)*** study expands current epidemiological evidence from China and reveals that high-concentration O_(3)exposure curtails the long-term survival of middle-aged and older adults.

关键词： Ozone Long-term exposure All-cause mortality Cohort study

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Solving Multitrip Pickup and Delivery Problem With Time Windows and Manpower Planning Using Multiobjective Algorithms

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1134-1153页

作者： Jiahai Wang Yuyan Sun Zizhen Zhang Shangce Gao the Department of Computer Science and also with the Key Laboratory of Machine Intelligence and Advanced ComputingMinistry of Educationand also with the Guangdong Key Laboratory of Big Data Analysis and ProcessingSun Yat-sen UniversityGuangzhou 510275China the Department of Computer Science Sun Yat-sen UniversityGuangzhou 510275China the Faculty of Engineering University of ToyamaToyama-shi 930-8555Japan

The multitrip pickup and delivery problem with time windows and manpower planning(MTPDPTW-MP)determines a set of ambulance routes and finds staff assignment for a hospital. It involves different stakeholders with diverse interests and objectives. This study firstly introduces a multiobjective MTPDPTW-MP(MO-MTPDPTWMP) with three objectives to better describe the real-world scenario. A multiobjective iterated local search algorithm with adaptive neighborhood selection(MOILS-ANS) is proposed to solve the problem. MOILS-ANS can generate a diverse set of alternative solutions for decision makers to meet their requirements. To better explore the search space, problem-specific neighborhood structures and an adaptive neighborhood selection strategy are carefully designed in MOILS-ANS. Experimental results show that the proposed MOILS-ANS significantly outperforms the other two multiobjective algorithms. Besides, the nature of objective functions and the properties of the problem are analyzed. Finally, the proposed MOILS-ANS is compared with the previous single-objective algorithm and the benefits of multiobjective optimization are discussed.

关键词： Adaptive neighborhood selection manpower planning multiobjective optimization multitrip pickup and delivery problem with time windows

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