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arXiv 2021年

作者： Zhan, Tianxiang Xiao, Fuyuan School of Computer and Information Science Southwest University Chongqing400715 China School of Big Data and Software Engineering Chongqing University Chongqing401331 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China

Time series has attracted a lot of attention in many fields today. Time series forecasting algorithm based on complex network analysis is a research hotspot. How to use time series information to achieve more accurate forecasting is a problem. To solve this problem, this paper proposes a weighted network forecasting method to improve the forecasting accuracy. Firstly, the time series will be transformed into a complex network, and the similarity between nodes will be found. Then, the similarity will be used as a weight to make weighted forecasting on the predicted values produced by different nodes. Compared with the previous method, the proposed method is more accurate. In order to verify the effect of the proposed method, the experimental part is tested on M1, M3 datasets and Construction Cost Index (CCI) dataset, which shows that the proposed method has more accurate forecasting performance. Copyright © 2021, The Authors. All rights reserved.

关键词： Time series

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Transformer-based Annotation Bias-aware Medical Image Segmentation

arXiv

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arXiv 2023年

作者： Liao, Zehui Xie, Yutong Hu, Shishuai Xia, Yong National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an710072 China Australian Institute for Machine Learning The University of Adelaide AdelaideSA Australia Ningbo Institute of Northwestern Polytechnical University Ningbo315048 China Research and Development Institute Northwestern Polytechnical University in Shenzhen Shenzhen518057 China

Manual medical image segmentation is subjective and suffers from annotator-related bias, which can be mimicked or amplified by deep learning methods. Recently, researchers have suggested that such bias is the combination of the annotator preference and stochastic error, which are modeled by convolution blocks located after decoder and pixel-wise independent Gaussian distribution, respectively. It is unlikely that convolution blocks can effectively model the varying degrees of preference at the full resolution level. Additionally, the independent pixel-wise Gaussian distribution disregards pixel correlations, leading to a discontinuous boundary. This paper proposes a Transformer-based Annotation Bias-aware (TAB) medical image segmentation model, which tackles the annotator-related bias via modeling annotator preference and stochastic errors. TAB employs the Transformer with learnable queries to extract the different preference-focused features. This enables TAB to produce segmentation with various preferences simultaneously using a single segmentation head. Moreover, TAB takes the multivariant normal distribution assumption that models pixel correlations, and learns the annotation distribution to disentangle the stochastic error. We evaluated our TAB on an OD/OC segmentation benchmark annotated by six annotators. Our results suggest that TAB outperforms existing medical image segmentation models which take into account the annotator-related bias. © 2023, CC BY-NC-ND.

关键词： Gaussian distribution

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Design of Leakage Current Monitoring System for Low Voltage Power Grid Based on NB-IoT 6th

Design of Leakage Current Monitoring System for Low Voltage ...

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6th International Conference on Advanced Machine Learning Technologies and applications, AMLTA 2021

作者： Xu, GuanWei Zheng, RongJin Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology Fuzhou China Fujian Institute of Engineering Smart Grid Simulation Analysis and Integrated Control of Fujian University Engineering Research Center Fuzhou Fujian China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical and Electrical Engineering National Taipei University of Technology Taipei Taiwan Department of Business Administration North Borneo University College Sabah Malaysia

ISBN: (纸本)9783030697167

Leakage current of low-voltage power grid lines will cause major safety hazards such as personal electric shock and electrical fire. Traditional leakage current protectors can not play their due protection role due to their quality problems and aging, and other reasons. When leakage current accidents occur, traditional manual troubleshooting is inefficient. Aiming at the safety of leakage current in a low-voltage power grid, a new leakage current monitoring system is designed based on NB-IoT technology. The system includes the detection and transmission of leakage current and the construction of the cloud platform, which can realize the real-time monitoring of leakage current in low-voltage power grid and prevent and solve the leakage current safety problems. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Leakage currents

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Large-Scale Target Detection and Classification Based on Improved Candidate Regions 11th

Large-Scale Target Detection and Classification Based on Imp...

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11th International Conference on Image and Graphics, ICIG 2021

作者： Xi, Runping Han, Qianqian Jia, Gaoyun Kou, Xuefeng School of Computer Science and Techology Northwest Polytechnical University Xi’an710072 China National Engineering Laboratory of Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China Shaanxi Provincial Key Laboratory of Speech and Image Information Processing Xi’an710129 China Shaanxi Baocheng Aviation instrument Co. Ltd. Baoji China

ISBN: (纸本)9783030873578

Target detection of aerial images has become a frontier subject of concern in the image processing field. Using existing method to detect and classify large-scale building objects in aerial images, the accuracy is still a little low. This is mainly because the current method does not make full use of the prior information of the target to be detected, so there are too much redundant information in the candidate box. In this paper, our own dataset were built and then utilize the Hough transform to filter out the images that may exist in the sequence image. For images with dense lines or circles, it is possible that there is an artificial building target which will be detected, otherwise it is excluded directly. Besides, this paper exploits significance analysis from the filtered image and then extract the area of interest where the potential target is located. The results of the above-mentioned processing lay a good foundation for the subsequent detection and classification which can help improve the accuracy. © 2021, Springer Nature Switzerland AG.

关键词： Antennas

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Ginsenoside compound-K attenuates OVX-induced osteoporosis via the suppression of RANKL-induced osteoclastogenesis and oxidative stress

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Natural Products and Bioprospecting 2023年第1期13卷 159-170页

作者： Lingli Ding Zhao Gao Siluo Wu Chen Chen Yamei Liu Min Wang Yage Zhang Ling Li Hong Zou Guoping Zhao Shengnan Qin Liangliang Xu Key Laboratory of Orthopaedics and Traumatology Lingnan Medical Research CenterThe First Affiliated Hospital of Guangzhou University of Chinese MedicineGuangzhou University of Chinese MedicineGuangzhouChina Er Sha Sports Training Center of Guangdong Province GuangzhouChina School of Basic Medical Science Guangzhou University of Chinese MedicineGuangzhouChina Engineering Laboratory for Nutrition Shanghai Institute of Nutrition and HealthChinese Academy of SciencesShanghaiChina Master Lab for Innovative Application of Nature Products National Center of Technology Innovation for Synthetic BiologyTianjin Institute of Industrial BiotechnologyChinese Academy of SciencesTianjinChina CAS Key Laboratory of Quantitative Engineering Biology Shenzhen Institute of Synthetic BiologyShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenChina CAS-Key Laboratory of Synthetic Biology CAS Center for Excellence in Molecular Plant SciencesShanghai Institute of Plant Physiology and EcologyChinese Academy of SciencesShanghaiChina Bio-Med Big Data Center Shanghai Institute of Nutrition and HealthChinese Academy of SciencesShanghaiChina State Key Laboratory of Genetic Engineering Department of Microbiology and ImmunologySchool of Life SciencesFudan UniversityShanghaiChina Department of Microbiology The Chinese University of Hong KongHong KongChina Department of Orthopaedics Guangzhou Institute of Traumatic SurgeryGuangzhou Red Cross HospitalMedical CollegeJinan UniversityGuangzhouChina

Osteoporosis(OP),a systemic and chronic bone disease,is distinguished by low bone mass and destruction of bone *** Compound-K(CK),one of the metabolites of ginsenoside Rb1,has anti-aging,anti-inflammatory,anti-cancer,and hypolipidemic *** have demonstrated CK could promote osteogenesis and fracture healing in our previous ***,the contribution of CK to osteoporosis has not been *** the present study,we investigated the effect of CK on osteoclastogenesis and ovariectomy(OVX)-induced *** results showed that CK inhibited receptor activator for nuclear factor-κB ligand(RANKL)-mediated osteoclast differentiation and reactive oxygen species(ROS)activity by inhibiting the phosphorylation of NF-κB p65 and oxidative stress in RAW264.7 *** addition,we also demonstrated that CK could inhibit bone resorption using bone marrow-derived ***,we demonstrated that CK attenuated bone loss by suppressing the activity of osteoclast and alleviating oxidative stress in *** together,these results showed CK could inhibit osteoclastogenesis and prevent OVX-induced bone loss by inhibiting NF-κB signaling pathway.

关键词： Ginsenoside CK NF-κB signaling pathway Osteoporosis Oxidative stress

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Influence of Rotation on Pedestrian Flow Considering Bipedal Features: Modeling Using a Fine Discrete Floor Field Cellular Automaton

SSRN

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SSRN 2022年

作者： Fu, Zhijian Xiong, Xingwen Luo, Lin Yang, Yunjia Feng, Yujing Chen, Hua School of Transportation and Logistics Southwest Jiaotong University Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu China National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Chengdu China Sichuan FAST Fire Safety Assessment Co. Ltd. Chengdu China

Previous studies assume pedestrians rotate with a single axis (often the geometric center of agents in simulation) for simple implementation, which ignores the asymmetry and bipedal features of pedestrian behavior. Therefore, for a higher level of simulation realism, we propose a floor field cellular automaton simulating the rotation with a dual-axis considering bipedal features. Then, we investigated the influence of rotation on the pedestrian flow in three typical scenarios where one could frequently observe the rotation behavior. The findings reveal that the rotation behaviors significantly influence the crowd phenomena of pedestrians, including the travel and flow efficiency, the shape of arching and trajectories of the crowd, and the lane formation. The pedestrians with the dual-axis rotation flow fluently and efficiently when passing through a bottleneck or a crowd: 1) in the case of single-exit room evacuation, the dual-axis rotation improves the efficiency by 5%-150%;2) in the case of unidirectional flow in the L-shaped passage, the improved efficiency by the dual-axis rotation is about 30%;3) in the counterflow, the dual-axis rotation greatly relieves the unrealistic congestion. © 2022, The Authors. All rights reserved.

关键词： Rotation

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BSEN: A bisiamese entity normalization method for biomedicine 3

BSEN: A bisiamese entity normalization method for biomedicin...

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2020 3rd International Conference on Computer Information Science and Artificial Intelligence, CISAI 2020

作者： Peng, Zirong Yu, Qinyong Yang, Hui Wang, Yongli Nanjing University of Science and Technology Nanjing Jiangsu210094 China CETC Big Data Research Institute Co. Ltd Guiyang Guizhou550022 China Big Data Application on Improving Government Governance Capabilities National Engineering Laboratory Guiyang Guizhou550022 China

Normalization of named entities in the field of biomedicine is an important task in biomedical text data mining. Compared with other tasks in biomedical text mining research, there are relatively few researches on entities normalization. In this article, a BiSiamese entity normalization method for biomedicine (BSEN) is proposed. Firstly, the text similarity algorithm is analyzed, and an improved similarity measurement algorithm for biomedical inverse text frequency and cosine (BIC) is proposed. Secondly, the data set is trained in pairs using BiSiamese network and combined with BIC to calculate text similarity. The entity corresponding to the maximum similarity calculated in the normalization knowledge base is the normalized result obtained by the BSEN method. The verification experiments on the verification data set show that the BSEN has achieved better normalization results than the existing methods. © 2020 Institute of Physics Publishing. All rights reserved.

关键词： Inverse problems

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Microscopic Right-of-Way Trading Mechanism for Cooperative Decision-Making: Theories and Preliminary Results

SSRN

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SSRN 2023年

作者： Sun, Zhanbo Qin, Ziye Ma, Rui Huang, Tianyu Gao, Ziyan Ji, Ang School of Transportation and Logistics Southwest Jiaotong University Sichuan Chengdu China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Sichuan Chengdu China Department of Civil and Environmental Engineering The University of Alabama in Huntsville HuntsvilleAL United States School of Air Traffic Management Civil Aviation Flight University of China Sichuan Deyang China SenseTime IAG Shanghai China

In this paper, a microscopic right-of-way trading mechanism (Micro-ROWTM) is developed to encourage cooperative behavior in mixed traffic, which consists of cooperative vehicles (CoVs) and non-cooperative vehicles (NCoVs). Micro-ROWTM encompasses the following functions: (i) detection of traffic conflicts and system-improving opportunities;(ii) participants report their attributes;(iii) right-of-way trade proposed by the system;and (iv) trade settlement and cooperative control. In the experiments, the proposed mechanism is tested using an illustrative ramp-merging example, in which each right-of-way trade proposal is offered to a group of participants comprised of a mainline leader, a mainline follower and a ramp vehicle. Upon the acceptance of a proposal, the mainline leader and/or mainline follower agrees to behave cooperatively (yield) to the ramp vehicle, and receive monetary compensation from the ramp vehicle in return. To help design the trading mechanism, six important properties are introduced and discussed, including (i) strong individual rationality, (ii) system efficiency and group efficiency, (iii) dominant-strategy incentive compatibility, (iv) social welfare maximization, (v) utilitarian envy minimization and (vi) payoff difference minimization. A linear programming-based trading and taxation model which satisfies the above properties is then developed and solved. Using the proposed Micro-ROWTM, when the flow rates is 1000veh/h for both the mainline and ramp traffic, the ramp vehicles can save 6.8% travel time and 27.4% fuel consumption on average, and the mainline vehicles can eventually obtain a positive payoff by compensation. From a system perspective, the ramp-merging section can save 107.5s of travel time and 2450.3g of fuel consumption per hour. © 2023, The Authors. All rights reserved.

关键词： Game theory

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Service Decomposition method for multimodal data exchange scenarios

Service Decomposition method for multimodal data exchange sc...

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Computer Science and Management technology (ICCSMT), International Conference on

作者： Deyou Jiang Lei Huang Hanyu Tian Yujie Xie Xiaoming Li School of Economics and Management Beijing Jiaotong University Beijing China National Engineering Laboratory of Comprehensive Transportation Big Data Application Technology Beijing Jingwei Information Technologies Limited Company Beijing China China Academy of Railway Sciences Institute of Computing Technologies Beijing China

Influenced by the complexity of multimodal data exchange scenarios and their differences in data flow graph construction, the objective basis of existing service decomposition methods is not sufficient, and the granularity of the results is too large and difficult to be decomposed. To address this problem, this paper presents a service decomposition method for multimodal data exchange scenarios. This method reconstructs the differentially constructed data flow diagram by unified rules at the stage of requirement analysis and design, and then completes the fine-grained division of microservices around documents based on service-decomposed rules. The case study shows that the method is more effective than the existing method in the multimodal data exchange scenario.

关键词：

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Managing Evacuation of Mixed Traffic Flow: Fleet Configuration, Lane Allocation, Lane Reversal, and Cross Elimination

SSRN

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SSRN 2022年

作者： Liu, Jialin Jiang, Rui Jia, Bin Liu, Yang Li, Xingang Wang, Ting Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing Jiaotong University Beijing100044 China Department of Industrial Systems Engineering and Management National University of Singapore Singapore117516 Singapore School of Automotive and Transportation Engineering Hefei University of Technology Hefei230009 China

Mixed traffic dynamic evacuation is a challenging task considering heterogeneous populations and traffic congestion. Based on a novel objective function of minimum evacuation network clearance time (ENCT), this paper proposes a mixed traffic dynamic evacuation planning (MTDEP) model, which determines both fleet demand and road supply management strategies, including mixed fleet configuration, lane allocation, lane reversal, and cross-elimination intersections. In this model, a road network is discretized into a multi-size cell network to load mixed traffic, and the holding-back problem of the relaxed CTM is eliminated by adding the penalty term. Then, the proposed model is linearized as a mixed-integer linear program, and a Kriging surrogate-based optimization (KSBO) algorithm is developed. Numerical experiments are conducted on a six-link network and the Sioux-Falls network to validate the effectiveness of our proposed model and solution method. The results show that: (a) the evacuation efficiency of using a mixed fleet is better than that of using a homogeneous fleet in a certain evacuation demand range;(b) while the collaborative management strategies could improve evacuation efficiency, they also take into account the evacuation fairness of the mixed fleet;and (c) the holding-back problem does not affect ENCT but increases the total travel time of all evacuees (ETTT), which should be completely eliminated. © 2022, The Authors. All rights reserved.

关键词： Kriging

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