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Facile synthesis of W-Mo bimetallic oxides with high adsorption properties from secondary resources

Tungsten 2024年第4期6卷 806-820页

作者： Jia-Li Cheng Yang-Si Liu Xiao-Li Xi Zuo-Ren Nie Collaborative Innovation Center of Capital Resource-Recycling Material Technology College of Materials Science and EngineeringBeijing University of TechnologyBeijing100124China National Engineering Laboratory for Industrial Big-Data Application Technology Beijing University of TechnologyBeijing100124China Key Laboratory of Advanced Functional Materials Ministry of EducationBeijing University of TechnologyBeijing100124China

A simple solvothermal method was used to obtain W-Mo bimetallic oxides from W-Mo alloy scrap,and pure metal powders were also used as the raw materials to simulate *** products had a sea urchin-like structure with abundant oxygen vacancies and the products prepared at low temperatures forms a sosoloid resembling orthorhombic W_(0.4)Mo_(0.6)O_(3).The WMo bimetallic oxide prepared at the reaction temperature of 120℃exhibited excellent selective adsorption performance for methylene blue(MB),which the adsorption rate of MB reached 99%in 12 min and the adsorption rate reached 90%after6 adsorption *** the W-Mo molar ratio is 1:3,the maximum adsorption capacity of sample for MB can reach1148 mg·g^(-1).The adsorption process followed the Langmuir and pseudo-second-order models,which is surface-controlled monolayer *** experimental results show the feasibility of preparing W-Mo bimetal oxide products from pure materials and *** process is simple and effective,which offered a potential approach for secondary resource recycling and reusing.

关键词： W-Mo bimetallic oxide Oxygen vacancy Selective adsorption W-Mo alloy scrap Solvothermal

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Jamming-Aided Secure Communication in Ultra-Dense LEO Integrated Satellite-Terrestrial Networks

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China Communications 2023年第7期20卷 43-56页

作者： Yongpeng Shi Jiajia Liu Jiadai Wang Yijie Xun School of Physics and Electronic Information Luoyang Normal CollegeLuoyang 471934China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of CybersecurityNorthwestern Polytechnical UniversityXi’an 710072China

The ultra-dense low earth orbit(LEO)integrated satellite-terrestrial networks(UDLEO-ISTN)can bring lots of benefits in terms of wide coverage,high capacity,and strong ***,the broadcasting and open natures of satellite links also reveal many challenges for transmission security protection,especially for eavesdropping *** to efficiently take advantage of the LEO satellite’s density and ensure the secure communication by leveraging physical layer security with the cooperation of jammers deserves further *** our knowledge,using satellites as jammers in UDLEO-ISTN is still a new problem since existing works mainly focused on this issue only from the aspect of terrestrial *** this end,we study in this paper the cooperative secrecy communication problem in UDLEOISTN by utilizing several satellites to send jamming signal to the *** iterative scheme is proposed as our solution to maximize the system secrecy energy efficiency(SEE)via jointly optimizing transmit power allocation and user *** experiment results verify that our designed optimization scheme can significantly enhance the system SEE and achieve the optimal power allocation and user association strategies.

关键词： ultra-dense LEO satellite integrated satellite-terrestrial network physical layer security cooperative jamming

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Delay recovery model for high-speed trains with compressed train dwell time and running time

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Railway engineering Science 2020年第4期28卷 424-434页

作者： Yafei Hou Chao Wen Ping Huang Liping Fu Chaozhe Jiang National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong UniversityChengdu 610031China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong UniversityChengdu 610031China Intelligent Transport Systems Center Wuhan University of TechnologyWuhan 430070China

Modeling the application of train operation adjustment actions to recover from delays is of great importance to supporting the decision-making of *** this study,the effects of two train operation adjustment actions on train delay recovery were explored using train operation records from scheduled and actual train ***,the modeling data were sorted to extract the possible influencing factors under two typical train operation adjustment actions,namely the compression of the train dwell time at stations and the compression of the train running time in *** regression methods were then employed to determine the importance of the influencing factors corresponding to the train delay recovery time,namely the delay time,the scheduled supplement time,the running interval,the occurrence time,and the place where the delay occurred,under the two train operation adjustment ***,the gradient-boosted regression tree(GBRT)algorithm was applied to construct a delay recovery model to predict the delay recovery effects of the train operation adjustment actions.A comparison of the prediction results of the GBRT model with those of a random forest model confirmed the better performance of the GBRT prediction model.

关键词： High-speed train Delay recovery Train operation adjustment actions Gradient-boosted regression tree

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Distribution Vehicle Routing Optimization Based on 3D Loading 4th

Distribution Vehicle Routing Optimization Based on 3D Loadin...

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4th International Conference on Smart Vehicular technology, Transportation, Communication and applications, VTCA 2021

作者： Luo, Xuan Zhang, Jin Yin, Tingyu Zhu, Hongxing Qiu, Mingyue School of Transportation and Logistics Southwest Jiaotong University Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Comprehensive Transportation Big Data Application Technology Laboratory Chengdu611756 China

ISBN: (纸本)9789811640384

The rapid development of e-commerce leads to increasingly fierce competition in the logistics industry. Cost reduction and efficiency has become the key issue for logistics enterprises to survive. Loading optimization and path optimization are the two core issues in distribution activities, and they are inseparable and related. The joint optimization of the two is more in line with the actual distribution optimization needs. Based on the analysis of the interaction between routing and loading, this paper proposes a multi-objective optimization model with the minimum distribution cost, the minimum number of vehicles and the maximum customer satisfaction as the objectives. A hybrid nesting algorithm based on NSGAII algorithm is designed, in which the packing module is designed by tree search algorithm combined with the deepest and leftmost algorithm. Finally, the real data of China Railway Express Chengdu branch are taken as a case to verify the feasibility of the model and algorithm. Combined with the results of the algorithm, some suggestions are put forward. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Customer satisfaction

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Wind-Bell Index: Towards Ultra-Fast Edge Query for Graph databases 39

Wind-Bell Index: Towards Ultra-Fast Edge Query for Graph Dat...

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39th IEEE International Conference on data engineering, ICDE 2023

作者： Qiu, Rui Ming, Yi Hong, Yisen Li, Haoyu Yang, Tong Peking University School of Computer Science National Engineering Laboratory for Big Data Analysis Technology and Application Beijing China Peking University Academy for Advanced Interdisciplinary Studies China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9798350322279

Graphs are good at presenting relational and structural information, making it powerful in the representation of various data. For the efficient storage and processing of graph-like data, graph databases have been rapidly developed and extensively studied. However, graph databases mostly use adjacency lists as their basic data structure (e.g., Neo4j), which could result in poor performance of edge due to the skewed degree distribution of *** design the Wind-Bell Index to address this problem. Wind-Bell Index is a memory-efficient index data structure, which can be attached to existing graph databases to speed up the edge. We have fully implemented our data structure in Neo4j, the most popular graph database today, and conduct theoretical and experimental analysis to evaluate the performance. Theoretical results prove the high query efficiency of our algorithm. And experimental results show that the average edge query speed is increased by hundreds of times compared with the original query interface of Neo4j. We believe that the excellent performance and scalability of Wind-Bell Index make it suitable for the application in a variety of graph databases. © 2023 IEEE.

关键词： Graph databases

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Continuous and generalized visual odometry based on FLANN_PSC-RANSAC_LSTM

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Journal of Intelligent and Fuzzy Systems 2024年第1-2期47卷 15-28页

作者： Li, Dengao Feng, Ran Wu, Fanming Zhao, Jinhua Zhao, Jumin College of Computer Science and Technology College of Data Science Taiyuan University of Technology Shanxi Taiyuan China College of Electronic Information and Optical Engineering Taiyuan University of Technology Shanxi Taiyuan China Key Laboratory of Big Data Fusion Analysis and Application of Shanxi Province Taiyuan University of Technology Shanxi Taiyuan China Intelligent Perception Engineering Technology Center of Shanxi Taiyuan China

In the field of simultaneous localization and mapping (SLAM), visual odometry (VO) always has great application prospects. In recent years, with the progress in the field of machine learning, methods based on neural networks are constantly being updated and applied. In this paper, we propose a continuous and generalized monocular visual odometry method based on features and neural networks. First, the feature information of adjacent image sequences is extracted by matching and troubleshooting algorithm (FLANN_PSC-RANSAC), then it and the corresponding six-degree-of-freedom information are simultaneously input into the long short-term memory artificial neural network (LSTM) for model construction, which not only ensures the reliability of the mode but also eliminates the influence of illumination on the data. In the real environment test, it has been effectively proved in terms of trajectory recovery accuracy and generalization ability to different environments and different illuminations. © 2024 - IOS Press. All rights reserved.

关键词： Long short-term memory

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A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Capability Evaluation of Manufacturing Enterprises 9th

A Hybrid Intelligent Model SFAHP-ANFIS-PSO for Technical Cap...

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19th International Conference on Advanced data Mining and applications, ADMA 2023

作者： Liu, Tingting Ding, Xuefeng Jiang, Yuming Hu, Dasha College of Computer Science Sichuan University Chengdu610065 China Big Data Analysis and Fusion Application Technology Engineering Laboratory of Sichuan Province Chengdu610065 China

ISBN: (纸本)9783031466731

In the collaborative production environment of manufacturing tasks, the evaluation of enterprise technical capability in advance has a direct impact on the high-performance collaboration between the supplier and the demander of production tasks. In order to solve the problem of efficiency and accuracy in the past evaluation methods, this paper applies the adaptive neuro fuzzy inference system (ANFIS) to the field of enterprise technical capability evaluation for the first time, and proposes an improved hybrid intelligent model SFAHP-ANFIS-PSO based on fuzzy theory. The model takes the four key indexes which have the deepest impact on enterprise technical capability evaluation as the input variables of the model, and the input data are evaluated by ANFIS with high accuracy. Spherical fuzzy analytic hierarchy process (SFAHP) calculated the weight of each evaluation index to preprocess the ANFIS model. Particle swarm optimization algorithm (PSO) continuously optimized the model parameters in the training process, shortened the model training time, improved the evaluation efficiency, and further improved the accuracy of the evaluation results. The experimental results show that the SFAHP-ANFIS-PSO model has high convergence speed and accuracy of results, and can be used to evaluate the technical capability of enterprises with high efficiency and high accuracy. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Analytic hierarchy process

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Visual-semantic network: a visual and semantic enhanced model for gesture recognition

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Visual Intelligence 2023年第1期1卷 1-13页

作者： Wang, Yizhe Cao, Congqi Zhang, Yanning National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science Northwestern Polytechnical University Xi’an 710129 China

Gesture recognition has attracted considerable attention and made encouraging progress in recent years due to its great potential in applications. However, the spatial and temporal modeling in gesture recognition is still a problem to be solved. Specifically, existing works lack efficient temporal modeling and effective spatial attention capacity. To efficiently model temporal information, we first propose a long- and short-term temporal shift module (LS-TSM) that models the long-term and short-term temporal information simultaneously. Then, we propose a spatial attention module (SAM) that focuses on where the change primarily occurs to obtain effective spatial attention capacity. In addition, the semantic relationship among gestures is helpful in gesture recognition. However, this is usually neglected by previous works. Therefore, we propose a label relation module (LRM) that takes full advantage of the relationship among classes based on their labels’ semantic information. To explore the best form of LRM, we design four different semantic reconstruction methods to incorporate the semantic relationship information into the class label’s semantic space. We perform extensive ablation studies to analyze the best settings of each module. The best form of LRM is utilized to build our visual-semantic network (VS Network), which achieves the state-of-the-art performance on two gesture datasets, i.e., EgoGesture and NVGesture. © The Author(s) 2023.

关键词： Gesture recognition Semantic relationship Spatial attention Temporal modeling

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A Method for Identifying the Timeliness of Manufacturing data Based on Weighted Timeliness Graph 9th

A Method for Identifying the Timeliness of Manufacturing Dat...

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19th International Conference on Advanced data Mining and applications, ADMA 2023

作者： Liu, Zehua Ding, Xuefeng Jiang, Yuming Hu, Dasha College of Computer Science Sichuan University Chengdu610065 China Big Data Analysis and Fusion Application Technology Engineering Laboratory of Sichuan Province Chengdu610065 China

ISBN: (纸本)9783031466601

Timeliness is one of the important indicators of data quality. In industrial production processes, a large amount of dependent data is generated, often resulting in unclear timestamps. Therefore, this article combines the conclusion dependency graph into a process dependency graph to determine the identification order of the timeliness of each process data;By constructing a weighted timeliness graph (WTG) and path single flux, a data timeliness identification method that does not completely rely on timestamps is proposed. Finally, a time-effectiveness identification method based on weighted time-effectiveness graph was discussed through an example and 9 dependency rules, and the effectiveness of the method was verified through a set of experiments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： big data

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The impact of COVID-19 on subway passenger flow in Chicago: A study of spatial variation of influencing factors 6

The impact of COVID-19 on subway passenger flow in Chicago: ...

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6th International Conference on Transportation Information and Safety, ICTIS 2021

作者： Zhou, Xinan Lu, Xiaoqian Song, Yicheng Yang, Hongtai Southwest Jiaotong University School of Transportation and Logistics National United Engineering Laboratory of Integrated and Intelligent Transportation National Engineering Laboratory of Integrated Transportation Big Data Application Technology Chengdu China

ISBN: (纸本)9781665497138

At the beginning of 2020, with the rapid spread of COVID-19 around the world, the passenger flow of subway has suffered from a serious impact. Based on the subway passenger flow data in Chicago, this article analyzes the impact of COVID-19 on rail transit passenger flow. ArcGIS is used to visualize the spatial-temporal distribution of the passenger flow of different stations during different time periods. Based on the fluctuation characteristics of passenger flow before and after the outbreak of COVID-19, one of the deep learning methods, the LSTM (Long-Short Term Memory) neural network model, is constructed to predict the passenger flow of each station in the scenario of no virus. The decline of passenger flow is calculated for each station. Stepwise regression model is constructed to determine factors that explain the decline in passenger flow, and significant factors are obtained: the original passenger flow, number of houses and jobs within 800m buffer zone, number of bus stops within 800m buffer zone, whether the station is a transfer station, distance from the station to the city center, and the number of low-income people. The results of the study show that after the outbreak of COVID-19, the passenger flow of the subway in Chicago experience a 'cliff-like' decline in the short term. The passenger flow in most areas dropped by more than 80%, and the passenger flow of some severely impacted stations dropped by more than 90%. Characteristics of the station and built environment factors of different stations influence the decline of passenger flow. © 2021 IEEE.

关键词： COVID-19

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