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Your search keyword '"Xu, Biao"' showing total 905 results
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905 results on '"Xu, Biao"'

7. Efficient Fraud Detection Using Deep Boosting Decision Trees

Author

Xu, Biao, Wang, Yao, Liao, Xiuwu, and Wang, Kaidong

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Applications
Abstract

Fraud detection is to identify, monitor, and prevent potentially fraudulent activities from complex data. The recent development and success in AI, especially machine learning, provides a new data-driven way to deal with fraud. From a methodological point of view, machine learning based fraud detection can be divided into two categories, i.e., conventional methods (decision tree, boosting...) and deep learning, both of which have significant limitations in terms of the lack of representation learning ability for the former and interpretability for the latter. Furthermore, due to the rarity of detected fraud cases, the associated data is usually imbalanced, which seriously degrades the performance of classification algorithms. In this paper, we propose deep boosting decision trees (DBDT), a novel approach for fraud detection based on gradient boosting and neural networks. In order to combine the advantages of both conventional methods and deep learning, we first construct soft decision tree (SDT), a decision tree structured model with neural networks as its nodes, and then ensemble SDTs using the idea of gradient boosting. In this way we embed neural networks into gradient boosting to improve its representation learning capability and meanwhile maintain the interpretability. Furthermore, aiming at the rarity of detected fraud cases, in the model training phase we propose a compositional AUC maximization approach to deal with data imbalances at algorithm level. Extensive experiments on several real-life fraud detection datasets show that DBDT can significantly improve the performance and meanwhile maintain good interpretability. Our code is available at https://github.com/freshmanXB/DBDT., Comment: 34 pages, 8 figures

Published
2023

8. Entanglement filter with Rydberg atoms

Author

Ye, Gen-Sheng, Xu, Biao, Chang, Yue, Shi, Shuai, Shi, Tao, and Li, Lin

Subjects
Physics - Atomic Physics, Quantum Physics
Abstract

Devices capable of deterministically manipulating the photonic entanglement are of paramount importance, since photons are the ideal messengers for quantum information. Here, we report a Rydberg-atom-based entanglement filter that preserves the desired photonic entangled state and deterministically blocks the transmission of the unwanted ones. Photonic entanglement with near-unity fidelity can be extracted from an input state with an arbitrarily low initial fidelity. The protocol is inherently robust, and succeeds both in the Rydberg blockade regime and in the interaction-induced dissipation regime. Such an entanglement filter opens new routes toward scalable photonic quantum information processing with multiple ensembles of Rydberg atoms., Comment: 10 pages for manuscript with 4 figures, 16 pages for Supplementary information with 7 figures and 2 tables

Published
2022
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10. Fungal diversity notes 1611–1716: taxonomic and phylogenetic contributions on fungal genera and species emphasis in south China

Author

Senanayake, Indunil C., Rossi, Walter, Leonardi, Marco, Weir, Alex, McHugh, Mark, Rajeshkumar, Kunhiraman C., Verma, Rajnish K., Karunarathna, Samantha C., Tibpromma, Saowaluck, Ashtekar, Nikhil, Ashtamoorthy, Sreejith K., Raveendran, Sanjay, Kour, Gurmeet, Singh, Aishwarya, De la Peña-Lastra, Saúl, Mateos, Antonio, Kolařík, Miroslav, Antonín, Vladimír, Ševčíková, Hana, Esteve-Raventós, Fernando, Larsson, Ellen, Pancorbo, Fermín, Moreno, Gabriel, Altés, Alberto, Turégano, Yolanda, Du, Tian-Ye, Lu, Li, Li, Qi-Rui, Kang, Ji-Chuan, Gunaseelan, Sugantha, Kezo, Kezhocuyi, Kaliyaperumal, Malarvizhi, Fu, Jizhen, Samarakoon, Milan C., Gafforov, Yusufjon, Teshaboeva, Shakhnoza, Kunjan, Pradeep C., Chamaparambath, Arya, Flakus, Adam, Etayo, Javier, Rodriguez-Flakus, Pamela, Zhurbenko, Mikhail P., de Silva, Nimali I., Tennakoon, Danushka S., Latha, K. P. Deepna, Manimohan, Patinjareveettil, Raj, K. N. Anil, Calabon, Mark S., Ahmadpour, Abdollah, Heidarian, Zeinab, Alavi, Zahra, Alavi, Fatemeh, Ghosta, Youbert, Azizi, Razmig, Luo, Mei, Zhao, Min-Ping, Kularathnage, Nuwan D., Hua, Li, Yang, Yun-Hui, Liao, Chun-Fang, Zhao, Hai-Jun, Lestari, Anis S., Jayasiri, Subashini C., Yu, Feng-Ming, Lei, Lei, Liu, Jian-Wei, Karimi, Omid, Tang, Song-Ming, Sun, Ya-Ru, Wang, Yong, Zeng, Ming, Htet, Zin H., Linaldeddu, Benedetto T., Alves, Artur, Phillips, Alan J. L., Bregant, Carlo, Montecchio, Lucio, De Kesel, André, Hustad, Vincent P., Miller, Andrew N., Fedosova, Anna G., Kučera, Viktor, Raza, Mubashar, Hussain, Muzammil, Chen, Yan-Peng, Thiyagaraja, Vinodhini, Gomdola, Deecksha, Rathnayaka, Achala R., Dissanayake, Asha J., Suwannarach, Nakarin, Hongsanan, Sinang, Maharachchikumbura, Sajeewa S. N., Dissanayake, Lakmali S., Wijayawardene, Nalin N., Phookamsak, Rungtiwa, Lumyong, Saisamorn, Jones, E. B. Gareth, Yapa, Neelamanie, Wanasinghe, Dhanushka N., Xie, Ning, Doilom, Mingkwan, Manawasinghe, Ishara S., Liu, Jian-Kui (Jack), Zhao, Qi, Xu, Biao, Hyde, Kevin D., and Song, Jiage

Published
2023
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11. Investigation of the Impact of Ducted Propellers on AUV Hydrodynamic Performance Based on CFD

Author

GUAN Yingjie, CUI Qingjia, XU Biao, BIAN Yougang, and QIN Xiaohui

Subjects
autonomous underwater vehicle(auv), hydrodynamic model, ducted propeller, computational fluid dynamics(cfd), Control engineering systems. Automatic machinery (General), TJ212-225, Technology
Abstract

Autonomous underwater vehicle (AUV) equipped with ducted propellers exhibit increased maneuverability. However, ducting also influences the AUV's dynamic characteristics. Accordingly, it is crucial to analyze the effect that ducted propellers exert on an AUV's hydrodynamic performance. This paper utilizes computational fluid dynamics (CFD) to study this impact. Firstly, two AUV models with identical geometry except for the presence of ducted propellers were constructed using 3D software. Subsequently, two sets of overlapping grids for the CFD hydrodynamic analysis were created, each for one of the AUVs. Hydrodynamic coefficients for both models were obtained by calculating their translational and rotational motions, and differences between these coefficients were analyzed to evaluate the ducted propellers' effect. The computational results reveal that ducted propellers augment the inertial hydrodynamic forces in surge motion while reducing those in sway, heaven, pitch, and yaw motions. In addition, the presence of ducted propellers heightens the viscous hydrodynamic forces during translational motion and diminishes them during rotational motion. The ducted propeller further impacts the AUV's streamlined shape, thereby altering the AUV's inertial and viscous hydrodynamic characteristics. Therefore, when designing AUV with ducted propellers, it is critical to consider the effect of ducting on the AUV.

Published
2023
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12. Three-dimensional Underwater Dynamic Target Tracking Based on Adaptive Interactive Multi-model Algorithm

Author

QIN Hongmao, YE Hongwei, CUI Qingjia, XU Biao, and HU Manjiang

Subjects
underwater target tracking, unscented kalman filter(ukf), interacting multiple model(imm), state prediction, transition probability matrix, Control engineering systems. Automatic machinery (General), TJ212-225, Technology
Abstract

Dynamic target tracking is a crucial technique for autonomous underwater vehicles (AUV), enabling key operations such as target detection and reconnaissance. Standard approaches for tracking maneuvering targets often involve the interacting multiple model (IMM) algorithm which integrates the constant velocity (CV) model and the coordinated turn (CT) model. However, these models traditionally utilize fixed transition probabilities and turn rates based on prior information, potentially leading to imprecise state estimations. In response to this, the paper introduces an adaptive parallel IMM (APIMM) based on current adaptive IMM algorithms. This method adaptively adjusts transition probabilities and pairs with the unscented Kalman filter (UKF) algorithm for state prediction of maneuvering targets in a 3D underwater environment. The enhanced algorithm chooses from a model set that encompasses the CV model, the 3D fixed center constant speed and turning rate model (CSCTR) with an adaptive turn rate, and the current statistical (CS) model. Simulation outcomes have demonstrated that this algorithm utilizes posterior information more effectively, possesses an accelerated model switching speed, and improves the prediction accuracy of the underwater dynamic target's state in three-dimensional space by approximately 15%.

Published
2023
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13. Scheme Design and Key Technology Application of Multi-joint Unmanned Underwater Vehicle

Author

HAN Tao, HU Zhiqiang, CUI Qingjia, QING Xiaohui, and XU Biao

Subjects
multi-joint unmanned underwater vehicle, functional carrier, basic carrier, jet manipulation, vector propulsion, experimental verification, Control engineering systems. Automatic machinery (General), TJ212-225, Technology
Abstract

Concerning the challenges of limited operational capabilities of autonomous underwater vehicles and the impaired passability caused by the externally mounted propellers on the existing chained multi-body underwater vehicles, this paper presents an overall design scheme for a multi-joint unmanned underwater vehicle composed of a functional carrier and a basic carrier. Initially, the structural arrangements of the functional carrier and basic carrier are introduced. Subsequently, a comprehensive exploration of the key technological principles incorporated in the scheme, such as jet manipulation, vector propulsion, folding antennas, among others is conducted. Lastly, a physical prototype of the basic carrier for the multi-joint unmanned underwater vehicle is developed, followed by successive trials in lake and sea environments. In the directional variable depth navigation tests, the depth error was no more than ±0.1 m, and the heading error was not exceeding ±1°. These experiment results validate the sailing capabilities of the basic carrier of the multi-joint unmanned underwater vehicle, thereby confirming the feasibility of the proposed design scheme for a multi-joint unmanned underwater vehicle in this paper.

Published
2023
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40. MOSI APP - A Motion Cueing Application to Mitigate Car Sickness While Performing Non-driving Task

Author

Li, Daofei, Xu, Biao, Chen, Linhui, Tang, Binbin, Yu, Tingzhe, Zhou, Keyuan, Qie, Nan, Shi, Yilei, Lu, Cheng, Zhang, Haimo, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, and Krömker, Heidi, editor

Published
2023
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42. Hypersonic Vehicle Tracking Algorithm Based on Virtual Radar Constructed by Artificial Intelligence

Author

Xu, Biao, Zhu, Xuxin, Li, Shuang, Zhang, Jinpeng, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Yan, Liang, editor, and Deng, Yimin, editor

Published
2023
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50. Magnifying image-enhanced endoscopy–only mode boosted early cancer diagnostic efficiency: a multicenter randomized controlled trial

Author

Jiang, Ai-Rui, Wen, Li-Ming, Ding, Jian-Wei, Zou, Rui-Zheng, Nie, Xu-Biao, Lin, Hui, Chen, Jing, Zhang, Wei-Sen, Dan, Liang-Ying, Zhu, Yu-Xia, Ren, Chun-Mei, Wu, Ying-Yang, Sheng, Lin-Lin, Chen, Ding-Rong, Liao, Guo-Bin, Zhao, Hai-Yan, Li, Jian-Jun, Zuo, Ying, Chen, Jie, Bai, Jian-Ying, Xu, Liang-Bi, and Yu, Shuang

Published
2023
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