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Lecture Notes in Artificial Intelligence 13031
Subseries of Lecture Notes in Computer Science
Series Editors
Randy GoebelUniversity of Alberta, Edmonton, Canada
Yuzuru TanakaHokkaido University, Sapporo, Japan
Wolfgang WahlsterDFKI and Saarland University, Saarbrücken, Germany
Founding Editor
Jörg SiekmannDFKI and Saarland University, Saarbrücken, Germany
More information about this subseries at http://www.springer.com/series/1244
Duc Nghia Pham • Thanaruk Theeramunkong •
Guido Governatori • Fenrong Liu (Eds.)
PRICAI 2021:Trends inArtificial Intelligence18th Pacific RimInternational Conference on Artificial Intelligence, PRICAI 2021Hanoi, Vietnam, November 8–12, 2021Proceedings, Part I
123
EditorsDuc Nghia PhamMIMOS BerhadKuala Lumpur, Malaysia
Thanaruk TheeramunkongSirindhorn International Institute of Scienceand TechnologyThammasat UniversityMueang Pathum Thani, ThailandGuido Governatori
Data61CSIROBrisbane, QLD, Australia
Fenrong LiuDepartment of PhilosophyTsinghua UniversityBeijing, China
ISSN 0302-9743 ISSN 1611-3349 (electronic)Lecture Notes in Artificial IntelligenceISBN 978-3-030-89187-9 ISBN 978-3-030-89188-6 (eBook)https://doi.org/10.1007/978-3-030-89188-6
LNCS Sublibrary: SL7 – Artificial Intelligence
© Springer Nature Switzerland AG 2021, corrected publication 2022This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of thematerial is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,broadcasting, reproduction on microfilms or in any other physical way, and transmission or informationstorage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology nowknown or hereafter developed.The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoes not imply, even in the absence of a specific statement, that such names are exempt from the relevantprotective laws and regulations and therefore free for general use.The publisher, the authors and the editors are safe to assume that the advice and information in this book arebelieved to be true and accurate at the date of publication. Neither the publisher nor the authors or the editorsgive a warranty, expressed or implied, with respect to the material contained herein or for any errors oromissions that may have been made. The publisher remains neutral with regard to jurisdictional claims inpublished maps and institutional affiliations.
This Springer imprint is published by the registered company Springer Nature Switzerland AGThe registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
These three-volume proceedings contain the papers presented at the 18th Pacific RimInternational Conference on Artificial Intelligence (PRICAI 2021) held virtually duringNovember 8–12, 2021, in Hanoi, Vietnam.
PRICAI, which was inaugurated in Tokyo in 1990, started out as a biennial inter-national conference concentrating on artificial intelligence (AI) theories, technologies,and applications in the areas of social and economic importance for Pacific Rimcountries. It provides a common forum for researchers and practitioners in variousbranches of AI to exchange new ideas and share experience and expertise. Since then,the conference has grown, both in participation and scope, to be a premier internationalAI event for all major Pacific Rim nations as well as countries from all around theworld. In 2018, the PRICAI Steering Committee decided to hold PRICAI on an annualbasis starting from 2019.
This year, we received an overwhelming number of 382 submissions to both theMain track (365 submissions) and the Industry special track (17 submissions). Thisnumber was impressive considering that for the first time PRICAI was being heldvirtually during a global pandemic situation. All submissions were reviewed andevaluated with the same highest quality standard through a double-blind review pro-cess. Each paper received at least two reviews, in most cases three, and in some casesup to four. During the review process, discussions among the Program Committee(PC) members in charge were carried out before recommendations were made, andwhen necessary, additional reviews were sourced. Finally, the conference and programco-chairs read the reviews and comments and made a final calibration for differencesamong individual reviewer scores in light of the overall decisions. The entire ProgramCommittee (including PC members, external reviewers, and co-chairs) expendedtremendous effort to ensure fairness and consistency in the paper selection process.Eventually, we accepted 92 regular papers and 28 short papers for oral presentation.This gives a regular paper acceptance rate of 24.08% and an overall acceptance rate of31.41%.
The technical program consisted of three tutorials and the main conference program.The three tutorials covered hot topics in AI from “Collaborative Learning and Opti-mization” and “Mechanism Design Powered by Social Interactions” to “TowardsHyperdemocary: AI-enabled Crowd Consensus Making and Its Real-World SocietalExperiments”. All regular and short papers were orally presented over four days inparallel and in topical program sessions. We were honored to have keynote presen-tations by four distinguished researchers in the field of AI whose contributions havecrossed discipline boundaries: Mohammad Bennamoun (University of WesternAustralia, Australia), Johan van Benthem (University of Amsterdam, The Netherlands;Stanford University, USA; and Tsinghua University, China), Virginia Dignum (UmeåUniversity, Sweden), and Yutaka Matsuo (University of Tokyo, Japan). We weregrateful to them for sharing their insights on their latest research with us.
The success of PRICAI 2021 would not be possible without the effort and support ofnumerous people from all over the world. First, we would like to thank the authors, PCmembers, and external reviewers for their time and efforts spent in making PRICAI2021 a successful and enjoyable conference. We are also thankful to various fellowmembers of the conference committee, without whose support and hard work PRICAI2021 could not have been successful:
– Advisory Board: Hideyuki Nakashima, Abdul Sattar, and Dickson Lukose– Industry Chair: Shiyou Qian– Local/Virtual Organizing Chairs: Sankalp Khanna and Adila Alfa Krisnadhi– Tutorial Chair: Guandong Xu– Web and Publicity Chair: Md Khaled Ben Islam– Workshop Chair: Dengji Zhao
We gratefully acknowledge the organizational support of several institutionsincluding Data61/CSIRO (Australia), Tsinghua University (China), MIMOS Berhad(Malaysia), Thammasat University (Thailand), and Griffith University (Australia).
Finally, we thank Springer, Ronan Nugent (Editorial Director, Computer ScienceProceedings), and Anna Kramer (Assistant Editor, Computer Science Proceedings) fortheir assistance in publishing the PRICAI 2021 proceedings as three volumes of itsLecture Notes in Artificial Intelligence series.
November 2021 Duc Nghia PhamThanaruk Theeramunkong
Guido GovernatoriFenrong Liu
vi Preface
Organization
PRICAI Steering Committee
Steering Committee
Quan Bai University of Tasmania, AustraliaTru Hoang Cao The University of Texas Health Science Center
at Houston, USAXin Geng Southeast University, ChinaGuido Governatori Data61, CSIRO, AustraliaTakayuki Ito Nagoya Institute of Technology, JapanByeong-Ho Kang University of Tasmania, AustraliaM. G. M. Khan University of the South Pacific, FijiSankalp Khanna Australian e-Health Research Centre, CSIRO, AustraliaDickson Lukose Monash University, AustraliaHideyuki Nakashima Sapporo City University, JapanAbhaya Nayak Macquarie University, AustraliaSeong Bae Park Kyung Hee University, South KoreaDuc Nghia Pham MIMOS Berhad, MalaysiaAbdul Sattar Griffith University, AustraliaAlok Sharma RIKEN, Japan, and University of the South Pacific, FijiThanaruk Theeramunkong Thammasat University, ThailandZhi-Hua Zhou Nanjing University, China
Honorary Members
Randy Goebel University of Alberta, CanadaTu-Bao Ho Japan Advanced Institute of Science and Technology,
JapanMitsuru Ishizuka University of Tokyo, JapanHiroshi Motoda Osaka University, JapanGeoff Webb Monash University, AustraliaAlbert Yeap Auckland University of Technology, New ZealandByoung-Tak Zhang Seoul National University, South KoreaChengqi Zhang University of Technology Sydney, Australia
Conference Organizing Committee
General Chairs
Guido Governatori Data61, CSIRO, AustraliaFenrong Liu Tsinghua University, China
Program Chairs
Duc Nghia Pham MIMOS Berhad, MalaysiaThanaruk Theeramunkong Thammasat University, Thailand
Local/Virtual Organizing Chairs
Sankalp Khanna Australian e-Health Research Centre, CSIRO, AustraliaAdila Alfa Krisnadhi University of Indonesia, Indonesia
Workshop Chair
Dengji Zhao ShanghaiTech University, China
Tutorial Chair
Guandong Xu University of Technology Sydney, Australia
Industry Chair
Shiyou Qian Shanghai Jiao Tong University, China
Web and Publicity Chair
Md Khaled Ben Islam Griffith University, Australia
Advisory Board
Hideyuki Nakashima Sapporo City University, JapanAbdul Sattar Griffith University, AustraliaDickson Lukose Monash University, Australia
Program Committee
Eriko Aiba The University of Electro-Communications, JapanPatricia Anthony Lincoln University, New ZealandChutiporn Anutariya Asian Institute of Technology, ThailandMohammad Arshi Saloot MIMOS Berhad, MalaysiaYun Bai University of Western Sydney, AustraliaChutima Beokhaimook Rangsit University, ThailandAteet Bhalla Independent Technology Consultant, IndiaChih How Bong Universiti Malaysia Sarawak, MalaysiaPoonpong Boonbrahm Walailak University, ThailandAida Brankovic Australian e-Health Research Centre, CSIRO, AustraliaXiongcai Cai University of New South Wales, AustraliaTru Cao University of Texas Health Science Center at Houston,
USAHutchatai Chanlekha Kasetsart University, ThailandSapa Chanyachatchawan National Electronics and Computer Technology Center,
ThailandSiqi Chen Tianjin University, China
viii Organization
Songcan Chen Nanjing University of Aeronautics and Astronautics,China
Wu Chen Southwest University, ChinaYingke Chen Sichuan University, ChinaWai Khuen Cheng Universiti Tunku Abdul Rahman, MalaysiaBoonthida Chiraratanasopha Yala Rajabhat University, ThailandPhatthanaphong
ChomphuwisetMahasarakham University, Thailand
Dan Corbett Optimodal Technologies, USACélia Da Costa Pereira Université Côte d’Azur, FranceJirapun Daengdej Assumption University, ThailandHoa Khanh Dam University of Wollongong, AustraliaXuan-Hong Dang IBM Watson Research, USAAbdollah Dehzangi Rutgers University, USASang Dinh Hanoi University of Science and Technology, VietnamClare Dixon University of Manchester, UKShyamala Doraisamy University Putra Malaysia, MalaysiaNuttanart Facundes King Mongkut’s University of Technology Thonburi,
ThailandEduardo Fermé Universidade da Madeira, PortugalSomchart Fugkeaw Thammasat University, ThailandKatsuhide Fujita Tokyo University of Agriculture and Technology,
JapanNaoki Fukuta Shizuoka University, JapanMarcus Gallagher University of Queensland, AustraliaDragan Gamberger Rudjer Boskovic Institute, CroatiaWei Gao Nanjing University, ChinaXiaoying Gao Victoria University of Wellington, New ZealandXin Geng Southeast University, ChinaManolis Gergatsoulis Ionian University, GreeceGuido Governatori Data61, CSIRO, AustraliaAlban Grastien Australian National University, AustraliaCharles Gretton Australian National University, AustraliaFikret Gurgen Bogazici University, TurkeyPeter Haddawy Mahidol University, ThailandChoochart Haruechaiyasak National Electronics and Computer Technology Center,
ThailandHamed Hassanzadeh Australian e-Health Research Centre, CSIRO, AustraliaTessai Hayama Nagaoka University of Technology, JapanJuhua Hu University of Washington, USAXiaodi Huang Charles Sturt University, AustraliaVan Nam Huynh Japan Advanced Institute of Science and Technology,
JapanNorisma Idris University of Malaya, MalaysiaMitsuru Ikeda Japan Advanced Institute of Science and Technology,
Japan
Organization ix
Masashi Inoue Tohoku Institute of Technology, JapanTakayuki Ito Kyoto University, JapanSanjay Jain National University of Singapore, SingaporeGuifei Jiang Nankai University, ChinaYichuan Jiang Southeast University, ChinaNattagit Jiteurtragool Digital Government Development Agency, ThailandHideaki Kanai Japan Advanced Institute of Science and Technology,
JapanRyo Kanamori Nagoya University, JapanNatsuda Kaothanthong Thammasat University, ThailandJessada Karnjana National Electronics and Computer Technology Center,
ThailandC. Maria Keet University of Cape Town, South AfricaGabriele Kern-Isberner Technische Universitaet Dortmund, GermanySankalp Khanna Australian e-Health Research Centre, CSIRO, AustraliaNichnan
KittiphattanabawonWalailak University, Thailand
Frank Klawonn Ostfalia University, GermanySébastien Konieczny CRIL-CNRS, FranceKrit Kosawat National Electronics and Computer Technology Center,
ThailandAlfred Krzywicki University of New South Wales, AustraliaKun Kuang Zhejiang University, ChinaYoung-Bin Kwon Chung-Ang University, South KoreaWeng Kin Lai Tunku Abdul Rahman University College, MalaysiaHo-Pun Lam Data61, CSIRO, AustraliaNasith Laosen Phuket Rajabhat University, ThailandVincent CS Lee Monash University, AustraliaRoberto Legaspi KDDI Research Inc., JapanGang Li Deakin University, AustraliaGuangliang Li Ocean University of China, ChinaTianrui Li Southwest Jiaotong University, ChinaChanjuan Liu Dalian University of Technology, ChinaFenrong Liu Tsinghua University, ChinaMichael Maher Reasoning Research Institute, AustraliaXinjun Mao National University of Defense Technology, ChinaEric Martin University of New South Wales, AustraliaMaria Vanina Martinez Instituto de Ciencias de la Computación, ArgentinaSanparith Marukatat National Electronics and Computer Technology Center,
ThailandMichael Mayo University of Waikato, New ZealandBrendan McCane University of Otago, New ZealandRiichiro Mizoguchi Japan Advanced Institute of Science and Technology,
JapanNor Liyana Mohd Shuib University of Malaya, MalaysiaM. A. Hakim Newton Griffith University, Australia
x Organization
Hung Duy Nguyen Thammasat University, ThailandPhi Le Nguyen Hanoi University of Science and Technology, VietnamKouzou Ohara Aoyama Gakuin University, JapanFrancesco Olivieri Griffith University, AustraliaMehmet Orgun Macquarie University, AustraliaNoriko Otani Tokyo City University, JapanMaurice Pagnucco University of New South Wales, AustraliaLaurent Perrussel IRIT - Universite de Toulouse, FranceBernhard Pfahringer University of Waikato, New ZealandDuc Nghia Pham MIMOS Berhad, MalaysiaJantima Polpinij Mahasarakham University, ThailandThadpong
PongthawornkamolKasikorn Business-Technology Group, Thailand
Yuhua Qian Shanxi University, ChinaJoel Quinqueton LIRMM, FranceTeeradaj Racharak Japan Advanced Institute of Science and Technology,
JapanFenghui Ren University of Wollongong, AustraliaMark Reynolds University of Western Australia, AustraliaJandson S. Ribeiro University of Koblenz-Landau, GermanyKazumi Saito University of Shizuoka, JapanChiaki Sakama Wakayama University, JapanKen Satoh National Institute of Informatics and Sokendai, JapanAbdul Sattar Griffith University, AustraliaNicolas Schwind National Institute of Advanced Industrial Science
and Technology, JapanNazha Selmaoui-Folcher University of New Caledonia, FranceLin Shang Nanjing University, ChinaAlok Sharma RIKEN, JapanChenwei Shi Tsinghua University, ChinaZhenwei Shi Beihang University, ChinaMikifumi Shikida Kochi University of Technology, JapanSoo-Yong Shin Sungkyunkwan University, South KoreaYanfeng Shu CSIRO, AustraliaTony Smith University of Waikato, New ZealandChattrakul Sombattheera Mahasarakham University, ThailandInsu Song James Cook University, AustraliaSafeeullah Soomro Virginia State University, USATasanawan Soonklang Silpakorn University, ThailandMarkus Stumptner University of South Australia, AustraliaMerlin Teodosia Suarez De La Salle University, PhilippinesXin Sun Catholic University of Lublin, PolandBoontawee Suntisrivaraporn DTAC, ThailandThepchai Supnithi National Electronics and Computer Technology Center,
ThailandDavid Taniar Monash University, Australia
Organization xi
Thanaruk Theeramunkong Thammasat University, ThailandMichael Thielscher University of New South Wales, AustraliaSatoshi Tojo Japan Advanced Institute of Science and Technology,
JapanShikui Tu Shanghai Jiao Tong University, ChinaMiroslav Velev Aries Design Automation, USAMuriel Visani Hanoi University of Science and Technology, Vietnam
and La Rochelle University, FranceToby Walsh University of New South Wales, AustraliaXiao Wang Beijing University of Posts and Telecommunications,
ChinaPaul Weng Shanghai Jiao Tong University, ChinaPeter Whigham University of Otago, New ZealandWayne Wobcke University of New South Wales, AustraliaSartra Wongthanavasu Khon Kaen University, ThailandBrendon J. Woodford University of Otago, New ZealandKaibo Xie University of Amsterdam, The NetherlandsMing Xu Xi’an Jiaotong-Liverpool University, ChinaShuxiang Xu University of Tasmania, AustraliaHui Xue Southeast University, ChinaMing Yang Nanjing Normal University, ChinaRoland Yap National University of Singapore, SingaporeKenichi Yoshida University of Tsukuba, JapanTakaya Yuizono Japan Advanced Institute of Science and Technology,
JapanChengqi Zhang University of Technology Sydney, AustraliaDu Zhang California State University, USAMin-Ling Zhang Southeast University, ChinaShichao Zhang Central South University, ChinaWen Zhang Beijing University of Technology, ChinaYu Zhang Southern University of Science and Technology, ChinaZhao Zhang Hefei University of Technology, ChinaZili Zhang Deakin University, AustraliaYanchang Zhao Data61, CSIRO, AustraliaShuigeng Zhou Fudan University, ChinaXingquan Zhu Florida Atlantic University, USA
Additional Reviewers
Aitchison, MatthewAkhtar, NaveedAlgar, ShannonAlmeida, YuriBoudou, JosephBurie, Jean-ChristopheChandra, Abel
Cheng, CharibethDamigos, MatthewDong, HuanfangDu Preez-Wilkinson, NathanielEffendy, SuhendryEng, Bah TeeFeng, Xuening
xii Organization
Fu, KerenGao, YiGeng, ChuanxingHabault, GuillaumeHang, Jun-YiHe, ZhengqiHoang, AnhHuynh, DuInventado, Paul SalvadorJan, ZohaibJannai, TokotokoJia, BinbinJiang, ZhaohuiKalogeros, EleftheriosKarim, AbdulKumar, ShiuLai, YongLaosen, KanjanaLee, Nung KionLee, ZhiyiLi, WeikaiLiang, YanyanLiu, JiexiLiu, XiaxueLiu, YanliLuke, Jing YuanMahdi, GhulamMayer, WolfgangMendonça, FábioMing, ZuhengMittelmann, MunyqueNguyen, Duy HungNguyen, Hong-HuyNguyen, Mau ToanNguyen, Minh HieuNguyen, Minh LeNguyen, Trung ThanhNikafshan Rad, HimaOkubo, YoshiakiOng, EthelOstertag, Cécilia
Phiboonbanakit, ThananutPhua, Yin JunPongpinigpinyo, SuneePreto, SandroQian, JunqiQiao, YukaiRiahi, VahidRodrigues, PedroRosenberg, ManouSa-Ngamuang, ChaitawatScherrer, RomaneSelway, MattSharma, RoneshSong, GeSu Yin, MyatSubash, AdityaTan, HongweiTang, JiahuaTeh, Chee SiongTettamanzi, AndreaTian, QingTran, VuVo, Duc VinhWang, Deng-BaoWang, KaixiangWang, ShuwenWang, YuchenWang, YunyunWilhelm, MarcoWu, LinzeXiangru, YuXing, GuanyuXue, HaoYan, WenzhuYang, WanqiYang, YikunYi, HuangYin, ZeYu, GuanbaoZhang, JianyiZhang, Jiaqiang
Organization xiii
Contents – Part I
AI Foundations/Decision Theory
Designing Bounded Min-Knapsack Bandits Algorithm for SustainableDemand Response. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Akansha Singh, P. Meghana Reddy, Shweta Jain, and Sujit Gujar
Designing Refund Bonus Schemes for Provision Point Mechanismin Civic Crowdfunding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Sankarshan Damle, Moin Hussain Moti, Praphul Chandra,and Sujit Gujar
Federated Learning for Non-IID Data: From Theory to Algorithm. . . . . . . . . 33Bojian Wei, Jian Li, Yong Liu, and Weiping Wang
Fixed-Price Diffusion Mechanism Design. . . . . . . . . . . . . . . . . . . . . . . . . . 49Tianyi Zhang, Dengji Zhao, Wen Zhang, and Xuming He
Multiclass Classification Using Dilute Bandit Feedback . . . . . . . . . . . . . . . . 63Gaurav Batra and Naresh Manwani
A Study of Misinformation Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Constantinos Varsos, Giorgos Flouris, Marina Bitsaki,and Michail Fasoulakis
Influence-Driven Explanations for Bayesian Network Classifiers . . . . . . . . . . 88Emanuele Albini, Antonio Rago, Pietro Baroni, and Francesca Toni
Public Project with Minimum Expected Release Delay . . . . . . . . . . . . . . . . 101Guanhua Wang and Mingyu Guo
Strategy Proof Mechanisms for Facility Location at Limited Locations . . . . . 113Toby Walsh
Applications of AI
A Consistency Enhanced Deep Lmser Network for Face Sketch Synthesis . . . 127Qingjie Sheng, Shikui Tu, and Lei Xu
A Cost-Efficient Framework for Scene Text Detection in the Wild . . . . . . . . 139Gangyan Zeng, Yuan Zhang, Yu Zhou, and Xiaomeng Yang
A Dueling-DDPG Architecture for Mobile Robots Path Planning Basedon Laser Range Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
Panpan Zhao, Jinfang Zheng, Qinglin Zhou, Chen Lyu, and Lei Lyu
A Fully Dynamic Context Guided Reasoning and Reconsidering Networkfor Video Captioning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
Xia Feng, Xinyu He, Rui Huang, and Caihua Liu
Adaptive Prediction of Hip Joint Center from X-ray Images UsingGeneralized Regularized Extreme Learning Machine and GlobalizedBounded Nelder-Mead Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
Fuchang Han, Shenghui Liao, Yiyong Jiang, Shu Liu, Yuqian Zhao,and Xiantao Shen
Adversarial Training for Image Captioning Incorporating RelationAttention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 197
Tianyu Chen, Zhixin Li, Canlong Zhang, and Huifang Ma
Element Re-identification in Crowdtesting . . . . . . . . . . . . . . . . . . . . . . . . . 212Li Zhang and Wei-Tek Tsai
Flame and Smoke Detection Algorithm for UAV Basedon Improved YOLOv4-Tiny . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
Ruinan Wu, Changchun Hua, Weili Ding, Yifan Wang, and Yubao Wang
Improving Protein Backbone Angle Prediction Using Hidden MarkovModels in Deep Learning. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
Fereshteh Mataeimoghadam, M. A. Hakim Newton, Rianon Zaman,and Abdul Sattar
Magic Mirror Stealth: Interactive Automatic Picture Editing System . . . . . . . 252MengDi Zhou, BoHeng Hu, and Si Liu
Off-TANet: A Lightweight Neural Micro-expression Recognizer withOptical Flow Features and Integrated Attention Mechanism . . . . . . . . . . . . . 266
Jiahao Zhang, Feng Liu, and Aimin Zhou
Pulmonary Nodule Classification of CT Images with Attribute Self-guidedGraph Convolutional V-Shape Networks . . . . . . . . . . . . . . . . . . . . . . . . . . 280
Xiangbo Zhang, Kun Wang, Xiaohong Zhang, and Sheng Huang
Semantic Structural and Occlusive Feature Fusionfor Pedestrian Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293
Hui Wang, Yu Zhang, Hongchang Ke, Ning Wei, and Zhongyu Xu
VTLayout: Fusion of Visual and Text Features for DocumentLayout Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308
Shoubin Li, Xuyan Ma, Shuaiqun Pan, Jun Hu, Lin Shi, and Qing Wang
xvi Contents – Part I
An Initial Study of Machine Learning Underspecification Using FeatureAttribution Explainable AI Algorithms: A COVID-19 Virus TransmissionCase Study. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
James Hinns, Xiuyi Fan, Siyuan Liu, Veera Raghava Reddy Kovvuri,Mehmet Orcun Yalcin, and Markus Roggenbach
Generation of Environment-Irrelevant Adversarial DigitalCamouflage Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336
Xu Teng, Hui Zhang, Bo Li, Chunming Yang, and Xujian Zhao
Magnitude-Weighted Mean-Shift Clustering with Leave-One-OutBandwidth Estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347
Yuki Yamagishi, Kazumi Saito, Kazuro Hirahara, and Naonori Ueda
Pervasive Monitoring of Gastrointestinal Health of Newborn Babies . . . . . . . 359Insu Song, Yi Huang, Tieh Hee Hai Guan Koh,and Victor Samuel Rajadurai
Price and Time Optimization for Utility-Aware Taxi Dispatching . . . . . . . . . 370Yuya Hikima, Masahiro Kohjima, Yasunori Akagi, Takeshi Kurashima,and Hiroyuki Toda
VAN: Voting and Attention Based Network for Unsupervised MedicalImage Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 382
Zhiang Zu, Guixu Zhang, Yaxin Peng, Zhen Ye, and Chaomin Shen
Data Mining and Knowledge Discovery
MGEoT: A Multi-grained Ensemble Method for TimeSeries Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 397
Ziyi Wang, Yujie Zhou, Chun Li, Lin Shang, and Bing Xue
Mining Skyline Frequent-Utility Itemsets with Utility Filtering . . . . . . . . . . . 411Wei Song, Chuanlong Zheng, and Philippe Fournier-Viger
Network Embedding with Topology-Aware Textual Representations . . . . . . . 425Jiaxing Chen, Zenan Xu, and Qinliang Su
Online Discriminative Semantic-Preserving Hashing for Large-ScaleCross-Modal Retrieval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440
Jinhan Yi, Yi He, and Xin Liu
Empirical Study on the Impact of Different Sets of Parameters of GradientBoosting Algorithms for Time-Series Forecasting with LightGBM . . . . . . . . 454
Filipa S. Barros, Vitor Cerqueira, and Carlos Soares
Contents – Part I xvii
Evolutionary Computation/Optimisation
A Two-Stage Efficient Evolutionary Neural Architecture Search Methodfor Image Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 469
Gonglin Yuan, Bing Xue, and Mengjie Zhang
Adaptive Relaxations for Multistage Robust Optimization . . . . . . . . . . . . . . 485Michael Hartisch
ALGNN: Auto-Designed Lightweight Graph Neural Network. . . . . . . . . . . . 500Rongshen Cai, Qian Tao, Yufei Tang, and Min Shi
Automatic Graph Learning with Evolutionary Algorithms:An Experimental Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513
Chenyang Bu, Yi Lu, and Fei Liu
Dendritic Cell Algorithm with Group Particle Swarm Optimizationfor Input Signal Generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527
Dan Zhang and Yiwen Liang
Knowledge Representation and Reasoning
Building Trust for Belief Revision. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 543Aaron Hunter
Correcting Large Knowledge Bases Using Guided Inductive LogicLearning Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556
Yan Wu, Zili Zhang, and Guodong Wang
High-Quality Noise Detection for Knowledge Graph Embeddingwith Rule-Based Triple Confidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 572
Yan Hong, Chenyang Bu, and Xindong Wu
Multi-agent Epistemic Planning with Inconsistent Beliefs, Trust and Lies . . . . 586Francesco Fabiano, Alessandro Burigana, Agostino Dovier,Enrico Pontelli, and Tran Cao Son
Correction to: Federated Learning for Non-IID Data: From Theoryto Algorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C1
Bojian Wei, Jian Li, Yong Liu, and Weiping Wang
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599
xviii Contents – Part I
Contents – Part II
Natural Language Processing
A Calibration Method for Sentiment Time Series by Deep Clustering . . . . . . 3Jingyi Wu, Baopu Qiu, and Lin Shang
A Weak Supervision Approach with Adversarial Training for NamedEntity Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Jianxuan Shao, Chenyang Bu, Shengwei Ji, and Xindong Wu
An Attention-Based Approach to Accelerating Sequence GenerativeAdversarial Nets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Minglei Gao, Sai Zhang, Xiaowang Zhang, and Zhiyong Feng
Autoregressive Pre-training Model-Assisted Low-Resource NeuralMachine Translation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
Nier Wu, Hongxu Hou, Yatu Ji, and Wei Zheng
Combining Improvements for Exploiting Dependency Trees in NeuralSemantic Parsing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
Defeng Xie, Jianmin Ji, Jiafei Xu, and Ran Ji
Deep Semantic Fusion Representation Based on Special Mechanismof Information Transmission for Joint Entity-Relation Extraction. . . . . . . . . . 73
Wenqiang Xu, Shiqun Yin, Junfeng Zhao, and Ting Pu
Exploiting News Article Structure for Automatic Corpus Generationof Entailment Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
Jan Christian Blaise Cruz, Jose Kristian Resabal, James Lin,Dan John Velasco, and Charibeth Cheng
Fake News Detection Using Multiple-View Text Representation . . . . . . . . . . 100Tuan Ha and Xiaoying Gao
Generating Pseudo Connectives with MLMs for Implicit DiscourseRelation Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113
Congcong Jiang, Tieyun Qian, Zhuang Chen, Kejian Tang,Shaohui Zhan, and Tao Zhan
Graph Convolutional Network Exploring Label Relations for Multi-labelText Classification. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
Ting Pu, Shiqun Yin, Wenwen Li, and Wenqiang Xu
Improving Long Content Question Generation with Multi-levelPassage Encoding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140
Peide Zhu
Learning Vietnamese-English Code-Switching Speech Synthesis ModelUnder Limited Code-Switched Data Scenario . . . . . . . . . . . . . . . . . . . . . . . 153
Cuong Manh Nguyen, Lam Viet Phung, Cuc Thi Bui, Trang Van Truong,and Huy Tien Nguyen
Multi-task Text Normalization Approach for Speech Synthesis . . . . . . . . . . . 164Cuc Thi Bui, Trang Van Truong, Cuong Manh Nguyen, Lam Viet Phung,Manh Tien Nguyen, and Huy Tien Nguyen
Performance-Driven Reinforcement Learning Approach for AbstractiveText Summarization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Trang-Phuong N. Nguyen, Nam-Chi Van, and Nhi-Thao Tran
Punctuation Prediction in Vietnamese ASRs Using Transformer-BasedModels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
Viet The Bui and Oanh Thi Tran
Rumor Detection on Microblogs Using Dual-Grained Feature via GraphNeural Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 205
Shouzhi Xu, Xiaodi Liu, Kai Ma, Fangmin Dong, Shunzhi Xiang,and Changsong Bing
Short Text Clustering Using Joint Optimization of Feature Representationsand Cluster Assignments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
Liping Sun, Tingli Du, Xiaoyu Duan, and Yonglong Luo
Soft-BAC: Soft Bidirectional Alignment Cost for End-to-End AutomaticSpeech Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
Yonghe Wang, Hui Zhang, Feilong Bao, and Guanglai Gao
Span Labeling Approach for Vietnamese and ChineseWord Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
Duc-Vu Nguyen, Linh-Bao Vo, Dang Van Thin,and Ngan Luu-Thuy Nguyen
VSEC: Transformer-Based Model for Vietnamese Spelling Correction . . . . . . 259Dinh-Truong Do, Ha Thanh Nguyen, Thang Ngoc Bui,and Hieu Dinh Vo
What Emotion Is Hate? Incorporating Emotion Information into the HateSpeech Detection Task. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 273
Kosisochukwu Judith Madukwe, Xiaoying Gao, and Bing Xue
xx Contents – Part II
Enhanced Named Entity Recognition with Semantic Dependency . . . . . . . . . 287Peng Wang, Zhe Wang, Xiaowang Zhang, Kewen Wang,and Zhiyong Feng
Improving Sentence-Level Relation Classification via Machine ReadingComprehension and Reinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . 299
Bo Xu, Zhengqi Zhang, Xiangsan Zhao, Hui Song, and Ming Du
Multi-modal and Multi-perspective Machine Translation by CollectingDiverse Alignments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 311
Lin Li, Turghun Tayir, Kaixi Hu, and Dong Zhou
Simplifying Paragraph-Level Question Generation via TransformerLanguage Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323
Luis Enrico Lopez, Diane Kathryn Cruz, Jan Christian Blaise Cruz,and Charibeth Cheng
Neural Networks and Deep Learning
ABAE: Utilize Attention to Boost Graph Auto-Encoder . . . . . . . . . . . . . . . . 337Tianyu Liu, Yifan Li, Yujie Sun, Lixin Cui, and Lu Bai
Adversarial Examples Defense via Combining Data Transformationsand RBF Layers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 349
Jingjie Li, Jiaquan Gao, and Xiao-Xin Li
An Improved Deep Model for Knowledge Tracingand Question-Difficulty Discovery. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362
Huan Dai, Yupei Zhang, Yue Yun, and Xuequn Shang
ARNet: Accurate and Real-Time Network for Crowd Counting . . . . . . . . . . 376Yinfeng Xia, Qing He, Wenyue Wei, and Baoqun Yin
Deep Recommendation Model Based on BiLSTM and BERT. . . . . . . . . . . . 390Changwei Liu and Xiaowen Deng
GCMNet: Gated Cascade Multi-scale Network for Crowd Counting . . . . . . . 403Jinfang Zheng, Panpan Zhao, Jinyang Xie, Chen Lyu, and Lei Lyu
GIAD: Generative Inpainting-Based Anomaly Detection viaSelf-Supervised Learning for Human Monitoring. . . . . . . . . . . . . . . . . . . . . 418
Ning Dong and Einoshin Suzuki
Heterogeneous Graph Attention Network for User Geolocation . . . . . . . . . . . 433Xuan Zhang, FuQiang Lin, DiWen Dong, WangQun Chen, and Bo Liu
Contents – Part II xxi
Hyperbolic Tangent Polynomial Parity Cyclic Learning Rate for DeepNeural Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448
Hong Lin, Xiaodong Yang, Binyan Wu, and Ruyan Xiong
Infrared Image Super-Resolution via HeterogeneousConvolutional WGAN . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 461
Yongsong Huang, Zetao Jiang, Qingzhong Wang, Qi Jiang,and Guoming Pang
Knowledge Compensation Network with Divisible Feature Learningfor Unsupervised Domain Adaptive Person Re-identification . . . . . . . . . . . . 473
Jiajing Hong, Yang Zhang, and Yuesheng Zhu
LoCo-VAE: Modeling Short-Term Preference as Joint Effect of Long-TermPreference and Context-Aware Impact in Recommendation . . . . . . . . . . . . . 487
Jianping Liu, Bo Wang, Ruifang He, Bin Wu, Shuo Zhang, Yuexian Hou,and Qinxue Jiang
Multi-scale Edge-Based U-Shape Network for Salient Object Detection . . . . . 501Han Sun, Yetong Bian, Ningzhong Liu, and Huiyu Zhou
Reconstruct Anomaly to Normal: Adversarially Learned and LatentVector-Constrained Autoencoder for Time-Series Anomaly Detection . . . . . . 515
Chunkai Zhang, Wei Zuo, Shaocong Li, Xuan Wang, Peiyi Han,and Chuanyi Liu
Robust Ensembling Network for Unsupervised Domain Adaptation . . . . . . . . 530Han Sun, Lei Lin, Ningzhong Liu, and Huiyu Zhou
SPAN: Subgraph Prediction Attention Network for Dynamic Graphs. . . . . . . 544Yuan Li, Chuanchang Chen, Yubo Tao, and Hai Lin
WINVC: One-Shot Voice Conversion with Weight AdaptiveInstance Normalization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559
Shengjie Huang, Mingjie Chen, Yanyan Xu, Dengfeng Ke,and Thomas Hain
Fusion Graph Convolutional Collaborative Filtering . . . . . . . . . . . . . . . . . . 574Zeqi Zhang, Ying Liu, and Fengli Sun
Multi-label Learning by Exploiting Imbalanced Label Correlations . . . . . . . . 585Shiqiao Gu, Liu Yang, Yaning Li, and Hui Li
Random Sparsity Defense Against Adversarial Attack . . . . . . . . . . . . . . . . . 597Nianyan Hu, Ting Lu, Wenjing Guo, Qiubo Huang, Guohua Liu,Shan Chang, Jiafei Song, and Yiyang Luo
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609
xxii Contents – Part II
Contents – Part III
Reinforcement Learning
Consistency Regularization for Ensemble Model BasedReinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
Ruonan Jia, Qingming Li, Wenzhen Huang, Junge Zhang, and Xiu Li
Detecting and Learning Against Unknown Opponentsfor Automated Negotiations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
Leling Wu, Siqi Chen, Xiaoyang Gao, Yan Zheng, and Jianye Hao
Diversity-Based Trajectory and Goal Selection with HindsightExperience Replay . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
Tianhong Dai, Hengyan Liu, Kai Arulkumaran, Guangyu Ren,and Anil Anthony Bharath
Off-Policy Training for Truncated TD(k) Boosted Soft Actor-Critic . . . . . . . . 46Shiyu Huang, Bin Wang, Hang Su, Dong Li, Jianye Hao, Jun Zhu,and Ting Chen
Adaptive Warm-Start MCTS in AlphaZero-Like DeepReinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
Hui Wang, Mike Preuss, and Aske Plaat
Batch-Constraint Inverse Reinforcement Learning . . . . . . . . . . . . . . . . . . . . 72Mao Chen, Li Wan, Chunyan Gou, Jiaolu Liao, and Shengjiang Wu
KG-RL: A Knowledge-Guided Reinforcement Learning for MassiveBattle Games . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
Shiyang Zhou, Weiya Ren, Xiaoguang Ren, Xianya Mi, and Xiaodong Yi
Vision and Perception
A Semi-supervised Defect Detection Method Based on Image Inpainting . . . . 97Huibin Cao, Yongxuan Lai, Quan Chen, and Fan Yang
ANF: Attention-Based Noise Filtering Strategy for UnsupervisedFew-Shot Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
Guangsen Ni, Hongguang Zhang, Jing Zhao, Liyang Xu, Wenjing Yang,and Long Lan
Asymmetric Mutual Learning for Unsupervised Cross-DomainPerson Re-identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
Danyang Huang, Lei Zhang, Qishuai Diao, Wei Wu, and Zhong Zhou
Collaborative Positional-Motion Excitation Module for EfficientAction Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
Tamam Alsarhan and Hongtao Lu
Graph Attention Convolutional Network with Motion Tempo Enhancementfor Skeleton-Based Action Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
Ruwen Bai, Xiang Meng, Bo Meng, Miao Jiang, Junxing Ren,Yang Yang, Min Li, and Degang Sun
Learning to Synthesize and Remove Rain Unsupervisedly . . . . . . . . . . . . . . 166Yinhe Qi, Meng Pan, and Zhi Jin
Object Bounding Box-Aware Embedding for Point CloudInstance Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
Lixue Cheng, Taihai Yang, and Lizhuang Ma
Objects as Extreme Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195Yang Yang, Min Li, Bo Meng, Zihao Huang, Junxing Ren,and Degang Sun
Occlusion-Aware Facial Expression Recognition Based RegionRe-weight Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
Xinghai Zhang, Xingming Zhang, Jinzhao Zhou, and Yubei Lin
Online Multi-Object Tracking with Pose-Guided Object Location and DualSelf-Attention Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
Xin Zhang, Shihao Wang, Yuanzhe Yang, Chengxiang Chu,and Zhong Zhou
Random Walk Erasing with Attention Calibration for Action Recognition . . . 236Yuze Tian, Xian Zhong, Wenxuan Liu, Xuemei Jia, Shilei Zhao,and Mang Ye
RGB-D Based Visual Navigation Using Direction Estimation Module . . . . . . 252Chao Luo, Sheng Bi, Min Dong, and Hongxu Nie
Semi-supervised Single Image Deraining with DiscreteWavelet Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265
Xin Cui, Wei Shang, Dongwei Ren, Pengfei Zhu, and Yankun Gao
Simple Light-Weight Network for Human Pose Estimation. . . . . . . . . . . . . . 279Bin Sun and Mingguo Zhao
xxiv Contents – Part III
SIN: Superpixel Interpolation Network. . . . . . . . . . . . . . . . . . . . . . . . . . . . 293Qing Yuan, Songfeng Lu, Yan Huang, and Wuxin Sha
SPANet: Spatial and Part-Aware Aggregation Network for 3DObject Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 308
Yangyang Ye
Subspace Enhancement and Colorization Network for Infrared VideoAction Recognition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321
Lu Xu, Xian Zhong, Wenxuan Liu, Shilei Zhao, Zhengwei Yang,and Luo Zhong
Thinking in Patch: Towards Generalizable Forgery Detectionwith Patch Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 337
Xueqi Zhang, Shuo Wang, Chenyu Liu, Min Zhang, Xiaohan Liu,and Haiyong Xie
When Distortion Meets Perceptual Quality: A Multi-taskLearning Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353
Jing Wen and Qianyu Guo
Feature Adaption with Predicted Boxes for Oriented Object Detectionin Aerial Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
Minhao Zou, Ziye Hu, Yuxiang Guan, Zhongxue Gan, Chun Guan,and Siyang Leng
Few-Shot Crowd Counting via Self-supervised Learning . . . . . . . . . . . . . . . 379Jiefeng Long, Chun Li, and Lin Shang
Low-Rank Orthonormal Analysis Dictionary Learning for ImageClassification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391
Kun Jiang, Zhaoli Liu, and Qindong Sun
MRAC-Net: Multi-resolution Anisotropic Convolutional Network for 3DPoint Cloud Completion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403
Sheng Liu, Dingda Li, Wenhao Huang, Yifeng Cao,and Shengyong Chen
Nonlinear Parametric Transformation and Generation of Images Basedon a Network with the CWNL Layer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
Slawomir Golak
PupilFace: A Cascaded Face Detection and Location NetworkFusing Attention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426
Xiang Li and Jiancheng Zou
Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 439
Contents – Part III xxv