Lecture Notes in Artificial Intelligence
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Lecture Notes in Artificial Intelligence 12798 Subseries of Lecture Notes in Computer Science Series Editors Randy Goebel University of Alberta, Edmonton, Canada Yuzuru Tanaka Hokkaido University, Sapporo, Japan Wolfgang Wahlster DFKI and Saarland University, Saarbrücken, Germany Founding Editor Jörg Siekmann DFKI and Saarland University, Saarbrücken, Germany
More information about this subseries at http://www.springer.com/series/1244
Hamido Fujita Ali Selamat
• •
Jerry Chun-Wei Lin Moonis Ali (Eds.)
•
Advances and Trends
in Artificial Intelligence
Artificial Intelligence Practices
34th International Conference
on Industrial, Engineering and Other Applications
of Applied Intelligent Systems, IEA/AIE 2021
Kuala Lumpur, Malaysia, July 26–29, 2021
Proceedings, Part I
123Editors Hamido Fujita Ali Selamat i-SOMET Incorporate Association Universiti Teknologi Malaysia Morioka, Japan Kuala Lumpur, Malaysia Jerry Chun-Wei Lin Moonis Ali Western Norway University Texas State University San Marcos of Applied Sciences San Marcos, TX, USA Bergen, Norway ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Artificial Intelligence ISBN 978-3-030-79456-9 ISBN 978-3-030-79457-6 (eBook) https://doi.org/10.1007/978-3-030-79457-6 LNCS Sublibrary: SL7 – Artificial Intelligence © Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material 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 information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective 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 are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
Artificial Intelligence innovations in recent decades have entered a sophisticated stage
in providing intelligent interaction between humans and machines, solving problems,
and providing advice in many different infrastructures. Machines in different disciplines
have become ubiquitous in all aspects of life, including education, governance, science,
healthcare, warfare, and industry. Computing machinery has become smaller and faster,
and the costs of data storage and communication have greatly decreased. Consequently,
big data of vast dimensionality is being intelligently collected and stored in smart
databases for use in decision making and prediction for applications such as security
and health care, amongst others. Moreover, novel and improved computing architec-
tures have been designed for efficient large-scale data processing, such as big data
frameworks, FPGAs and GPUs. Thanks to these advancements and recent break-
throughs in artificial intelligence, researchers and practitioners have developed more
complex and effective artificial intelligence-based systems. This has led to a greater
interest in artificial intelligence to solve complex real-world problems, and the proposal
of many innovative applications.
This volume contains the proceedings of the 34th International Conference on
Industrial, Engineering and other Applications of Applied Intelligent Systems
(IEA/AIE 2021), which was held online during July 26–29, 2021, in Kuala Lumpur,
Malaysia. The IEA/AIE conference is an annual event that emphasizes applications of
applied intelligent systems to solve real-life problems in all areas including engineer-
ing, science, industry, automation and robotics, business and finance, medicine and
biomedicine, bioinformatics, cyberspace, and human-machine interactions. This year,
145 submissions were received. Each paper was evaluated by three to four reviewers
from an International Program Committee consisting of 196 members from 37 coun-
tries. Based on the evaluation, 87 papers were selected as full papers and 19 as short
papers, which are presented in two volumes. We are grateful to all the reviewers for the
time spent writing detailed and constructive comments for the authors, and also the
authors for the proposal of so many high-quality papers.
The program of IEA/AIE 2021 included eight special sessions:
• Special Session on Data Stream Mining: Algorithms and Applications
(DSMAA2021)
• Special Session on Intelligent Knowledge Engineering in Decision Making Systems
(IKEDS2021)
• Special Session on Knowledge Graphs in Digitalization Era (KGDE2021)
• Special Session on Spatiotemporal Big Data Analytics (SBDA2021)
• Special Session on Big Data and Intelligence Fusion Analytics (BDIFA2021)
• Special Session on AI in Healthcare (AIH2021)
• Special Session on Intelligent Systems and e-Applications (iSeA2021)
• Special Session on Collective Intelligence in Social Media (CISM2021).vi Preface
Moreover, two keynote talks were given by Professor Francisco Herrera, from the
University of Granada, Spain, and Director of the Andalusian Research Institute “Data
Science and Computational Intelligence”, and Professor Vincent S. Tseng from the
Department of Computer Science, National Yang Ming Chiao Tung University,
Taiwan.
We would like to thank everyone who has contributed to the success of this year’s
edition of IEA/AIE, that is the authors, Program Committee members, reviewers,
keynote speakers, organizers and participants.
May 2021 Hamido Fujita
Ali Selamat
Jerry Chun-Wei Lin
Moonis AliOrganization General Chairs Hamido Fujita, Japan Moonis Ali, USA Organizing Chairs Ali Selamat, Malaysia Jun Sasaki, Japan Program Chairs Ali Selamat, Malaysia Jerry Chun-Wei Lin, Norway Special Session Chairs Philippe Fournier-Viger, China Nor Azura Mohd Ghani, Malaysia Publicity Chairs Mohd Hazli Mohamed Zabil, Malaysia Lim Kok Cheng, Malaysia Program Committee Abidalrahman Moh’D, USA Adel Bouhoula, Tunisia Adrianna Kozierkiewicz, Poland Ahmed Tawfik, Egypt Alban Grastien, Australia Alexander Ferrein, Germany Artur Andrzejak, Germany Ayahiko Niimi, Japan Barbara Pes, Italy Bay Vo, Vietnam Dariusz Krol, Poland Dinh Tuyen Hoang, Korea Du Nguyen
viii Organization Engelbert Mephu Nguifo, France Eugene Santos Jr., USA Farid Nouioua, France Farshad Badie, Denmark Fevzi Belli, Germany Flavio Soares Correa da Silva, Brazil Franz Wotawa, Austria Giorgos Dounias, Greece Hadjali Allel, France Hamido Fujita, Japan He Jiang, China Ingo Pill, Austria Jerry Chun-Wei Lin, Norway Joao Mendes-Moreira, Portugal João Paulo Carvalho, Portugal Jose Maria-Luna, Spain Krishna Reddy P., India Ladjel Bellatreche, France Leszek Borzemski, Poland Maciej Grzenda, Poland Mark Levin, USA Mercedes Merayo, Spain Nazha Selmaoui-Folcher, Germany Ngoc-Thanh Nguyen, Poland Philippe Fournier-Viger, China Philippe Leray, France Rui Abreu, Portugal Sabrina Senatore, Italy Said Jabbour, France Shyi-Ming Chen, Taiwan Sonali Agarwal, India Takayuki Ito, Japan Tim Hendtlass, Australia Trong Hieu Tran, Vietnam Tzung-Pei Hong, Taiwan Uday Rage, Japan Unil Yun, Korea Van Cuong Tran, Vietnam Wen-Juan Hou, Taiwan Wolfgang Mayer, Australia Xiangdong An, USA Xinzheng Niu, China Yun Sing Koh, Australia Yutaka Watanobe, Japan
Contents – Part I Knowledge Discovery and Pattern Mining Fast Mining of Top-k Frequent Balanced Association Rules . . . . . . . . . . . . . 3 Xiangyu Liu, Xinzheng Niu, Jieliang Kuang, Shenghan Yang, and Pengpeng Liu Towards Increasing Open Data Adoption Through Stream Data Integration and Imputation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Robert Kunicki and Maciej Grzenda Towards Efficient Discovery of Periodic-Frequent Patterns in Columnar Temporal Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Ravikumar Penugonda, Likhitha Palla, Uday Kiran Rage, Yutaka Watanobe, and Koji Zettsu Data-Driven Simulation of Ride-Hailing Services Using Imitation and Reinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Haritha Jayasinghe, Tarindu Jayatilaka, Ravin Gunawardena, and Uthayasanker Thayasivam Discovering Spatial High Utility Itemsets in High-Dimensional Spatiotemporal Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Sai Chithra Bommisetty, Ravikumar Penugonda, Uday Kiran Rage, Minh Son Dao, and Koji Zettsu A Single-Stage Tree-Structure-Based Approach to Determine Fuzzy Average-Utility Itemsets. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Tzung-Pei Hong, Meng-Ping Ku, Hsiu-Wei Chiu, Wei-Ming Huang, Shu-Min Li, and Jerry Chun-Wei Lin Mining Episode Rules from Event Sequences Under Non-overlapping Frequency . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Oualid Ouarem, Farid Nouioua, and Philippe Fournier-Viger Distributed Mining of High Utility Time Interval Sequential Patterns with Multiple Minimum Utility Thresholds . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86 Sumalatha Saleti, Jaya Lakshmi Tangirala, and Ragunathan Thirumalaisamy
x Contents – Part I Artificial Intelligence and Machine Learning Emergency Analysis: Multitask Learning with Deep Convolutional Neural Networks for Fire Emergency Scene Parsing . . . . . . . . . . . . . . . . . . . . . . . 101 Jivitesh Sharma, Ole-Christoffer Granmo, and Morten Goodwin Comparison of Consolidation Methods for Predictive Learning of Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 Ryoichi Nakajo and Tetsuya Ogata Evolutionary Optimization of Convolutional Neural Network Architecture Design for Thoracic X-Ray Image Classification . . . . . . . . . . . . . . . . . . . . . 121 Hassen Louati, Slim Bechikh, Ali Louati, Abdulaziz Aldaej, and Lamjed Ben Said Understanding the Effects of Mitigation on De-identified Data . . . . . . . . . . . 133 Andrew Chester, Yun Sing Koh, and Junjae Lee Combining Siamese Network and Correlation Filter for Complementary Object Tracking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Kosuke Honda and Hamido Fujita Closed-Form Expressions for Global and Local Interpretation of Tsetlin Machines. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Christian D. Blakely and Ole-Christoffer Granmo Explainable Reinforcement Learning with the Tsetlin Machine . . . . . . . . . . . 173 Saeed Rahimi Gorji, Ole-Christoffer Granmo, and Marco Wiering Sematic, Topology, and Ontology Models Semantic Technologies Towards Missing Values Imputation. . . . . . . . . . . . . 191 Iker Esnaola-Gonzalez, Unai Garciarena, and Jesús Bermúdez An Improved Integer Programming Formulation for Inferring Chemical Compounds with Prescribed Topological Structures . . . . . . . . . . . . . . . . . . . 197 Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, and Tatsuya Akutsu Automatic Classification for Ontology Generation by Pretrained Language Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 Atsushi Oba, Incheon Paik, and Ayato Kuwana Deep Learning Architecture for Topological Optimized Mechanical Design Generation with Complex Shape Criterion . . . . . . . . . . . . . . . . . . . . . . . . . 222 Waad Almasri, Dimitri Bettebghor, Fakhreddine Ababsa, Florence Danglade, and Faouzi Adjed
Contents – Part I xi Computational Ontology and BIM Technology in Data-Driven Indoor Route Planning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 235 Barbara Strug and Grażyna Ślusarczyk Collaborative Maintenance of EDOAL Alignments in VocBench . . . . . . . . . 243 Armando Stellato, Manuel Fiorelli, Tiziano Lorenzetti, and Andrea Turbati DIKG2: A Semantic Data Integration Approach for Knowledge Graphs Generation from Web Forms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255 Rahma Dandan and Sylvie Despres Ontology-Based Resume Searching System for Job Applicants in Information Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 Tung T. Phan, Vinh Q. Pham, Hien D. Nguyen, Anh T. Huynh, Dung A. Tran, and Vuong T. Pham An Approach to Expressing Metamodels’ Semantics in a Concept System . . . 274 Marcin Jodłowiec and Marek Krótkiewicz Medical and Health-Related Applications Birth-Death MCMC Approach for Multivariate Beta Mixture Models in Medical Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 Mahsa Amirkhani, Narges Manouchehri, and Nizar Bouguila Intelligent Asthma Self-management System for Personalised Weather-Based Healthcare Using Machine Learning . . . . . . . . . . . . . . . . . . 297 Radiah Haque, Sin-Ban Ho, Ian Chai, Chin-Wei Teoh, Adina Abdullah, Chuie-Hong Tan, and Khairi Shazwan Dollmat Deep Forecasting of COVID-19: Canadian Case Study . . . . . . . . . . . . . . . . 309 Fadoua Khennou and Moulay A. Akhloufi COVID-19 Genome Analysis Using Alignment-Free Methods . . . . . . . . . . . 316 M. Saqib Nawaz, Philippe Fournier-Viger, Xinzheng Niu, Youxi Wu, and Jerry Chun-Wei Lin Deep Efficient Neural Networks for Explainable COVID-19 Detection on CXR Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 329 Mohamed Chetoui and Moulay A. Akhloufi Predicting Psychological Distress from Ecological Factors: A Machine Learning Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 341 Ben Sutter, Raymond Chiong, Gregorius Satia Budhi, and Sandeep Dhakal
xii Contents – Part I Graphic and Social Network Analysis Configuration Model of Employee Competences in a Social Media Team . . . 355 Jarosław Wikarek and Paweł Sitek The Extended Graph Generalization as a Representation of the Metamodels’ Extensional Layer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 369 Marcin Jodłowiec, Marek Krótkiewicz, and Piotr Zabawa WawPart: Workload-Aware Partitioning of Knowledge Graphs . . . . . . . . . . . 383 Amitabh Priyadarshi and Krzysztof J. Kochut Analysis of Sentimental Behaviour over Social Data Using Machine Learning Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396 Abdul Razaque, Fathi Amsaad, Dipal Halder, Mohamed Baza, Abobakr Aboshgifa, and Sajal Bhatia Signal and Bioinformatic Processing A Large-Scale Dataset for Hate Speech Detection on Vietnamese Social Media Texts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415 Son T. Luu, Kiet Van Nguyen, and Ngan Luu-Thuy Nguyen Determining 2-Optimality Consensus for DNA Structure . . . . . . . . . . . . . . . 427 Dai Tho Dang, Huyen Trang Phan, Ngoc Thanh Nguyen, and Dosam Hwang Evolutionary Computation Utilizing Center-Based Sampling Theory to Enhance Particle Swarm Classification of Textual Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 441 Anwar Ali Yahya, Yousef Asiri, and Ahmed Abdu Alattab Conditional Preference Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447 Nahla Ben Amor, Didier Dubois, Henri Prade, and Syrine Saidi Enhancing Multi-objective Evolutionary Neural Architecture Search with Surrogate Models and Potential Point-Guided Local Searches . . . . . . . . 460 Quan Minh Phan and Ngoc Hoang Luong Insightful and Practical Multi-objective Convolutional Neural Network Architecture Search with Evolutionary Algorithms. . . . . . . . . . . . . . . . . . . . 473 Tu Do and Ngoc Hoang Luong Method for Automatic Furniture Placement Based on Simulated Annealing and Genetic Algorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 480 Eliška Svobodová and Ladislava Smítková Janků
Contents – Part I xiii Attack and Security Recent Research on Phishing Detection Through Machine Learning Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 495 Do Nguyet Quang, Ali Selamat, and Ondrej Krejcar A Transaction Classification Model of Federated Learning . . . . . . . . . . . . . . 509 Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava, and Philippe Fournier-Viger On the Assessment of Robustness of Telemedicine Applications Against Adversarial Machine Learning Attacks. . . . . . . . . . . . . . . . . . . . . . . . . . . . 519 Ibrahim Yilmaz, Mohamed Baza, Ramy Amer, Amar Rasheed, Fathi Amsaad, and Rasha Morsi A 1D-CNN Based Deep Learning for Detecting VSI-DDoS Attacks in IoT Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 530 Enkhtur Tsogbaatar, Monowar H. Bhuyan, Doudou Fall, Yuzo Taenaka, Khishigjargal Gonchigsumlaa, Erik Elmroth, and Youki Kadobayashi Natural Language and Text Processing Hierarchical Transformer Encoders for Vietnamese Spelling Correction . . . . . 547 Hieu Tran, Cuong V. Dinh, Long Phan, and Son T. Nguyen Fast and Memory-Efficient TFIDF Calculation for Text Analysis of Large Datasets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557 Samah Senbel Collapsed Gibbs Sampling of Beta-Liouville Multinomial for Short Text Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 Samar Hannachi, Fatma Najar, Koffi Eddy Ihou, and Nizar Bouguila Constructive and Toxic Speech Detection for Open-Domain Social Media Comments in Vietnamese. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 572 Luan Thanh Nguyen, Kiet Van Nguyen, and Ngan Luu-Thuy Nguyen Fuzzy Inference and Theory The Behaviour of the Product T-Norm in Combination with Several Implications in Fuzzy PID Controller. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 587 Nourelhouda Zerarka, Saoussen Bel Hadj Kacem, and Moncef Tagina Hub and Spoke Logistics Network Design for Urban Region with Clustering-Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 598 Quan Duong, Dang Nguyen, and Quoc Nguyen
xiv Contents – Part I Sensor and Communication Networks Smartphone Sensor-Based Fall Detection Using Machine Learning Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 609 Mariam Dedabrishvili, Besik Dundua, and Natia Mamaiashvili IPR-SN: Intelligent Packet Routing in Satellite Networks Based on Distributed Deep Reinforcement Learning . . . . . . . . . . . . . . . . . . . . . . . 621 Tao Huang, Lixiang Liu, and Shuaijun Liu Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633
Contents – Part II Prediction and Recommendation F2DeepRS: A Deep Recommendation Framework Applied to ICRC Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Yongquan Xie, Finn Tseng, Kristinsson Johannes, Shiqi Qiu, and Yi Lu Murphey A Novel Rule-Based Online Judge Recommender System to Promote Computer Programming Education . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Md. Mostafizer Rahman, Yutaka Watanobe, Uday Kiran Rage, and Keita Nakamura Using Machine Learning to Predict Salaries of Major League Baseball Players . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Cheng-Yu Lee, Ping-Yu Hsu, Ming-Shien Cheng, Jun-Der Leu, Ni Xu, and Bo-Lun Kan Efficient Prediction of Discharge and Water Levels Using Ensemble Learning and Singular-Spectrum Analysis-Based Denoising . . . . . . . . . . . . . 34 Anh Duy Nguyen, Viet Hung Vu, Minh Hieu Nguyen, Duc Viet Hoang, Thanh Hung Nguyen, Kien Nguyen, and Phi Le Nguyen An Efficient Transformer-Based Model for Vietnamese Punctuation Prediction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Hieu Tran, Cuong V. Dinh, Quang Pham, and Binh T. Nguyen Study of Hybridized Support Vector Regression Based Flood Susceptibility Mapping for Bangladesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Zakaria Shams Siam, Rubyat Tasnuva Hasan, Soumik Sarker Anik, Fahima Noor, Mohammed Sarfaraz Gani Adnan, and Rashedur M. Rahman A Fusion Approach for Paper Submission Recommendation System . . . . . . . 72 Son T. Huynh, Nhi Dang, Phong T. Huynh, Dac H. Nguyen, and Binh T. Nguyen One-Class Classification Approach Using Feature-Slide Prediction Subtask for Feature Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 Toshitaka Hayashi and Hamido Fujita
xvi Contents – Part II Data Management, Clustering and Classification A Novel Approach for Enhancing Vietnamese Sentiment Classification . . . . . 99 Cuong V. Nguyen, Khiem H. Le, and Binh T. Nguyen Consistency Assessment of Datasets in the Context of a Problem Domain . . . 112 Bogumila Hnatkowska, Zbigniew Huzar, and Lech Tuzinkiewicz Effects of Performance Clustering in User Modelling for Learning Style Knowledge Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126 Chin-Wei Teoh, Sin-Ban Ho, Khairi Shazwan Dollmat, Ian Chai, Wan-Noorshahida Mohd-Isa, Chuie-Hong Tan, Sek-Kit Teh, and Manzoor Shahida Raihan A Novel Perspective of Text Classification by Prolog-Based Deductive Databases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 Kiet Van Nguyen, Tin Van Huynh, and Anh Gia-Tuan Nguyen Improving Human Emotion Recognition from Emotive Videos Using Geometric Data Augmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Nusrat J. Shoumy, Li-Minn Ang, D. M. Motiur Rahaman, Tanveer Zia, Kah Phooi Seng, and Sabira Khatun Applying Method of Automatic Classification Tools to Make Effective Organizing of Photos Taken in Childcare Facilities . . . . . . . . . . . . . . . . . . . 162 Takaaki Yamaga, Takayuki Inoue, Hiroki Uemura, Wakaho Otoyama, and Jun Sasaki Land Use/Land Cover Change Analysis Due to Tourism in the Chittagong Hill Tracts of Bangladesh. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173 Fayezah Anjum, Hasan Mohiuddin Zilany, Syed Shahir Ahmed Rakin, Md. Abdul Hoque, Aina-Nin Ania, Md. Asadut Zaman, Jebun Nahar Moni, and Rashedur M. Rahman Robotics Estimation Method for Operational Environment Complexity by a Robotic Team . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 187 Denis A. Beloglazov, Maria A. Vasileva, Victor V. Soloviev, Vladimir A. Pereverzev, and Viacheslav H. Pshihopov A Cloud-Based Robot Framework for Indoor Object Identification Using Unsupervised Segmentation Technique and Convolution Neural Network (CNN) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Raihan Kabir, Yutaka Watanobe, and Md. Rashedul Islam
Contents – Part II xvii Knowledge Based and Decision Support Systems The Concept of Information Graphs as a Tool to Identify Vulnerabilities in the Information Map of an Organisation. . . . . . . . . . . . . . . . . . . . . . . . . 215 Zygmunt Mazur and Janusz Pec A Learning-Automata Based Solution for Non-equal Partitioning: Partitions with Common GCD Sizes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Rebekka Olsson Omslandseter, Lei Jiao, and B. John Oommen Building a Knowledge Graph with Inference for a Production Machine Using the Web of Things Standard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240 Sascha Meckler, Harald Steinmüller, and Andreas Harth Open-World Knowledge Graph Completion Benchmarks for Knowledge Discovery. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 252 Felix Hamann, Adrian Ulges, Dirk Krechel, and Ralph Bergmann A Case-Based Reasoning Approach for a Decision Support System in Manufacturing. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265 Sascha Lang, Valentin Plenk, and Ute Schmid Online Automatic Assessment System for Program Code: Architecture and Experiences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272 Yutaka Watanobe, Md. Mostafizer Rahman, Uday Kiran Rage, and Ravikumar Penugonda A Multi-criteria Group Decision Making Procedure Based on a Multi-granular Linguistic Approach for Changeable Scenarios . . . . . . . . 284 José Ramón Trillo, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, and Juan Antonio Morente-Molinera Multimedia Applications Edge Based Method for Kidney Segmentation in MRI Scans . . . . . . . . . . . . 299 Ala’a R. Al-Shamasneh, Hamid A. Jalab, and Hend Alkahtani Using the HAAR Wavelet Transform and K-nearest Neighbour Algorithm to Improve ECG Detection and Classification of Arrhythmia . . . . . . . . . . . . 310 A. M. Khairuddin and K. N. F. Ku Azir Query by Humming for Song Identification Using Voice Isolation . . . . . . . . 323 Edwin Alfaro-Paredes, Leonardo Alfaro-Carrasco, and Willy Ugarte IMAGE-2-AQI: Aware of the Surrounding Air Qualification by a Few Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335 Minh-Son Dao, Koji Zettsu, and Uday Kiran Rage
xviii Contents – Part II Advances in Sports Video Summarization – A Review Based on Cricket Videos . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 347 Vani Vasudevan and Mohan Sellappa Gounder Augmented Audio Data in Improving Speech Emotion Classification Tasks. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360 Nusrat J. Shoumy, Li-Minn Ang, D. M. Motiur Rahaman, Tanveer Zia, Kah Phooi Seng, and Sabira Khatun Innovative Applications of Intelligent Systems Intelligent System of Mooring Planning, Based on Deep Q-Learning . . . . . . . 369 B. V. Gurenko and M. A. Vasileva Experimental Study on Predictive Modeling in the Gamification Marketing Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379 Zhou-Yi Lim, Lee-Yeng Ong, and Meng-Chew Leow Pivot Point Based Intelligent System to Associate Creative Textual Artefacts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 Hrishikesh Kulkarni and Bradly Alicea Mood Support: A Personalized Intelligent Support Assignment System Using an Agent-Based Dynamic Configuration Model . . . . . . . . . . . . . . . . . 399 Azizi Ab Aziz, Roqia Rateb, and Arya Muhammad Bimo Continuous Build Outcome Prediction: A Small-N Experiment in Settings of a Real Software Project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412 Marcin Kawalerowicz and Lech Madeyski Jaskier: A Supporting Software Tool for Continuous Build Outcome Prediction Practice. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 426 Marcin Kawalerowicz and Lech Madeyski CPS and Industrial Applications Automated Diagnosis of Cyber-Physical Systems . . . . . . . . . . . . . . . . . . . . 441 Franz Wotawa, Oliver Tazl, and David Kaufmann Quick Start and Adaptive New Server Monitor . . . . . . . . . . . . . . . . . . . . . . 453 Wei Zhang Map-Matching Based on HMM for Urban Traffic . . . . . . . . . . . . . . . . . . . . 462 Dongzi Chen, Xinzheng Niu, Philippe Fournier-Viger, Wenxin Wu, and Bing Wang
Contents – Part II xix The Choice of AI Matters: Alternative Machine Learning Approaches for CPS Anomalies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474 Uraz Odyurt, Dolly Sapra, and Andy D. Pimentel On-demand Knowledge Graphs for Standards-Based Power Grid Data Provisioning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 485 Vijay S. Kumar, Sharad Dixit, Kareem S. Aggour, Jenny Weisenberg Williams, and Paul Cuddihy Defect, Anomaly and Intrusion Detection Intrusion Detection Algorithm Based on SDA-ELM . . . . . . . . . . . . . . . . . . 495 Xiaotao Wei, Shuyu Ren, Yinglong Li, Xi-Xi Wang, and Mengxia Jin Explaining Defect Detection with Saliency Maps . . . . . . . . . . . . . . . . . . . . 506 Joe Lorentz, Thomas Hartmann, Assaad Moawad, Francois Fouquet, and Djamila Aouada d-BTAI: The Dynamic-Binary Tree Based Anomaly Identification Algorithm for Industrial Systems. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519 Jyotirmoy Sarkar, Santonu Sarkar, Snehanshu Saha, and Swagatam Das Identifying Anomaly Work in Intralogistics Using BLE and LPWA . . . . . . . 533 Masahiro Yamaguchi, Noriko Yuasa, Yuki Yoshimura, and Takanobu Otsuka Financial and Supply Chain Applications Impact Analysis of Proactive and Reactive Inventory Disruption Management on Supply Chain Performance . . . . . . . . . . . . . . . . . . . . . . . . 543 Maroua Kessentini and Narjes Bellamine Ben Saoud A ML-Based Stock Trading Model for Profit Predication . . . . . . . . . . . . . . . 554 Jimmy Ming-Tai Wu, Lingyun Sun, Gautam Srivastava, and Jerry Chun-Wei Lin Machine Learning-Based Empirical Investigation for Credit Scoring in Vietnam’s Banking . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564 Khanh Quoc Tran, Binh Van Duong, Linh Quang Tran, An Le-Hoai Tran, An Trong Nguyen, and Kiet Van Nguyen Bayesian Networks Unsupervised Co-training of Bayesian Networks for Condition Prediction . . . 577 Mathilde Monvoisin, Philippe Leray, and Mathieu Ritou
xx Contents – Part II BigData and Time Series Processing Implementation of Neural Network Regression Model for Faster Redshift Analysis on Cloud-Based Spark Platform . . . . . . . . . . . . . . . . . . . . . . . . . . 591 Snigdha Sen, Snehanshu Saha, Pavan Chakraborty, and Krishna Pratap Singh Target Class Supervised Sample Length and Training Sample Reduction of Univariate Time Series. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 603 Sanjay Kumar Sonbhadra, Sonali Agarwal, and P. Nagabhushan Information Retrieval and Relation Extraction Improving Relation Extraction via Joint Coding Using BiLSTM and DCNN. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 617 Kaixu Wang, Qianqian Ren, Li Hui, Hui Xu, Shiyang Li, and Peng Xu A Possible Worlds Interpretation of Many-Sorted Theory for IR . . . . . . . . . . 629 Mohammed Sadou, Yassine Djouadi, and Allel Hadj-Ali Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 637
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