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Web and Big Data: 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part II (Lecture Notes in Computer Science #14332)

by Jianxin Li Geyong Min Xiangyu Song Ruyi Feng Yunliang Chen

The 4-volume set LNCS 14331, 14332, 14333, and 14334 constitutes the refereed proceedings of the 7th International Joint Conference, APWeb-WAIM 2023, which took place in Wuhan, China, in October 2023. The total of 138 papers included in the proceedings were carefully reviewed and selected from 434 submissions. They focus on innovative ideas, original research findings, case study results, and experienced insights in the areas of the World Wide Web and big data, covering Web technologies, database systems, information management, software engineering, knowledge graph, recommend system and big data.

Web and Big Data: 7th International Joint Conference, APWeb-WAIM 2023, Wuhan, China, October 6–8, 2023, Proceedings, Part IV (Lecture Notes in Computer Science #14334)

by Xiangyu Song Ruyi Feng Yunliang Chen Jianxin Li Geyong Min

The 4-volume set LNCS 14331, 14332, 14333, and 14334 constitutes the refereed proceedings of the 7th International Joint Conference, APWeb-WAIM 2023, which took place in Wuhan, China, in October 2023. The total of 138 papers included in the proceedings were carefully reviewed and selected from 434 submissions. They focus on innovative ideas, original research findings, case study results, and experienced insights in the areas of the World Wide Web and big data, covering Web technologies, database systems, information management, software engineering, knowledge graph, recommend system and big data.

Sentiment Analysis and its Application in Educational Data Mining (SpringerBriefs in Applied Sciences and Technology)

by Soni Sweta

The book delves into the fundamental concepts of sentiment analysis, its techniques, and its practical applications in the context of educational data. The book begins by introducing the concept of sentiment analysis and its relevance in educational settings. It provides a thorough overview of the various techniques used for sentiment analysis, including natural language processing, machine learning, and deep learning algorithms. The subsequent chapters explore applications of sentiment analysis in educational data mining across multiple domains. The book illustrates how sentiment analysis can be employed to analyze student feedback and sentiment patterns, enabling educators to gain valuable insights into student engagement, motivation, and satisfaction. It also examines how sentiment analysis can be used to identify and address students' emotional states, such as stress, boredom, or confusion, leading to more personalized and effective interventions. Furthermore, the book explores the integration of sentiment analysis with other educational data mining techniques, such as clustering, classification, and predictive modeling. It showcases real-world case studies and examples that demonstrate how sentiment analysis can be combined with these approaches to improve educational decision-making, curriculum design, and adaptive learning systems.

Introduction to Analytical Mechanics

by Amitabha Ghosh

This comprehensive, introductory textbook on Analytical Mechanics is designed for both seasoned researchers and budding students of Mechanics. This book meticulously outlines the whole route to analytical treatment of the 'science of motion'. Authored with years of teaching expertise, this book unravels new concepts beyond the traditional Newtonian framework, ensuring clarity for beginners. The book is tailored to focus primarily upon areas essential in a first-level course. Unveil innovative treatments helpful in taking the first-time reader through the labyrinthian path along which often analytical mechanics progresses. Ideal for a semester-long study at senior undergraduate and junior postgraduate levels, our text features ample solved examples to reinforce theoretical applications.

Distributionally Robust Optimization and its Applications in Power System Energy Storage Sizing

by Wei Wei Rui Xie

This book introduces the mathematical foundations of distributionally robust optimization (DRO) for decision-making problems with ambiguous uncertainties and applies them to tackle the critical challenge of energy storage sizing in renewable-integrated power systems, providing readers with an efficient and reliable approach to analyze and design real-world energy systems with uncertainties. Covering a diverse range of topics, this book starts by exploring the necessity for energy storage in evolving power systems and examining the benefits of employing distributionally robust optimization. Subsequently, the cutting-edge mathematical theory of distributionally robust optimization is presented, including both the general theory and moment-based, KL-divergence, and Wasserstein-metric distributionally robust optimization theories. The techniques are then applied to various practical energy storage sizing scenarios, such as stand-alone microgrids, large-scale renewable power plants, bulk power grids, and multi-carrier energy networks. This book offers clear explanations and accessible guidance to bridge the gap between advanced optimization methods and industrial applications. Its interdisciplinary scope makes the book appealing to researchers, graduate students, and industry professionals working in electrical engineering and operations research, catering to both beginners and experts.

Industrial Recommender System: Principles, Technologies and Enterprise Applications

by Lantao Hu Yueting Li Guangfan Cui Kexin Yi

Recommender systems, as a highly popular AI technology in recent years, have been widely applied across various industries. They have transformed the way we interact with technology, influencing our choices and shaping our experiences. This book provides a comprehensive introduction to industrial recommender systems, starting with the overview of the technical framework, gradually delving into each core module such as content understanding, user profiling, recall, ranking, re-ranking and so on, and introducing the key technologies and practices in enterprises. The book also addresses common challenges in recommendation cold start, recommendation bias and debiasing. Additionally, it introduces advanced technologies in the field, such as reinforcement learning, causal inference. Professionals working in the fields of recommender systems, computational advertising, and search will find this book valuable. It is also suitable for undergraduate, graduate, and doctoral students majoring in artificial intelligence, computer science, software engineering, and related disciplines. Furthermore, it caters to readers with an interest in recommender systems, providing them with an understanding of the foundational framework, insights into core technologies, and advancements in industrial recommender systems. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.

Digital Forensics and Watermarking: 22nd International Workshop, IWDW 2023, Jinan, China, November 25–26, 2023, Revised Selected Papers (Lecture Notes in Computer Science #14511)

by Bin Ma Jian Li Qi Li

This book constitutes the refereed post proceedings of the 22nd International Workshop on Digital Forensics and Watermarking, IWDW 2023, held in Jinan, China, during November 25–26, 2023. The 22 full papers included in this book were carefully reviewed and selected from 48 submissions. The workshop focuses on subjects such as novel research, development and application of digital watermarking, data hiding, and forensic techniques for multimedia security.

Trends and Applications in Knowledge Discovery and Data Mining: PAKDD 2024 Workshops, RAFDA and IWTA, Taipei, Taiwan, May 7–10, 2024, Proceedings (Lecture Notes in Computer Science #14658)

by Zhaoxia Wang Chang Wei Tan

This book constitutes the workshops that have been held in conjunction with the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, which took place in Osaka, Japan, during May 25–28, 2023. For RAFDA 2024, Workshop on Research and Applications of Foundation Models for Data Mining and Affective Computing, 15 submissions have been received and 9 full papers have been accepted for publication. For IWTA 2024, International Workshop on Temporal Analytics, 4 full papers have been accepted from a total of 6 submissions.

Robust Design and Assessment of Product and Production by Means of Probabilistic Multi-objective Optimization

by Maosheng Zheng Jie Yu

This book develops robust design and assessment of product and production from viewpoint of system theory, which is quantized with the introduction of brand new concept of preferable probability and its assessment. It aims to provide a new idea and novel way to robust design and assessment of product and production and relevant problems. Robust design and assessment of product and production is attractive to both customer and producer since the stability and insensitivity of a product’s quality to uncontrollable factors reflect its value. Taguchi method has been used to conduct robust design and assessment of product and production for half a century, but its rationality is criticized by statisticians due to its casting of both mean value of a response and its dispersion into one index, which doesn’t characterize the issue of simultaneous optimization of above two independent sub-responses sufficiently for robust design, so an appropriate approach is needed. The preference or role of a response in the evaluation is indicated by using preferable probability as the unique index. Thus, the rational approach for robust design and assessment of product and production is formulated by means of probabilistic multi-objective optimization, which reveals the simultaneous optimization of both mean value of a response and its dispersion in manner of joint probability. Besides, defuzzification and fuzzification measurements are involved as preliminary approaches for robust assessment, the latter provides miraculous treatment for the 'target the best' case flexibly.

Cracking the Machine Learning Code: Technicality or Innovation? (Studies in Computational Intelligence #1155)

by KC Santosh Rodrigue Rizk Siddhi K. Bajracharya

Employing off-the-shelf machine learning models is not an innovation. The journey through technicalities and innovation in the machine learning field is ongoing, and we hope this book serves as a compass, guiding the readers through the evolving landscape of artificial intelligence. It typically includes model selection, parameter tuning and optimization, use of pre-trained models and transfer learning, right use of limited data, model interpretability and explainability, feature engineering and autoML robustness and security, and computational cost – efficiency and scalability. Innovation in building machine learning models involves a continuous cycle of exploration, experimentation, and improvement, with a focus on pushing the boundaries of what is achievable while considering ethical implications and real-world applicability. The book is aimed at providing a clear guidance that one should not be limited to building pre-trained models to solve problems using the off-the-self basic building blocks. With primarily three different data types: numerical, textual, and image data, we offer practical applications such as predictive analysis for finance and housing, text mining from media/news, and abnormality screening for medical imaging informatics. To facilitate comprehension and reproducibility, authors offer GitHub source code encompassing fundamental components and advanced machine learning tools.

The Contribution of Mathematics to School STEM Education: Current Understandings

by Katie Makar Judy Anderson

This book presents contemporary STEM education research conducted by mathematics education researchers and their collaborators which highlights the important and pivotal role of mathematics in school STEM education. It showcases evidence of the types of integrated curriculum approaches to STEM education which highlight mathematics as a key component and where mathematical concepts can be learnt through integrated tasks. These examples challenge the idea that mathematics is just an application or ‘servant’ to the other STEM subjects and highlight the contribution that mathematics can make to the understanding and practices of the other STEM subjects. This book fills a void in the current research literature on the role of mathematics in STEM education, provides evidence of the possibilities for designing integrated STEM curriculum and highlights current understandings of the role of mathematics in school STEM education. For researchers, it identifies and elaborates gaps to encourage further exploration in this field.

Intelligent Systems and Computing (Lecture Notes on Data Engineering and Communications Technologies #207)

by Bing-Yuan Cao Shu-Feng Wang Seyed Hadi Nasseri Yu-Bin Zhong

This book includes high quality research papers submitted at the 2022 “Four Session (ICFIE, ICORG, GDORS, CGHMORS) Celebration” Joint International Conference held on December 28, 2022 and the online meeting of the Fuzzy Information and Engineering Branch of the China Operations Research Society on September 17, 2022. It covers topics in the fields of certainty, stochastic uncertainty, and fuzzy uncertainty, including computer science and mathematics, operations research and control, artificial intelligence, information and engineering technology, barrier-free communication for people with disabilities, digital logistics and knowledge representation, medical applications, queuing theory and game theory, algorithms and optimization methods. The book is a valuable reference book for scholars, engineers, management professionals, and graduate, undergraduate, and vocational students interested in computer science, mathematics, and fuzzy mathematics and operations research, as well as their applications in information technology and engineering.

Dynamical Behaviors of Fractional-Order Complex Dynamical Networks

by Jin-Liang Wang

This book benefits researchers, engineers, and graduate students in the field of fractional-order complex dynamical networks. Recently, the dynamical behaviors (e.g., passivity, finite-time passivity, synchronization, and finite-time synchronization, etc.) for fractional-order complex networks (FOCNs) have attracted considerable research attention in a wide range of fields, and a variety of valuable results have been reported. In particular, passivity has been extensively used to address the synchronization of FOCNs.

Web and Big Data. APWeb-WAIM 2023 International Workshops: KGMA 2023 and SemiBDMA 2023, Wuhan, China, October 6–8, 2023, Proceedings (Communications in Computer and Information Science #2094)

by Jianxin Li Geyong Min Xiangyu Song Ruyi Feng Yunliang Chen

This proceedings constitutes selected papers from the Workshops KGMA and SemiBDMA which were held in conjunction with APWeb-WAIM 2023 which took place in Wuhan, China, during October 6-8, 2023. The 7 full papers included in this book were carefully reviewed and selected from 15 papers submitted to these workshops. They focus on new research approaches on the theory, design, and implementation of data management systems.

Advances in Risk and Reliability Modelling and Assessment: Proceedings of 5th International Conference on Reliability Safety and Hazard (ICRESH 2024) (Lecture Notes in Mechanical Engineering)

by Prabhakar V. Varde Gopika Vinod N. S. Joshi

This book presents the proceedings of the 5th International Conference on Reliability Safety & Hazard-2024, held in Mumbai during February 21–24, 2024. It covers the latest advances in artificial intelligence and machine learning in development of risk-conscious culture. Various topics covered in this volume are reliability prediction, precursor event analysis, fuzzy reliability, structural reliability, passive system reliability, digital system reliability, risk-informed approach to decision making, dynamic PSA, uncertainty and sensitivity modeling, among others. The book is a valuable resource for researchers and professionals working in both academia and industry in the areas of complex systems, safety-critical systems, and risk-based engineering.

Guaranteed Computational Methods for Self-Adjoint Differential Eigenvalue Problems (SpringerBriefs in Mathematics)

by Xuefeng Liu

This monograph presents a study of newly developed guaranteed computational methodologies for eigenvalue problems of self-adjoint differential operators. It focuses on deriving explicit lower and upper bounds for eigenvalues, as well as explicit estimations for eigenfunction approximations. Such explicit error estimations rely on the finite element method (FEM) along with a new theory of explicit quantitative error estimation, diverging from traditional studies that primarily focus on qualitative results. To achieve quantitative error estimation, the monograph begins with an extensive analysis of the hypercircle method, that is, the Prager–Synge theorem. It introduces a novel a priori error estimation technique based on the hypercircle method. This facilitates the explicit estimation of Galerkin projection errors for equations such as Poisson's and Stokes', which are crucial for obtaining lower eigenvalue bounds via conforming FEMs. A thorough exploration of the fundamental theory of projection-based explicit lower eigenvalue bounds under a general setting of eigenvalue problems is also offered. This theory is extensively detailed when applied to model eigenvalue problems associated with the Laplace, biharmonic, Stokes, and Steklov differential operators, which are solved by either conforming or non-conforming FEMs. Moreover, there is a detailed discussion on the Lehmann–Goerisch theorem for the purpose of high-precision eigenvalue bounds, showing its relationship with previously established theorems, such as Lehmann–Maehly's method and Kato's bound. The implementation details of this theorem with FEMs, a topic rarely covered in existing literature, are also clarified. Lastly, the monograph introduces three new algorithms to estimate eigenfunction approximation errors, revealing the potency of classical theorems. Algorithm I extends Birkhoff’s result that works for simple eigenvalues to handle clustered eigenvalues, while Algorithm II generalizes the Davis–Kahan theorem, initially designed for strongly formulated eigenvalue problems, to address weakly formulated eigenvalue problems. Algorithm III utilizes the explicit Galerkin projection error estimation to efficiently handle Galerkin projection-based approximations.

Intelligence Computation and Applications: 14th International Symposium, ISICA 2023, Guangzhou, China, November 18–19, 2023, Revised Selected Papers, Part I (Communications in Computer and Information Science #2146)

by Yong Liu Kangshun Li

This two-volume set, CCIS 2146 and CCIS 2147, constitutes the refereed proceedings of the 14th International Symposium on Intelligence Computation and Applications, ISICA 2023, held in Guangzhou, China, during November 18–19, 2023. The 82 full papers included in these proceedings were carefully reviewed and selected from 178 submissions. The papers presented in these two volumes are organized in the following topical sections: Part I: Frontiers of evolutionary Intelligent Optimization Algorithms; Exploration of computer vision; Machine learning and its applications. Part II: Machine Learning and its applications; Big data analysis and Information security; Intelligent application of computer.

Adult Mortality in India: Trends, Socio-economic Disparities and Consequences (Sustainable Development Goals Series)

by Moradhvaj Dhakad Nandita Saikia

This volume provides a comprehensive overview of the adult mortality situation in India. Each chapter ranges from general adult mortality patterns to its consequences in India. It discusses data-related challenges to studying adult mortality and examines the level, trends, and changing patterns, whether convergence or divergence of adult mortality across the regions from 1981 to 2015. Analyzing the mortality risk across different socioeconomic groups of the population in India, it examines the major underlying causes of adult death with a detailed analysis of external causes of death. The volume enhances the reader's understanding of adult health situations through the lenses of gender, caste, religion, rural-urban, economic status, and region of residence, and its severe consequences at the household level. It is a valuable addition to knowledge on demography, epidemiology, health economics, applied statistics, and public health studies worldwide. It is a must-reference work for Master's and Ph.D. scholars to explore India's and low- and middle-income countries' mortality situations.

Differential Geometry and General Relativity: Volume 1 (Graduate Texts in Physics)

by Canbin Liang Bin Zhou

This book, the first in a three-volume set, explains general relativity using the mathematical tool of differential geometry. The book consists of ten chapters, the first five of which introduce differential geometry, which is widely applicable even outside the field of relativity. Chapter 6 analyzes special relativity using geometric language. In turn, the last four chapters introduce readers to the fundamentals of general relativity. Intended for beginners, this volume includes numerous exercises and worked-out example in each chapter to facilitate the learning experience. Chiefly written for graduate-level courses, the book’s content will also benefit upper-level undergraduate students, and can be used as a reference guide for practicing theoretical physicists.

Intelligent Computing and Networking: Proceedings of IC-ICN 2022 (Lecture Notes in Networks and Systems #632)

by Valentina Emilia Balas Vijay Bhaskar Semwal Anand Khandare

This book gathers high-quality peer-reviewed research papers presented at the International Conference on Intelligent Computing and Networking (IC-ICN 2022), organized by the Computer Department, Thakur College of Engineering and Technology, in Mumbai, Maharashtra, India, on February 25–26, 2022. The book includes innovative and novel papers in the areas of intelligent computing, artificial intelligence, machine learning, deep learning, fuzzy logic, natural language processing, human–machine interaction, big data mining, data science and mining, applications of intelligent systems in healthcare, finance, agriculture and manufacturing, high-performance computing, computer networking, sensor and wireless networks, Internet of Things (IoT), software-defined networks, cryptography, mobile computing, digital forensics and blockchain technology.

A Gentle Introduction to Group Theory

by Bana Al Subaiei Muneerah Al Nuwairan

The book is intended to serve as an introductory course in group theory geared towards second-year university students. It aims to provide them with the background needed to pursue more advanced courses in algebra and to provide a rich source of examples and exercises. Studying group theory began in the late eighteenth century and is still gaining importance due to its applications in physics, chemistry, geometry, and many fields in mathematics. The text is broadly divided into three parts. The first part establishes the prerequisite knowledge required to study group theory. This includes topics in set theory, geometry, and number theory. Each of the chapters ends with solved and unsolved exercises relating to the topic. By doing this, the authors hope to fill the gaps between all the branches in mathematics that are linked to group theory. The second part is the core of the book which discusses topics on semigroups, groups, symmetric groups, subgroups, homomorphisms, isomorphism, and Abelian groups. The last part of the book introduces SAGE, a mathematical software that is used to solve group theory problems. Here, most of the important commands in SAGE are explained, and many examples and exercises are provided.

Advances in Topology and Their Interdisciplinary Applications (Industrial and Applied Mathematics)

by Santanu Acharjee

This book contains selected chapters on recent research in topology. It bridges the gap between recent trends of topological theories and their applications in areas like social sciences, natural sciences, soft computing, economics, theoretical chemistry, cryptography, pattern recognitions and granular computing. There are 14 chapters, including two chapters on mathematical economics from the perspective of topology. The book discusses topics on function spaces, relator space, preorder, quasi-uniformities, bitopological dynamical systems, b-metric spaces and related fixed point theory. This book is useful to researchers, experts and scientists in studying the cutting-edge research in topology and related areas and helps them applying topology in solving real-life problems the society and science are facing these days.

Theories in Ecological Risk Assessment (Theoretical Biology)

by Masashi Kamo

This book introduces various mathematical models used in ecological risk assessment, primarily discussing models used in hazard assessment. The book aims to link ecology and conservation biology with risk assessments, bringing together the knowledge of ecotoxicology and ecology for effective risk assessment. The first part describes population-level assessment in ecological risk assessment. The chapters cover current methodologies for ecological risk assessment, individual-level assessment, population dynamics models for population-level assessment, case studies, mathematical models for population extinctions, the derivation of mean time to extinction (MTE) and their case studies. The second part of the book discusses the mathematical models involved in hazard assessments. It introduces the method of risk assessment using species sensitivity distributions (SSDs), hazard assessment of metals, chemical mixtures using the Michaelis-Menten equation, basic elements of statistics and related topics. Expected readers are risk assessors in governments and public sectors, students and young researchers interested in environmental science. The book is made accessible and easy to follow by beginners in mathematical biology and theoretical ecology.

Marketing and Smart Technologies: Proceedings of ICMarkTech 2022, Volume 1 (Smart Innovation, Systems and Technologies #344)

by José Luís Reis Marisa Del Rio Araujo Luís Paulo Reis José Paulo Marques dos Santos

This book includes selected papers presented at the International Conference on Marketing and Technologies (ICMarkTech 2022), held at Universidade de Santiago de Compostela, Spain, during 1 – 3 December 2022. It covers up-to-date cutting-edge research on artificial intelligence applied in marketing, virtual and augmented reality in marketing, business intelligence databases and marketing, data mining and big data, marketing data science, web marketing, e-commerce and v-commerce, social media and networking, geomarketing and IoT, marketing automation and inbound marketing, machine learning applied to marketing, customer data management and CRM, and neuromarketing technologies.

Proceedings of the 5th International Conference on Numerical Modelling in Engineering: Volume 2: Numerical Modelling in Mechanical and Materials Engineering, NME 2022, 23–24 August, Ghent University, Belgium (Lecture Notes in Mechanical Engineering)

by Magd Abdel Wahab

This book gathers outstanding papers on numerical modeling in Mechanical Engineering (Volume 2) as part of the 2-volume proceedings of the 5th International Conference on Numerical Modeling in Engineering (NME 2021), which was held in Ghent, Belgium, on August 23–24, 2022. The overall objective of the conference was to bring together international scientists and engineers in academia and industry from fields related to advanced numerical techniques, such as the finite element method (FEM), boundary element method (BEM), isogeometric analysis (IGA), and their applications to a wide range of engineering disciplines. This book addresses numerical simulations of various mechanical and materials engineering industrial applications such as aerospace applications, acoustic analysis, bio-mechanical applications, contact problems and wear, heat transfer analysis, vibration and dynamics, transient analysis, nonlinear analysis, composite materials, polymers, metal alloys, fracture mechanics, fatigue of materials, creep, mechanical behavior, micro-structure, phase transformation, and crystal plasticity. The book is intended for academics, including graduate students and researchers, as well as industrial practitioners working in the numerical modeling in mechanical engineering topics.

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