Generalized Fixed Point Theorems with Their Applications
In this presented book contains six chapters that areIntroduction, Review of Literature, Random Fixed point theorems and application in Sb metric spaces, Perov Type Results in Gauge Spaces and its Applications to Systems of Integral Equations, Hyers Ulam Stability And Solutions For A Class Of Nonlinear Integral Equations By Fixed Point Technique, Fixed point theorems for the sum of three classes of mixed monotone operators and applications, Tripled Common fixed point results in ordered S-metric spaces. We prove some random fixed point theorems and apply our obtained results to show existence of a unique solution to an initial value problem as an application. We also prove a tripled coincidence and common fixed point theorems for commuting mappings with mixed g-monotone property in partially ordered S-metric spaces. Our obtained results are applied for solving nonlinear fractional differential equations with integral boundary conditions, and also, we give some specific examples.
Qplex: A Computational Modeling and Analysis Methodology for Stochastic Systems
Predicting the cost of cab rides using machine learning
Taxis are an integral part of modern society. And predicting the cost of journeys is of great importance to passengers, taxi drivers and taxi companies. It allows passengers to plan their expenses and avoid unexpectedly high prices. For taxi drivers, it helps them optimise their work, choose more profitable routes and increase their earnings. It helps taxi companies to manage prices, attract more customers and increase their profits. In addition, predicting the cost of taxi rides can be useful for city authorities when planning transport infrastructure and developing urban public transport programmes. Applying machine learning to taxi fare forecasting can take into account many factors such as distance, time of day, weather conditions, demand level and many others to create more accurate and reliable forecasts. Thus, predicting the cost of taxi journeys using machine learning methods is an urgent task that can benefit both individual users and society as a whole.
Multiplication in different logical view
Multiplication process is discussed differently here in the book. This logical view is different from previous and this method describes the multiplication process perfectly. The various types of multiplication is discussed here which is different than our previous knowledge and my logical view on multiplication gives the proper view of product rule of two numbers as well as two different things. Field system is discussed here which is different than our own field system of higher mathematics. Multiplication process perfectly described here with other operation and anyone who knows multiplication can read and think about my logical method. It is a new point of view for multiplication rule and it will help us to understand the view of multiplication process. Reader may read my research paper published in "International Journal of Scientific & Engineering Research" where I also wrote the method and in my book I have discussed the method perfectly to establish a new process of multiplication which is logically perfect than before.
Analyse the Impact of Magnetic Field and Temperature on Fluid Flow
This book explores the intricate interplay between magnetic fields, temperature variations, and fluid dynamics, providing a comprehensive analysis of their combined effects on fluid flow behavior. It delves into the theoretical foundations and practical applications, emphasizing the significance of magneto hydrodynamics (MHD) in engineering, physics, and environmental sciences. Through detailed mathematical models, experimental studies, and simulations, the book highlights the influence of magnetic fields on flow patterns, heat transfer, and stability, along with the role of temperature gradients. The work offers valuable insights for researchers and professionals seeking to optimize fluid systems in areas like energy generation, aerospace, and medical technologies.
Linear Algebra
This is an introductory text on linear algebra and its contemporary applications to data science, artificial intelligence, and more.
Geometric Modeling
This book provides the fundamental knowledge and tools necessary to understand the principles and techniques in the field of geometric modeling and is an essential textbook for undergraduate and graduate students. It includes a detailed exploration of key modeling techniques, from wireframe modeling to complex fractal modeling, highlighting their various applications in different fields and industries. In this book, the basic representation of geometric 3D objects with wireframes as the backbone of more complex models is explored. The details of surface modeling with techniques such as NURBS and subdivision surfaces are discussed. Concepts of constructive solid geometry (CSG) and boundary representation (B-rep) are explained and methods of representing 3D objects with volume are presented. The beauty of fractals and their ability to simulate natural phenomena, produce complex patterns and create stunning visual designs are explained. And finally, the basic and attractive concepts of rendering and visualization have been discussed.
Challenging mathematics
This comprehensive text delves into the intricate world of higher mathematics, offering a rigorous exploration of advanced concepts crucial for today's aspiring mathematicians and scientists. From abstract algebra to complex analysis, the book covers a wide spectrum of topics, providing readers with a solid foundation for further academic pursuits and real-world problem-solving. Written for upper-level undergraduate and graduate students, this volume stands out for its clear explanations of challenging theories and its emphasis on practical applications. The authors expertly balance theoretical depth with insightful examples, making abstract ideas accessible without sacrificing mathematical rigor.By mastering the contents of this book, readers will not only enhance their mathematical prowess but also develop critical thinking skills essential for tackling complex problems in various scientific and technological fields.Whether you're aiming for a career in pure mathematics, physics, engineering, or data science, this text is an indispensable resource for pushing the boundaries of your mathematical understanding.
Mathematics for the Engineers I
Mathematics is the language of engineering and a compulsory subject in worldwide engineering education. So as engineering students, it is mandatory to study Mathematics and learn Mathematical calculations meticulously. In engineering, there are several branches such as computer engineering, electrical and electronic engineering, mechanical engineering, communication engineering and civil engineering and each branch has a different study set focused on the significance of Mathematics. Mathematics provides the analytical and problem-solving tools necessary for engineers to design, analyze and optimize systems, ensuring that they meet safety, efficiency and performance requirements. Without mathematics, engineers would struggle to design effective control systems, leading to inefficiencies and instability in processes. This book provides the easiest and comfortable techniques to the students to learn mathematical calculations effortlessly and independently at home. Moreover, the necessary formulas have been included here with the very beginning of this book so that students can get a complete idea of calculations without the help of other study materials.
Mathematics for the Engineers II
Mathematics is the language of engineering and a compulsory subject in worldwide engineering education. So as engineering students, it is mandatory to study Mathematics and learn Mathematical calculations meticulously. In engineering, there are several branches such as computer engineering, electrical and electronic engineering, mechanical engineering, communication engineering and civil engineering and each branch has a different study set focused on the significance of Mathematics. Mathematics provides the analytical and problem-solving tools necessary for engineers to design, analyze and optimize systems, ensuring that they meet safety, efficiency and performance requirements. Without mathematics, engineers would struggle to design effective control systems, leading to inefficiencies and instability in processes. This book provides the easiest and comfortable techniques to the students to learn mathematical calculations effortlessly and independently at home. Moreover, the necessary formulas have been included here with the very beginning of this book so that students can get a complete idea of calculations without the help of other study materials.
Applied Satisfiability
Apply satisfiability to a range of difficult problems The Boolean Satisfiability Problem (SAT) is one of the most famous and widely-studied problems in Boolean logic. Optimization versions of this problem include the Maximum Satisfiability Problem (MaxSAT) and its extensions, such as partial MaxSAT and weighted MaxSAT, which concern not merely whether but to what extent a solution satisfies a given set of problems. Numerous applications of SAT and MaxSAT have emerged in fields related to logic and computing technology. Applied Satisfiability: Cryptography, Scheduling and Coalitional Games outlines some of these applications in three specific fields. It offers a huge range of SAT applications and their possible impacts, allowing readers to tackle previously challenging optimization problems with a new selection of tools. Professionals and researchers in this field will find the scope of their computational solutions to otherwise intractable problems vastly increased. Applied Satisfiability readers will also find: Coding and problem-solving skills applicable to a variety of fields Chapters covering topics including cryptographic key recovery, various forms of scheduling, coalition structure generation, and many more Specific experiments and case studies that demonstrate the effectiveness of satisfiability-aided methods Applied Satisfiability is ideal for researchers, graduate students, and practitioners in these fields looking to bring a new skillset to bear in their studies and careers.
Is Math Real?
One of the world's most creative mathematicians offers a new way to look at math--focusing on questions, not answers        Winner of the Los Angeles Times Book Prize A New Scientist Best Book of the Year    "Brilliant."--Popular Science   Where do we learn math: From rules in a textbook? From logic and deduction? Not really, according to mathematician Eugenia Cheng: we learn it from human curiosity--most importantly, from asking questions. This may come as a surprise to those who think that math is about finding the one right answer, or those who were told that the "dumb" question they asked just proved they were bad at math. But Cheng shows why people who ask questions like "Why does 1 + 1 = 2?" are at the very heart of the search for mathematical truth.        Is Math Real? is a much-needed repudiation of the rigid ways we're taught to do math, and a celebration of the true, curious spirit of the discipline. Written with intelligence and passion, Is Math Real? brings us math as we've never seen it before, revealing how profound insights can emerge from seemingly unlikely sources.       
Measuring and Modeling by Examples
This book starts with an anthology of mathematical functions that can be useful to describe phenomena that occur in the world we see, and how their features can be adjusted by changing their parameters. Then we have a look at the art of measuring and quantifying the world, and how to do this most efficiently and precisely.The most important part is about finding the "pattern" in the measurements: a mathematical function that "fits" with the data. This can be chosen according to several criteria, and using different algorithms, for example the new "multidirectional least squares regression". The last part shows many real life examples in various fields of science: experiments and their analyses.
Mathematical Analysis
This book provides an overview of the most up-to-date developments in the field, presenting original contributions and surveys from a spectrum of respected academics in Mathematical Analysis. Each chapter highlights new research directions, making this book suitable for graduate students, faculty, and researchers.
Fundamentals of Multivariable Calculus
This textbook is carefully designed as an early undergraduate introduction to the calculus of several real variables. The balanced coverage is devoted to limits, continuity, partial derivatives, extrema, the nabla operator, multiple integrals, line integrals, surface integrals, and the fundamental theorems of vector calculus.Engaging and accessible with detailed diagrams and copious worked examples, the presentation is well suited to students pursuing applied fields such as engineering. Multiple integration is motivated intuitively through the calculation of mass. The chapter-end problems provide both drill and challenge.Overall, the book should equip students with the knowledge and confidence needed for subsequent courses.An appendix on hints renders the book suitable for self-study. Prerequisites are limited to single-variable calculus, linear algebra, and analytic geometry.
Contributions to the Theory of Partitions and Their Applications
The theory of partitions, which studies the ways in which integers can be expressed as sums of other integers, has profound implications in various fields of mathematics. Significant contributions by mathematicians such as Euler and Hardy have paved the way for a deeper understanding of partition functions and their properties. Recent advancements have explored partitions in combinatorial contexts, offering insights into generating functions and generalized partition functions, including k-color overpartitions, Andrews' singular overpartitions, designated summands, l-regular cubic partition pairs, (l; m)-regular bipartition triples, and partition quadruples with t-cores.
Complex Analysis
The book comprises six chapters, each meticulously structured to build a comprehensive understanding of complex analysis. Chapter 1 covers the most fundamental concepts, providing the essential groundwork that permeates the entire text. Chapter 2 delves into normal families, the Riemann mapping theorem, and conformal mapping. Chapter 3 focuses on the zeros of analytic functions, while Chapter 4 explores the essential properties of harmonic and subharmonic functions. Chapter 5 introduces H^p spaces and the Fourier transform, highlighting their interconnections. The final chapter discusses uniform approximation by rational functions.Emphasizing foundational theories, modern methods, and key ideas in complex analysis, this book also presents some cutting-edge research problems and recent advancements. The topics are thoughtfully selected, and the exposition is clear and rigorous. This book is an excellent resource for graduate students and independent learners alike. It features many new and concise proofs of classical theorems, and offers numerous challenging exercises to deepen understanding.
Mathematics of Business
Businesses are always indispensable entity in any society. Money may be given to loaf without being useful to anyone. The major and the fundamental principles of any form of banking is that every idle money usually yields in most cases no increase. Thus, any individual who possesses certain amount of money than is needed for day to day activities as well as the necessities for living may not just put them away in safe places. Financial Mathematics plays a vital role in Economics and Commerce. Certain Economic terminologies with usual notations are necessary and imperative tools for any form of demonstrations of the applications of the financial Mathematics.
The Cognitive Dimension of Social Argumentation Proceedings of the 4th European Conference on Argumentation Volume II
This is Volume II of the proceedings of the 4th European Conference on Argumentation, "The cognitive dimension of social argumentation", held at the University of Roma Tre in September 2022. The European Conference on Argumentation (ECA) is an international initiative aiming to consolidate and advance various strands of research on argumentation and reasoning by gathering scholars from a range of disciplines such as philosophy, communication, linguistics, computer science, cognitive science, discourse analysis, and more. The 2022 Rome edition focused on the sociocognitive factors that affect argumentation, both in terms of dynamics and outcomes. Taken together, the contributions collected in these three volumes of the ECA 2022 proceedings provide a faithful approximation of the breadth and depth of ongoing discussions in argumentation scholarship. They also attest how the markedly interdisciplinary character of this field has been evolving in recent years: whereas philosophy and linguistics were always partners in the study of argument, nowadays they are supported also by computer science and experimental psychology, as well as communication and media studies in a broader sense - all of which are well represented in this volume.
The Cognitive Dimension of Social Argumentation Proceedings of the 4th European Conference on Argumentation Volume III
This is Volume III of the proceedings of the 4th European Conference on Argumentation, "The cognitive dimension of social argumentation", held at the University of Roma Tre in September 2022. The European Conference on Argumentation (ECA) is an international initiative aiming to consolidate and advance various strands of research on argumentation and reasoning by gathering scholars from a range of disciplines such as philosophy, communication, linguistics, computer science, cognitive science, discourse analysis, and more. The 2022 Rome edition focused on the sociocognitive factors that affect argumentation, both in terms of dynamics and outcomes. Taken together, the contributions collected in these three volumes of the ECA 2022 proceedings provide a faithful approximation of the breadth and depth of ongoing discussions in argumentation scholarship. They also attest how the markedly interdisciplinary character of this field has been evolving in recent years: whereas philosophy and linguistics were always partners in the study of argument, nowadays they are supported also by computer science and experimental psychology, as well as communication and media studies in a broader sense - all of which are well represented in this volume.
The Cognitive Dimension of Social Argumentation Proceedings of the 4th European Conference on Argumentation Volume I
This is Volume I of the proceedings of the 4th European Conference on Argumentation, "The cognitive dimension of social argumentation", held at the University of Roma Tre in September 2022. The European Conference on Argumentation (ECA) is an international initiative aiming to consolidate and advance various strands of research on argumentation and reasoning by gathering scholars from a range of disciplines such as philosophy, communication, linguistics, computer science, cognitive science, discourse analysis, and more. The 2022 Rome edition focused on the sociocognitive factors that affect argumentation, both in terms of dynamics and outcomes. Taken together, the contributions collected in these three volumes of the ECA 2022 proceedings provide a faithful approximation of the breadth and depth of ongoing discussions in argumentation scholarship. They also attest how the markedly interdisciplinary character of this fi eld has been evolving in recent years: whereas philosophy and linguistics were always partners in the study of argument, nowadays they are supported also by computer science and experimental psychology, as well as communication and media studies in a broader sense - all of which are well represented in this volume.
Summary Statistics
Statistics is used to conduct research, evaluate outcomes, develop critical thinking and make informed decisions about a set of data. The main purpose of statistics seeks to provide an analysis of quantitative data. The principles of statistics also provide guidelines for conducting surveys. Statisticians know how to gather information while avoiding bias and using a random sample. There are a variety of benefits of studying statistics. It improves ability to identify and communicate patterns and outcomes. Learning statistics also incorporates the use of probability. Businesses and individuals can use statistics to calculate the probability of their desired outcome and evaluate whether the probable benefits outweigh the cost. This cost-benefit analysis can improve decision-making and reduce losses. Statistical inference is a calculation that uses data analysis to infer the root causes, effects and properties of a correlation or statistical trend. Statistical models can offer more accurate projections of sales, results and returns. Statistics focuses on a cause-and-effect relationship between variables.
Complex Analysis and Special Functions
The first two parts of this book focus on developing standard analysis concepts in the extended complex plane. We cover differentiation and integration of functions of one complex variable. Famous Cauchy formulas are established and applied in the frame of residue theory. Taylor series is used to investigate analytic functions, and they are connected to harmonic functions. Laurent series theory is developed. The third part of the book finds applications of the earlier chapter in conformal mappings and the Laplace transform. Special functions solving ordinary differential equations are studied extensively, along with their asymptotic behavior. A highlight of the book is the elliptic function of Weierstrass and Jacobi. Finally, we present Laplace's method, which is applied to find large arguments asymptotic of some special functions. The book is filled with examples, exercises, and problems of varying degrees of difficulty. This makes it useful to all students in mathematics, physics, and related fields.
Mathematical Optimization Theory and Operations Research: Recent Trends
This book constitutes the revised selected papers from the 23rd International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2024, held in Omsk, Russia from June 30 to July 06, 2024. The 26 full papers included in this book were carefully reviewed and selected from 79 submissions. These papers have been organized in the following topical sections: Mathematical programming; Combinatorial optimization; Operations research; and Machine learning and optimization.
Quadratic Ideal Numbers
This book introduces quadratic ideal numbers as objects of study with applications to binary quadratic forms and other topics. The text requires only minimal background in number theory, much of which is reviewed as needed. Computational methods are emphasized throughout, making this subject appropriate for individual study or research at the undergraduate level or above.
Exploring Stochastic Approaches to Epidemic Modeling
Stochastic calculus has become an essential mathematical tool for modeling complex biological systems characterized by randomness and uncertainty. Unlike deterministic models, which may overlook the variability inherent in biological processes, stochastic calculus allows for explicitly incorporating noise and random fluctuations into the governing equations. This approach has proven particularly effective in fields such as population dynamics, gene regulation, neural activity, and the transmission of infectious diseases, where systems are influenced by random factors at both micro and macro scales. Researchers can use stochastic differential equations (SDEs) and It繫 calculus to model biological systems' temporal evolution, accounting for deterministic components and stochastic disturbances. Applying stochastic calculus in biological modeling improves the precision of predictions and deepens our understanding of the mechanisms driving biological variability. As the discipline progresses, stochastic calculus is expected to play a growing role in enhancing our comprehension of complex biological phenomena and optimizing interventions in medicine, ecology, and biotechnology.
Deep Learning Technology and Image Sensing
In this Special Issue, we explore the transformative power of deep learning-based computing technologies in improving the accuracy and reliability of image recognition systems. From advancing autonomous driving to enhancing object detection, deep learning continues to push the boundaries of what is achievable. Additionally, cutting-edge computer vision technologies enable precise medical imaging segmentation and improve image quality in challenging conditions, such as low-light environments and astronomical observations. Leading experts in the field present their latest research and innovations, offering a comprehensive view of the applications and future potential of deep learning in image and video sensing technologies. Together, we envision a future where artificial intelligence not only enhances our everyday devices but also redefines how we interact with technology and the world around us.
The Dynamics of Front Propagation in Nonlocal Reaction-Diffusion Equations
Quantitative Data Analysis
This handbook is designed to provide students and others with an introduction to the fundamental concepts of quantitative data analysis. Aimed primarily at students who will be carrying out field surveys and collecting data, it is also an introductory guide to sampling methods, without requiring advanced prior knowledge of statistics or mathematics. The manual is designed to be accessible and educational, with practical illustrations to help students understand and assimilate the concepts.
The Making, The Rise, And the Future of The Speaking Man - Fifth Edition
The making, rise, and future of the speaking man encapsulates not just the biological and cognitive evolution of Homo sapiens but also the dynamic relationship between culture, technology, and society. From the early developments of vocal communication to the creation of language-based civilizations and the potential of futuristic technologies, human speech is at the core of how we define ourselves as a species. Looking ahead, the speaking man will continue to evolve, shaped by forces both biological and technological, creating new possibilities for how we communicate and connect with each other-and with the world around us.
Manual of analysis methods and techniques
This book is the synthesis of years of teaching analytical methods and techniques, aimed at second-year Master's students in animal production and nutrition in the Department of Agronomic Sciences and Biotechnology. It aims to support the learning of various biological, biochemical and enzyme-linked immunosorbent analysis techniques and methods. The aim is to introduce students to laboratory work, particularly in the context of their final dissertation.The manuscript is divided into four main chapters, arranged chronologically by analytical method, as follows: 1- Spectral methods. 2- Fractionation methods. 3- Labeling methods.4- Electron microscopy.Like any work, it may contain errors and gaps. So it's always encouraging and motivating to receive corrections, advice and recommendations from fellow teachers and researchers working in the field.
An Orthogonal Projection Algorithm for Solving Quadratic Program
This book deals with the construction of an orthogonal projection algorithm for solutions of quadratic programming problems. The algorithm starts by finding the unconstrained optimum using the classical theory of differentiation and then tests the solution for feasibility in the constrained problem. If the unconstrained optimum is infeasible in the constrained problem, then the algorithm makes a move to search for the optimum solution which in most situations is achievable in only one step. The work-ability of the algorithm is shown by applying it in solving several quadratic programming problems. The solutions obtained by using the Projection Algorithm are compared with those obtained by using OPTIMIZER software. The projection algorithm is found to give the same or better optimal solutions than the OPTIMIZER.
Geometry learning mediated by Cabri-G矇om癡tre software
This study is the result of research that culminated in our master's dissertation, which looked at the various phases of learning in the light of Guy Brousseau's theory of didactic situations. It was developed from a qualitative perspective, prioritizing the context of the relationships and interactions that took place in a learning environment, supported by dynamic geometry software, with the involvement of 37 students from a school in Curitiba. There were six sessions of observation of mathematics classes that dealt with the teaching of quadrilaterals. The analysis showed that the students who already had a command of the computer and did so with skill, had difficulties when dealing with the software. This suggests a "student-machine" paradox, that is, even though they have the skills to deal with the computer, the student is challenged with the minimum skills required to deal with the software. Faced with this situation, new didactic contracts emerge to replace the previous ones. The study shows that the didactic contracts established between student, teacher and knowledge, when broken, open up as an opportunity to take new paths towards full learning.
Machine Learning for Cybersecurity
"Machine Learning for Cybersecurity: Threat Detection and Mitigation" delves into the transformative role of machine learning in addressing contemporary cybersecurity challenges. This reprint provides an in-depth exploration of how advanced techniques such as deep learning, natural language processing, and explainable AI are revolutionizing intrusion detection, anomaly detection, and threat intelligence. With a focus on practical applications, it covers critical topics such as malware analysis, IoT and cloud security, blockchain security, adversarial attacks, and secure data sharing. Through this reprint, readers will gain insights into cutting-edge approaches for vulnerability assessments, authentication, and privacy preservation while exploring frameworks for implementing security-aware AI systems.This comprehensive resource is essential for researchers, practitioners, and policymakers striving to strengthen digital ecosystems. It offers both theoretical insights and actionable solutions, paving the way for innovative cybersecurity strategies to combat an ever-evolving threat landscape.
Lectures on Advanced Topics in Categorical Data Analysis
This book continues the mission of the previous text by the author, Lectures on Categorical Data Analysis, by expanding on the introductory concepts from that volume and providing a mathematically rigorous presentation of advanced topics and current research in statistical techniques which can be applied in the social, political, behavioral, and life sciences. It presents an intuitive and unified discussion of an array of themes in categorical data analysis, and the emphasis on structure over stochastics renders many of the methods applicable in machine learning environments and for the analysis of big data. The book focuses on graphical models, their application in causal analysis, the analytical properties of parameterizations of multivariate discrete distributions, marginal models, and coordinate-free relational models. To guide the readers in future research, the volume provides references to original papers and also offers detailed proofs of most of the significant results. Like the previous volume, it features exercises and research questions, making it appropriate for graduate students, as well as for active researchers.
Engineering Data Analysis with MATLAB(R)
This uses MATLAB(R) for data analysis and statistics, offering a broad review of computational data analysis, in particular algebra, trigonometry, regression modeling, correlation, and graphical representation of results, covering both basic and more complex material, with a large number of worked examples and practice exercises.
Multiaxial Notch Fracture and Fatigue
This book presents unified fatigue life prediction equations for a low/medium/high cycle fatigue of metallic materials, relevant to plain materials and notched components.
Mathematical Data Science with Applications in Business, Industry, and Medicine
Mathematical data science is a field that combines mathematical techniques with data science methods to extract insights and knowledge from data. It involves working with data at all stages of the data lifecycle, from collection and storage to cleansing and processing, the analysis and visualization of data, and the communication of the results and findings. Data scientists use a variety of tools and techniques to analyze data, including mathematical concepts and models, artificial intelligence techniques, machine learning algorithms, statistical analysis, and data visualization. Furthermore, data science can be used to make predictions, identify patterns, and draw conclusions from data, and it is applied in a variety of areas, including business, industry, and medicine. It is a rapidly evolving field, and data scientists are expected to stay up to date with new tools, techniques, and technologies. This Reprint is a collection of articles on a wide range of topics in the field of mathematical data science, with applications in business, industry, and medicine. The proposed methods and concepts are discussed in detail and illustrated with several real-life data examples.
Production scheduling for parallel machines
This book presents a comparison of hybrid solution methods for integrated multi-machine production sizing and scheduling problems with sequence-dependent setups. The proposed methods are based on the decomposition of the problem into 2 levels: In the first level, the assignment of jobs to machines and their sequencing is performed via genetic algorithms, the solution obtained at this level is used to determine the sizing of batches and inventories in the second level in an exact way using the branch and cut method.The results showed the variant based on the Teaching-learning based optimization (TLBO) algorithm as the best in performance with a good solution quality in a reasonable computation time.
Database Systems for Advanced Applications
The seven-volume set LNCS 14850-14856 constitutes the proceedings of the 29th International Conference on Database Systems for Advanced Applications, DASFAA 2024, held in Gifu, Japan, in July 2024. The total of 147 full papers, along with 85 short papers, presented together in this seven-volume set was carefully reviewed and selected from 722 submissions. Additionally, 14 industrial papers, 18 demo papers and 6 tutorials are included. The conference presents papers on subjects such as: Part I: Spatial and temporal data; database core technology; federated learning. Part II: Machine learning; text processing. Part III: Recommendation; multi-media. Part IV: Privacy and security; knowledge base and graphs. Part V: Natural language processing; large language model; time series and stream data. Part VI: Graph and network; hardware acceleration. Part VII: Emerging application; industry papers; demo papers.
Graph Theory
This standard textbook on modern graph theory combines the authority of a classic with the engaging freshness of style that is the hallmark of active mathematics. It covers the core material of the subject, with concise yet complete proofs, while offering glimpses of more advanced methods in each field via one or two deeper results. This is a major new edition. Among many other improvements, it offers additional tools for applying the regularity lemma, brings the tangle theory of graph minors up to the cutting edge of current research, and addresses new topics such as chi-boundedness in perfect graph theory. The book can be used as a reliable text for an introductory graduate course and is also suitable for self-study. From the reviews: "Deep, clear, wonderful. This is a serious book about the heart of graph theory. It has depth and integrity." Persi Diaconis & Ron Graham, SIAM Review "The book has received a very enthusiastic reception, which it amply deserves. A masterly elucidation of modern graph theory." Bulletin of the Institute of Combinatorics and its Applications "Succeeds dramatically ... a hell of a good book." MAA Reviews " ... like listening to someone explain mathematics." Bulletin of the AMS
Computational Methods for Transition States and Pathways in Rare Events
Based on the calculation of transition states and the identification of transition paths, the book aims to provide a comprehensive guide to understanding and simulating rare events.
Mathematical Optimizations
Mathematical optimization is a crucial field that focuses on finding the best possible solutions from a range of options. At its essence, optimization involves maximizing or minimizing a specific goal while considering various constraints or limitations. This process is widely applicable across many areas, including business, engineering, healthcare, and logistics. The optimization process starts by defining the problem clearly, identifying the key variables involved, and understanding the constraints that may impact the potential. One of the most common methods used in this field is linear programming, which involves problems where both the goals and constraints are expressed as linear relationships. This approach is particularly useful for tasks like resource allocation, where the objective is to use limited resources in the most efficient way. In contrast, nonlinear programming deals with problems that involve complex relationships between variables, allowing for a wider range of potential solutions.
