Dynamics Of Information Systems Algorithmic Approaches

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Dynamics of Information Systems: Algorithmic Approaches

Author : Alexey Sorokin
Publisher : Springer Science & Business Media
ISBN 13 : 1461475821
Total Pages : 347 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Dynamics of Information Systems: Algorithmic Approaches by : Alexey Sorokin

Download or read book Dynamics of Information Systems: Algorithmic Approaches written by Alexey Sorokin and published by Springer Science & Business Media. This book was released on 2013-08-23 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dynamics of Information Systems: Algorithmic Approaches presents recent developments and results found by participants of the Fourth International Conference on the Dynamics of Information Systems, which took place at the University of Florida, Gainesville FL, USA on February 20-22, 2012. The purpose of this conference was to bring together scientists and engineers from industry, government, and universities to exchange knowledge and results in a broad range of topics relevant to the theory and practice of the dynamics of information systems.Dynamics of Information plays an increasingly critical role in our society. The influence of information on social, biological, genetic, and military systems must be better understood to achieve large advances in the capability and understanding of these systems. Applications are widespread and include: detection of terrorist networks, design of highly efficient businesses, computer networks, quantum entanglement, genome modeling, multi-robotic systems, and industrial and manufacturing safety. The book contains state-of-the-art work on theory and practice relevant to the dynamics of information systems. It covers algorithmic approaches to numerical computations with infinite and infinitesimal numbers; presents important problems arising in service-oriented systems, such as dynamic composition and analysis of modern service-oriented information systems and estimation of customer service times on a rail network from GPS data; addresses the complexity of the problems arising in stochastic and distributed systems; and discusses modulating communication for improving multi-agent learning convergence. Network issues—in particular minimum-risk maximum-clique problems, vulnerability of sensor networks, influence diffusion, community detection, and link prediction in social network analysis, as well as a comparative analysis of algorithms for transmission network expansion planning—are described in later chapters.

Network Information Systems

Author : Wassim M. Haddad
Publisher : SIAM
ISBN 13 : 1611977541
Total Pages : 637 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Network Information Systems by : Wassim M. Haddad

Download or read book Network Information Systems written by Wassim M. Haddad and published by SIAM. This book was released on 2023-06-06 with total page 637 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents a unique treatment of network control systems. Drawing from fundamental principles of dynamical systems theory and dynamical thermodynamics, the authors develop a continuous-time, discrete-time, and hybrid dynamical system and control framework for linear and nonlinear large-scale network systems. The proposed framework extends the concepts of energy, entropy, and temperature to undirected and directed information networks. Continuous-time, discrete-time, and hybrid thermodynamic principles are used to design distributed control protocol algorithms for static and dynamic networked systems in the face of system uncertainty, exogenous disturbances, imperfect system network communication, and time delays. Network Information Systems: A Dynamical Systems Approach is written for applied mathematicians, dynamical systems theorists, control theorists, and engineers. Researchers and graduate students in a variety of fields who seek a fundamental understanding of the rich behavior of controlled large-scale network systems will also find this book useful. This book can be used for a first course on control design of large-scale network systems, such as control protocols for network systems, network information systems, a dynamical systems approach to network systems, and network thermodynamic systems. The prerequisites are a first course in nonlinear systems theory and a first course in advanced (multivariable) calculus.

Dynamics of Information Systems

Author : Michael Hirsch
Publisher : Springer Science & Business Media
ISBN 13 : 1441956891
Total Pages : 378 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Dynamics of Information Systems by : Michael Hirsch

Download or read book Dynamics of Information Systems written by Michael Hirsch and published by Springer Science & Business Media. This book was released on 2010-04-11 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Dynamics of Information Systems" presents state-of-the-art research explaining the importance of information in the evolution of a distributed or networked system. This book presents techniques for measuring the value or significance of information within the context of a system. Each chapter reveals a unique topic or perspective from experts in this exciting area of research. This volume is intended for graduate students and researchers interested in the most recent developments in information theory and dynamical systems, as well as scientists in other fields interested in the application of these principles to their own area of study.

Algorithmic Information Dynamics

Author : Hector Zenil
Publisher : Cambridge University Press
ISBN 13 : 1108659268
Total Pages : 346 pages
Book Rating : 4.1/5 (86 download)

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Book Synopsis Algorithmic Information Dynamics by : Hector Zenil

Download or read book Algorithmic Information Dynamics written by Hector Zenil and published by Cambridge University Press. This book was released on 2023-05-25 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biological systems are extensively studied as interactions forming complex networks. Reconstructing causal knowledge from, and principles of, these networks from noisy and incomplete data is a challenge in the field of systems biology. Based on an online course hosted by the Santa Fe Institute Complexity Explorer, this book introduces the field of Algorithmic Information Dynamics, a model-driven approach to the study and manipulation of dynamical systems . It draws tools from network and systems biology as well as information theory, complexity science and dynamical systems to study natural and artificial phenomena in software space. It consists of a theoretical and methodological framework to guide an exploration and generate computable candidate models able to explain complex phenomena in particular adaptable adaptive systems, making the book valuable for graduate students and researchers in a wide number of fields in science from physics to cell biology to cognitive sciences.

Dynamic Information Retrieval Modeling

Author : Grace Hui Yang
Publisher : Springer Nature
ISBN 13 : 3031023013
Total Pages : 126 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Dynamic Information Retrieval Modeling by : Grace Hui Yang

Download or read book Dynamic Information Retrieval Modeling written by Grace Hui Yang and published by Springer Nature. This book was released on 2022-05-31 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big data and human-computer information retrieval (HCIR) are changing IR. They capture the dynamic changes in the data and dynamic interactions of users with IR systems. A dynamic system is one which changes or adapts over time or a sequence of events. Many modern IR systems and data exhibit these characteristics which are largely ignored by conventional techniques. What is missing is an ability for the model to change over time and be responsive to stimulus. Documents, relevance, users and tasks all exhibit dynamic behavior that is captured in data sets typically collected over long time spans and models need to respond to these changes. Additionally, the size of modern datasets enforces limits on the amount of learning a system can achieve. Further to this, advances in IR interface, personalization and ad display demand models that can react to users in real time and in an intelligent, contextual way. In this book we provide a comprehensive and up-to-date introduction to Dynamic Information Retrieval Modeling, the statistical modeling of IR systems that can adapt to change. We define dynamics, what it means within the context of IR and highlight examples of problems where dynamics play an important role. We cover techniques ranging from classic relevance feedback to the latest applications of partially observable Markov decision processes (POMDPs) and a handful of useful algorithms and tools for solving IR problems incorporating dynamics. The theoretical component is based around the Markov Decision Process (MDP), a mathematical framework taken from the field of Artificial Intelligence (AI) that enables us to construct models that change according to sequential inputs. We define the framework and the algorithms commonly used to optimize over it and generalize it to the case where the inputs aren't reliable. We explore the topic of reinforcement learning more broadly and introduce another tool known as a Multi-Armed Bandit which is useful for cases where exploring model parameters is beneficial. Following this we introduce theories and algorithms which can be used to incorporate dynamics into an IR model before presenting an array of state-of-the-art research that already does, such as in the areas of session search and online advertising. Change is at the heart of modern Information Retrieval systems and this book will help equip the reader with the tools and knowledge needed to understand Dynamic Information Retrieval Modeling.

Reinforcement Learning and Dynamic Programming Using Function Approximators

Author : Lucian Busoniu
Publisher : CRC Press
ISBN 13 : 1351833820
Total Pages : 335 pages
Book Rating : 4.3/5 (518 download)

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Book Synopsis Reinforcement Learning and Dynamic Programming Using Function Approximators by : Lucian Busoniu

Download or read book Reinforcement Learning and Dynamic Programming Using Function Approximators written by Lucian Busoniu and published by CRC Press. This book was released on 2017-07-28 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has provided researchers with a way to optimally solve decision and control problems involving complex dynamic systems, its practical value was limited by algorithms that lacked the capacity to scale up to realistic problems. However, in recent years, dramatic developments in Reinforcement Learning (RL), the model-free counterpart of DP, changed our understanding of what is possible. Those developments led to the creation of reliable methods that can be applied even when a mathematical model of the system is unavailable, allowing researchers to solve challenging control problems in engineering, as well as in a variety of other disciplines, including economics, medicine, and artificial intelligence. Reinforcement Learning and Dynamic Programming Using Function Approximators provides a comprehensive and unparalleled exploration of the field of RL and DP. With a focus on continuous-variable problems, this seminal text details essential developments that have substantially altered the field over the past decade. In its pages, pioneering experts provide a concise introduction to classical RL and DP, followed by an extensive presentation of the state-of-the-art and novel methods in RL and DP with approximation. Combining algorithm development with theoretical guarantees, they elaborate on their work with illustrative examples and insightful comparisons. Three individual chapters are dedicated to representative algorithms from each of the major classes of techniques: value iteration, policy iteration, and policy search. The features and performance of these algorithms are highlighted in extensive experimental studies on a range of control applications. The recent development of applications involving complex systems has led to a surge of interest in RL and DP methods and the subsequent need for a quality resource on the subject. For graduate students and others new to the field, this book offers a thorough introduction to both the basics and emerging methods. And for those researchers and practitioners working in the fields of optimal and adaptive control, machine learning, artificial intelligence, and operations research, this resource offers a combination of practical algorithms, theoretical analysis, and comprehensive examples that they will be able to adapt and apply to their own work. Access the authors' website at www.dcsc.tudelft.nl/rlbook/ for additional material, including computer code used in the studies and information concerning new developments.

Engineering Artificially Intelligent Systems

Author : William F. Lawless
Publisher : Springer Nature
ISBN 13 : 3030893855
Total Pages : 291 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Engineering Artificially Intelligent Systems by : William F. Lawless

Download or read book Engineering Artificially Intelligent Systems written by William F. Lawless and published by Springer Nature. This book was released on 2021-11-16 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time. To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.

Dynamics, Information and Complexity in Quantum Systems

Author : Fabio Benatti
Publisher : Springer Science & Business Media
ISBN 13 : 1402093063
Total Pages : 535 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Dynamics, Information and Complexity in Quantum Systems by : Fabio Benatti

Download or read book Dynamics, Information and Complexity in Quantum Systems written by Fabio Benatti and published by Springer Science & Business Media. This book was released on 2009-04-17 with total page 535 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a self-contained overview of the entropic approach to quantum dynamical systems. In it, complexity in quantum dynamics is addressed by comparison with the classical ergodic, information, and algorithmic complexity theories.

Dynamics of Information Systems

Author : Chrysafis Vogiatzis
Publisher : Springer
ISBN 13 : 3319100467
Total Pages : 210 pages
Book Rating : 4.3/5 (191 download)

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Book Synopsis Dynamics of Information Systems by : Chrysafis Vogiatzis

Download or read book Dynamics of Information Systems written by Chrysafis Vogiatzis and published by Springer. This book was released on 2014-10-14 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: The contributions of this volume stem from the “Fifth International Conference on the Dynamics of Information Systems” held in Gainesville, FL in February 2013, and discuss state-of the-art techniques in handling problems and solutions in the broad field of information systems. Dynamics of Information Systems: Computational and Mathematical Challenges presents diverse aspects of modern information systems with an emphasis on interconnected network systems and related topics, such as signal and message reconstruction, network connectivity, stochastic network analysis, cyber and computer security, community and cohesive structures in complex networks. Information systems are a vital part of modern societies. They are essential to our daily actions, including social networking, business and bank transactions, as well as sensor communications. The rapid increase in these capabilities has enabled us with more powerful systems, readily available to sense, control, disperse, and analyze information.

Unsupervised Learning

Author : Matthew Kyan
Publisher : John Wiley & Sons
ISBN 13 : 1118875346
Total Pages : 331 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Unsupervised Learning by : Matthew Kyan

Download or read book Unsupervised Learning written by Matthew Kyan and published by John Wiley & Sons. This book was released on 2014-05-02 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new approach to unsupervised learning Evolving technologies have brought about an explosion of information in recent years, but the question of how such information might be effectively harvested, archived, and analyzed remains a monumental challenge—for the processing of such information is often fraught with the need for conceptual interpretation: a relatively simple task for humans, yet an arduous one for computers. Inspired by the relative success of existing popular research on self-organizing neural networks for data clustering and feature extraction, Unsupervised Learning: A Dynamic Approach presents information within the family of generative, self-organizing maps, such as the self-organizing tree map (SOTM) and the more advanced self-organizing hierarchical variance map (SOHVM). It covers a series of pertinent, real-world applications with regard to the processing of multimedia data—from its role in generic image processing techniques, such as the automated modeling and removal of impulse noise in digital images, to problems in digital asset management and its various roles in feature extraction, visual enhancement, segmentation, and analysis of microbiological image data. Self-organization concepts and applications discussed include: Distance metrics for unsupervised clustering Synaptic self-amplification and competition Image retrieval Impulse noise removal Microbiological image analysis Unsupervised Learning: A Dynamic Approach introduces a new family of unsupervised algorithms that have a basis in self-organization, making it an invaluable resource for researchers, engineers, and scientists who want to create systems that effectively model oppressive volumes of data with little or no user intervention.

Models of Science Dynamics

Author : Andrea Scharnhorst
Publisher : Springer Science & Business Media
ISBN 13 : 3642230679
Total Pages : 292 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Models of Science Dynamics by : Andrea Scharnhorst

Download or read book Models of Science Dynamics written by Andrea Scharnhorst and published by Springer Science & Business Media. This book was released on 2012-01-23 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models of Science Dynamics aims to capture the structure and evolution of science, the emerging arena in which scholars, science and the communication of science become themselves the basic objects of research. In order to capture the essence of phenomena as diverse as the structure of co-authorship networks or the evolution of citation diffusion patterns, such models can be represented by conceptual models based on historical and ethnographic observations, mathematical descriptions of measurable phenomena, or computational algorithms. Despite its evident importance, the mathematical modeling of science still lacks a unifying framework and a comprehensive study of the topic. This volume fills this gap, reviewing and describing major threads in the mathematical modeling of science dynamics for a wider academic and professional audience. The model classes presented cover stochastic and statistical models, system-dynamics approaches, agent-based simulations, population-dynamics models, and complex-network models. The book comprises an introduction and a foundational chapter that defines and operationalizes terminology used in the study of science, as well as a review chapter that discusses the history of mathematical approaches to modeling science from an algorithmic-historiography perspective. It concludes with a survey of remaining challenges for future science models and their relevance for science and science policy.

Control in an Information Rich World

Author : Richard M. Murray
Publisher : SIAM
ISBN 13 : 9780898718010
Total Pages : 111 pages
Book Rating : 4.7/5 (18 download)

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Book Synopsis Control in an Information Rich World by : Richard M. Murray

Download or read book Control in an Information Rich World written by Richard M. Murray and published by SIAM. This book was released on 2003-01-01 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of control provides the principles and methods used to design physical and information systems that maintain desirable performance by sensing and automatically adapting to changes in the environment. This report spells out some of the prospects for control in the current and future technological environment, describes the role the field will play in military, commercial, and scientific applications over the next decade, and recommends actions required to enable new breakthroughs in engineering and technology through the application of control research. This brief yet thorough report provides renewed vision, a detailed list of new application areas, and specific recommendations for future research directions in control, dynamics, and systems, compiled by experts in the field.

Optimization in Engineering Sciences

Author : Pierre Borne
Publisher : Wiley-ISTE
ISBN 13 : 9781848214323
Total Pages : 336 pages
Book Rating : 4.2/5 (143 download)

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Book Synopsis Optimization in Engineering Sciences by : Pierre Borne

Download or read book Optimization in Engineering Sciences written by Pierre Borne and published by Wiley-ISTE. This book was released on 2012-12-26 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this book is to present the main methods of static and dynamic optimization. It has been written within the framework of the European Union project – ERRIC (Empowering Romanian Research on Intelligent Information Technologies), funded by the EU’s FP7 Research Potential program and developed in cooperation between French and Romanian teaching researchers. Through the principles of various proposed algorithms (with additional references) this book allows the interested reader to explore various methods of implementation such as linear programming, nonlinear programming – particularly important given the wide variety of existing algorithms, dynamic programming with various application examples and Hopfield networks. The book examines optimization in relation to systems identification; optimization of dynamic systems with particular application to process control; optimization of large scale and complex systems; optimization and information systems.

Algorithmic Aspects of Cloud Computing

Author : Yann Disser
Publisher : Springer
ISBN 13 : 303019759X
Total Pages : 183 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Algorithmic Aspects of Cloud Computing by : Yann Disser

Download or read book Algorithmic Aspects of Cloud Computing written by Yann Disser and published by Springer. This book was released on 2019-04-27 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the 4th International Symposium on Algorithmic Aspects of Cloud Computing, ALGOCLOUD 2018, held in Helsinki, Finland, in August 2018. The 11 revised full papers were carefully reviewed and selected from 29 submissions. The aim of the symposium is to present research activities and results on topics related to algorithmic, design, and development aspects of modern cloud-based systems.

An Elementary Approach to Design and Analysis of Algorithms

Author : Lekh R. Vermani
Publisher : Wspc (Europe)
ISBN 13 : 9781786346759
Total Pages : 0 pages
Book Rating : 4.3/5 (467 download)

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Book Synopsis An Elementary Approach to Design and Analysis of Algorithms by : Lekh R. Vermani

Download or read book An Elementary Approach to Design and Analysis of Algorithms written by Lekh R. Vermani and published by Wspc (Europe). This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In computer science, an algorithm is an unambiguous specification of how to solve a class of problems. Algorithms can perform calculation, data processing and automated reasoning tasks. As an effective method, an algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function. Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states, eventually producing "output" and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate random input. This book introduces a set of concepts in solving problems computationally such as Growth of Functions; Backtracking; Divide and Conquer; Greedy Algorithms; Dynamic Programming; Elementary Graph Algorithms; Minimal Spanning Tree; Single-Source Shortest Paths; All Pairs Shortest Paths; Flow Networks; Polynomial Multiplication, to ways of solving NP-Complete Problems, supported with comprehensive, and detailed problems and solutions, making it an ideal resource to those studying computer science, computer engineering and information technology.

Defense Against Biological Attacks

Author : Sunit K. Singh
Publisher : Springer
ISBN 13 : 3030030539
Total Pages : 327 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Defense Against Biological Attacks by : Sunit K. Singh

Download or read book Defense Against Biological Attacks written by Sunit K. Singh and published by Springer. This book was released on 2019-03-30 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: This first volume of a two-volume set describes general aspects, such as the historical view on the topic, the role of information distribution and preparedness of health-care systems and preparedness in emergency cases. Part two describes and discusseses in detail the pathogens and toxins that are potentially used for biological attacks. As such, the book is a valuable resource for faculties engaged in molecular biology, genetic engineering, neurology, biodefense, biosafety & biosecurity, virology, and infectious disease programs, as well as professional medical research organizations.

Computational Science and Its Applications – ICCSA 2019

Author : Sanjay Misra
Publisher : Springer
ISBN 13 : 3030242897
Total Pages : 845 pages
Book Rating : 4.0/5 (32 download)

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Book Synopsis Computational Science and Its Applications – ICCSA 2019 by : Sanjay Misra

Download or read book Computational Science and Its Applications – ICCSA 2019 written by Sanjay Misra and published by Springer. This book was released on 2019-06-28 with total page 845 pages. Available in PDF, EPUB and Kindle. Book excerpt: The six volumes LNCS 11619-11624 constitute the refereed proceedings of the 19th International Conference on Computational Science and Its Applications, ICCSA 2019, held in Saint Petersburg, Russia, in July 2019. The 64 full papers, 10 short papers and 259 workshop papers presented were carefully reviewed and selected form numerous submissions. The 64 full papers are organized in the following five general tracks: computational methods, algorithms and scientific applications; high performance computing and networks; geometric modeling, graphics and visualization; advanced and emerging applications; and information systems and technologies. The 259 workshop papers were presented at 33 workshops in various areas of computational sciences, ranging from computational science technologies to specific areas of computational sciences, such as software engineering, security, artificial intelligence and blockchain technologies.