Perpustakaan Digital

In the era of Internet of Things (IoT) that we have entered, the “Monitoring–Decision–Execution” cycle of typical autonomic and automation systems is extended to include distributed developments that might scale from a smart home or greenhouse to a smart city, and from autonomous driving to emergency management. In such highly distributed and scalable architectures, each of the three processes can be situated at any physical or virtual computing system and located, ideally, at any place. Hence, communication and interoperation between the subsystems that comprise the total IoT system, namely extreme edge, edge, fog, and cloud deployments, are of critical importance. This reprint presents a collection of high-quality, state-of-the-art research papers, each introducing challenging issues in pervasive computing across the different domains of the IoT ecosystem. It comprises four papers focusing on customized application frameworks, three papers dealing with issues of ambient intelligence and assisted living of the aging population, three papers considering blockchain technology in various IoT applications, and two survey papers related to sensors and their applications.

The aim of this book is to highlight up to date exploited technologies and approaches in terms of antenna designs and requirements. In this regard, this book targets a broad range of subjects, including the microstrip antenna and the dipole and printed monopole antenna. The varieties of antenna designs, along with several different approaches to improve their overall performance, have given this book a great value, in which makes this book is deemed as a good reference for practicing engineers and under/postgraduate students working in this field. The key technology trends in antenna design as part of the mobile communication evolution have mainly focused on multiband, wideband, and MIMO antennas, and all have been clearly presented, studied and implemented within this book. The forthcoming 5G systems consider a truly mobile multimedia platform that constitutes a converged networking arena that not only includes legacy heterogeneous mobile networks but advanced radio interfaces and t

This Reprint presents a comprehensive and timely synthesis of the Special Issue Vision Science and Optometry, featuring 17 carefully selected peer-reviewed contributions. This collection captures the most recent investigative and clinical advances in vision science and optometric research, including topics such as binocular vision, eye movements, eye tracking, anterior and posterior pole examinations, accommodation, lighting effects, circadian light, color vision, aberrometry, ocular surface dynamics, contact lens technologies, and refractive surgery techniques. The assembled articles reflect high-quality original research and critical reviews, aimed at enhancing the knowledge base of researchers, eye care professionals, and clinicians. By consolidating these insights in a unified Reprint, we facilitate easy access to state-of-the-art content, support professional development, and encourage integration of emerging findings into daily practice and future research endeavors. This Reprint serves as a valuable reference for advancing clinical outcomes and fostering interdisciplinary collaboration within the vision science and optometry community.

This volume comprises the fifth collection of papers submitted by the Editorial Board Members (EBMs) of the journal Mathematical and Computational Applications (MCA), as well as outstanding scholars working in the core research fields of MCA. This collection typifies the most insightful and influential original articles regarding key topics in these fields.

Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of the increased dissemination and distribution of multimedia content over the internet, data hiding methods, such as digital watermarking and steganography, are becoming increasingly relevant in providing multimedia security. The goal of this book is to focus on the improvement of data hiding algorithms and their different applications (both traditional and emerging), bringing together researchers and practitioners from different research fields, including data hiding, signal processing, cryptography, and information theory, among others. Related Books Cryptography and Its Applications in Information Security Computer Science & Mathematics ... Image and Video Forensics Engineering Digital Image Processing Computer Science & Mathematics ... Advanced Mathematical Methods in Intelligent Multime

Big data approaches and artificial intelligence are rapidly reshaping the way geoscientists analyze, model, and interpret the Earth. This Special Issue focuses on the practical application of big data mining, machine learning, and artificial intelligence in Earth science. It aims to explore the role of big data paradigms in guiding model development, the integration of domain knowledge into AI systems, and the validation of AI methodologies within geoscientific contexts. Comprising 17 papers, the Reprint highlights transformative advances in areas such as mineral prospectivity prediction with metallogenic belt identification, geological data inversion, modeling and deep learning architectures, and combining geological databases with big data mining. It further introduces knowledge graphs and large language models as emerging tools that enhance data integration, interpretation, and knowledge discovery. By presenting AI-driven geology as a forward-looking paradigm, the collection demonstrates how artificial intelligence can revolutionize traditional geoscience practices by providing improved accuracy and deeper insight. Through practical examples and case studies, the Reprint illustrates the application of these technologies to complex geoscientific problems. It equips researchers, practitioners, and students with cutting-edge knowledge and tools to harness big data and machine learning, fostering innovation and advancing understanding across the geoscience disciplines.

The development and application of advanced numerical and computer methods in civil engineering have become increasingly more important for modern engineers and researchers in recent decades. Advanced numerical and computer methods can be used, from the material level to the structural level, for solving nearly all engineering problems, solely or in combination with experimental/theoretical studies. In this Special Issue, we have successfully collected 10 excellent papers that present recent progress either in the novel development or the novel application of advanced numerical and computer methods for solving problems in civil engineering. Related Books Advanced Numerical and Computational Methods for Engineering and Applied Mathematical Problems Computer Science & Mathematics Numerical Simulation and Computational Methods in Engineering and Sciences Computer Science & Mathematics ... Advanced Numerical Methods in Applied Sciences Computer Science & Mathematics Numerical and Comput

This reprint concerns methods of data analysis for risk management in economics, finance, and business. The presented papers contain research on data analysis methods, including classical statistical methods, and machine learning methods that have emerged from statistics and are being effectively applied using high-speed computers, considering the availability of big data. Related Books Big Data Analytics and Information Science for Business and Biomedical Applications II Biology & Life Sciences ... Financial Data Analytics and Statistical Learning Business & Economics Big Data Analytics and Information Science for Business and Biomedical Applications Computer Science & Mathematics Data Analysis and Mining Computer Science & Mathematics Statistical Methods in Data Science and Applications Computer Science & Mathematics The recommendations have been generated using an AI system. About: About MDPI Books Advisory Board Legal Information: MDPI Privacy Policy Terms and Conditions Te

The increasing demand for high data rate applications and the delivery of zero-latency multimedia content drives technological evolutions towards the design and implementation of next-generation broadband wireless networks. In this context, various novel technologies have been introduced, such as millimeter wave (mmWave) transmission, massive multiple input multiple output (MIMO) systems, and non-orthogonal multiple access (NOMA) schemes in order to support the vision of fifth generation (5G) wireless cellular networks. The introduction of these technologies, however, is inextricably connected with a holistic redesign of the current transceiver structures, as well as the network architecture reconfiguration. To this end, ultra-dense network deployment along with distributed massive MIMO technologies and intermediate relay nodes have been proposed, among others, in order to ensure an improved quality of services to all mobile users. In the same framework, the design and evaluation of

This Reprint presents a carefully curated collection of peer-reviewed, open access articles from the Electronics Special Issue “Security Challenges and Opportunities of Artificial Intelligence/Big Data Scenarios”, capturing state-of-the-art research at the intersection of artificial intelligence, big data analytics, cybersecurity, privacy engineering, and trustworthy intelligent systems. The contributions in this volume address a broad spectrum of critical topics, including adversarial machine learning, data leakage and privacy preservation, secure model training and deployment, authentication and access control in AI-driven systems, ethical risks and bias mitigation, regulatory compliance for big data platforms, and resilience against cyber threats in cloud, edge, and IoT environments. Beyond technical defenses and vulnerability detection, this Reprint highlights the dual nature of AI and big data: while these technologies introduce novel attack surfaces and systemic security risks, they also empower advanced threat intelligence, automated anomaly detection, predictive security analytics, and robust risk management across public service scenarios. We express our sincere gratitude to all contributing authors for their impactful work, to the reviewers for their rigorous and constructive feedback, and to the editorial and publishing teams at MDPI for their dedicated support throughout the process.

This Special Issue serves as a valuable resource for readers seeking to delve into the exciting field of flexible and wearable electronics and contribute to their further advancements. This Special Issue presents research papers, short communications, and review articles focusing on the following themes: (1) Novel structural designs, material fabrication, signal processing, and modeling of flexible and wearable sensors applying a wide range of mechanisms to flexible and wearable electronics;(2) MEMS techniques used in the production process of wearable and flexible sensors, along with simulation analysis with theoretical modeling;(3) Multiple application scenarios utilizing multivariable flexible and wearable sensor systems. Related Books Flexible and Wearable Sensors Engineering Wearable Sensors for Human Health Monitoring and Analysis Engineering Bioelectronics & Wearable Devices: Sensing, Signal Processing and Powering Engineering Flexible Electronics Engineering Wearable Sensing

Additive manufacturing (AM) or, more commonly, 3D printing is one of the fundamental elements of Industry 4.0. and the fourth industrial revolution. It has shown its potential example in the medical, automotive, aerospace, and spare part sectors. Personal manufacturing, complex and optimized parts, short series manufacturing and local on-demand manufacturing are some of the current benefits. Businesses based on AM have experienced double-digit growth in recent years. Accordingly, we have witnessed considerable efforts in developing processes and materials in terms of speed, costs, and availability. These open up new applications and business case possibilities all the time, which were not previously in existence. Most research has focused on material and AM process development or effort to utilize existing materials and processes for industrial applications. However, improving the understanding and simulation of materials and AM process and understanding the effect of different steps

In this Special Issue, one review paper highlights the necessity of multiscale CFD, coupling micro- and macro-scales, for exchanging information at the interface of the two scales. Four research papers investigate the hydrodynamics, heat transfer, and chemical reactions of various processes using Eulerian CFD modeling. CFD models are attractive for industrial applications. However, substantial efforts in physical modeling and numerical implementation are still required before their widespread implementation. Related Books CFD Modeling of Complex Chemical Processes: Multiscale and Multiphysics Challenges Engineering CFD Applications in Energy Engineering Research and Simulation Engineering CFD Applications in Energy Engineering Research and Simulation Engineering DNA Damage, Oxidative Stress and Related Metabolic By-Products in Cancer and Environmental Studies Biology & Life Sciences ... Application of CFD Simulations to Marine Hydrodynamic Problems Engineering ... The recommendations

Land cover and land use (LCLU) is an important component of the Earth system. It affects ecosystem services, water conservation, infectious disease outbreaks, food security, the climate system, urban forms, etc. In the last few decades, remote sensing technology has evolved dramatically for better radiometric, spatial, and spectral resolution image products. Such advances in remote sensing, together with a variety of machine- and deep learning algorithms and multiple high-performance cloud computing platforms, further provide the potential and opportunities for fine-resolution, global-scale, and dynamic LCLU mapping. In addition, along with the development of drone technology, the (near) real-time monitoring of land surface in different sectors, such as forestry and agriculture, has attracted much attention in recent years. The improved documenting of LCLU leads the scientific community to further explore the driving factors of LCLU changes and reveal the underlying mechanisms for better land use planning. This Reprint synthesizes recent advances in LCLU mapping, change detection, accuracy assessment, and driver analysis, providing important insights into the remote sensing of LCLU.

The research on parameterized complexity (PC), described in these peer-reviewed chapters by esteemed researchers, provides ties to practice as well as new theoretical developments, many in the direction of AI. Applications in bioinformatics and social choice are described, as well as faster, less costly approximation methods and new techniques using machine learning to find treewidth and other metrics. Many practical problems can be solved by harnessing the power of both PC and SAT solvers or integer linear programming modeled by parameterized graph problems. The extremely rapid development and deployment of PC continues to bring fresh understanding and solutions to fundamental open questions. Related Books Symmetry and Complexity 2019 Computer Science & Mathematics ... Theoretical and Computational Research in Various Scheduling Models Computer Science & Mathematics Quantum Computing Algorithms and Computational Complexity Computer Science & Mathematics Graph Algorithms and Applica

A key aspect of cyber-physical systems (CPS) is their potential for integrating information technologies with embedded control systems and physical systems to form new or improved functionalities. CPS thus draws upon advances in many areas. This positioning provides unprecedented opportunities for innovation, both within and across existing domains. However, at the same time, it is commonly understood that we are already stretching the limits of existing methodologies. In embarking towards CPS with such unprecedented capabilities, it becomes essential to improve our understanding of CPS complexity and how we can deal with it. Complexity has many facets, including complexity of the CPS itself, of the environments in which the CPS acts, and in terms of the organizations and supporting tools that develop, operate, and maintain CPS. This book is a result of a journal Special Issue, with the objective of providing a forum for researchers and practitioners to exchange their latest achieveme

Mathematical modeling is routinely used in physical and engineering sciences to help understand complex systems and optimize industrial processes. Mathematical modeling differs from Artificial Intelligence because it does not exclusively use the collected data to describe an industrial phenomenon or process, but it is based on fundamental laws of physics or engineering that lead to systems of equations able to represent all the variables that characterize the process. Conversely, Machine Learning methods require a large amount of data to find solutions, remaining detached from the problem that generated them and trying to infer the behavior of the object, material or process to be examined from observed samples. Mathematics allows us to formulate complex models with effectiveness and creativity, describing nature and physics. Together with the potential of Artificial Intelligence and data collection techniques, a new way of dealing with practical problems is possible. The insertion

The present reprint contains 14 papers accepted and published in the Special Issue of the MDPI Mathematics journal, entitled "Fuzzy Logic and Soft Computing – Dedicated to the Centenary of the Birth of Lotfi A. Zadeh (1921-2017)", which covers a wide range of topics connected to the theory and applications of fuzzy logic and soft computing. More precisely, these topics include:  mathematical programming problems with coefficients and/or decision variables expressed by fuzzy numbers; soft computing methods in a fuzzy environment;  fuzzy inner product spaces; M-hazy vector spaces;  interval ranges of fuzzy sets; arithmetic operations of fuzzy sets; gradual numbers;  Interval-valued fuzzy soft sets; interval-valued fuzzy soft topology; preference relationships; L-fuzzy sub-effect algebras; Fuzzy differential subordinations;  m-polar fuzzy set in semigroups;  practical use of the marks; the  fuzzy logic approach for decision-making systems in management control; multigranulation rough se

In this issue, psychometrics researchers were invited to make reanalyses or extensions of a previously published dataset from a recent paper by Myszkowski and Storme (2018). The dataset analyzed consisted of responses to a multiple-choice logical reasoning nonverbal test, comprising the last series of Raven’s (1941) Standard Progressive Matrices. Although the original paper already proposed several modeling strategies, this issue presents new or improved procedures to study the psychometrics properties of tests of this type. Related Books How Intelligence Can Be a Solution to Consequential World Problems Social Sciences, Arts & Humanities Psycho-Educational Assessments: Theory and Practice Social Sciences, Arts & Humanities Statistical Data Modeling and Machine Learning with Applications II Computer Science & Mathematics The Great Debate Social Sciences, Arts & Humanities Scientific Reasoning in Science Education: From Global Measures to Fine-Grained Descriptions of Students' Competen

The aim of this reprint focuses on the latest protocol research, software/hardware development and implementation, and system architecture design in addressing emerging security and privacy issues for modern wireless communication networks. Relevant topics include, but are not limited to, the following: deep-learning-based security and privacy design; covert communications; information-theoretical foundations for advanced security and privacy techniques; lightweight cryptography for power-constrained networks; physical layer key generation; prototypes and testbeds for security and privacy solutions; encryption and decryption algorithm for low-latency constrained networks; security protocols for modern wireless communication networks; network intrusion detection; physical layer design with security consideration; anonymity in data transmission; vulnerabilities in security and privacy in modern wireless communication networks; challenges of security and privacy in node–edge–cloud compu

The impact of climate change on hydrological processes, droughts, land use patterns, and ecosystem health is a critical area of research for understanding and managing the future of our planet. At the same time, changes in land use, agricultural methods, and population growth may contribute to climate change. With its ability to process large datasets and identify hidden patterns, deep learning has provided new tools for analyzing complex environmental data and developing predictive models. These tools offer a promising avenue for advancing our potential response to environmental challenges. This Special Issue brings together researchers from diverse fields, applying deep learning methods and new models to investigate climate change drivers and their impact on droughts, desertification, ice sheet melting, land use changes, and ecosystem service value. The goal is to enhance the capacity for predicting the interrelationships between the above-mentioned environmental components.

This reprint focuses on innovative methodologies based on remote sensing, as well as the monitoring and analysis of the relationship between urbanization and ecosystem services on different scales. The published papers describe the use of innovative technologies for land cover change monitoring, ecosystem service modeling and mapping, and innovation in land-use planning, in addition to highlighting the potential of technologies to tackle challenges such as the sustainability of urbanization, climate change adaptation, and sustainable land management.

The digital economy has significantly impacted countries throughout the world by contributing to the growth of the economy and the further progress of societies. Recent developments demonstrate that the information and innovation-driven era triggered integration of traditional activities and digital technologies. Moreover, the rise of innovation has been accelerating in emerging industries such as cleantech, the new generation of information technology, biotechnology, and high-end equipment manufacturing. The estimations provided by the World Economic Forum predict that “new value creation over the next decade will be based on digitally enabled platform business models”. Therefore, organizations must change the traditional approaches adopted and capture value in the context of digital disruptions. These tendencies raise a number of management challenges that need to be solved by the efforts of the scientific community. Therefore, this Special Issue provides the platform for a fruitfu

This book focuses on recent developments in new industrial platforms, with Industry 4.0 on its way to becoming Industry 5.0. The book covers smart decision support systems for green and sustainable machining, microscale machining, cyber-physical production networks, and the optimization of assembly lines. The modern multiobjective algorithms and multicriteria decision-making methods are applied to various real-world industrial problems. The emerging problem of cybersecurity in advanced technologies is addressed as well. Related Books New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes Engineering Smart Manufacturing & Automation Control Systems for Industry 4.0/5.0 Engineering Process Control and Smart Manufacturing for Industry 4.0 Engineering Novel Industry 4.0 Technologies and Applications Engineering Industry 4.0 – The Global Industrial Revolution: Achievements, Obstacles and Research Needs for the Digital Transformation of Industry Engin