تحسين النتائح
ترتيب حسب
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الصفحة 1
الصفحة 1
Machine-learning-assisted intelligent processing and optimization of complex systems
Focuses on the most recent developments in intelligent optimization methods and their applications in various test cases. The reprint covers various topics, including distributed multiagent modeling, metaheuristic algorithms, multisource data fusion, mobile computing and mobile sensing, machine learning-based intelligent processing for modeling complex manufacturing systems, and data-driven intelligent modeling
Machine learning for biomedical application
Biomedicine is a multidisciplinary branch of medical science that consists of many scientific disciplines, e.g., biology, biotechnology, bioinformatics, and genetics; moreover, it covers various medical specialties. In recent years, this field of science has developed rapidly. This means that a large amount of data has been generated, due to (among other reasons) the processing, analysis, and recognition of a wide range of biomedical signals and images obtained through increasingly advanced medical imaging devices. The analysis of these data requires the use of advanced IT methods, which include those related to the use of artificial intelligence, and in particular machine learning. It is a summary of the Special Issue “Machine Learning for Biomedical Application”, briefly outlining selected applications of machine learning in the processing, analysis, and recognition of biomedical data, mostly regarding biosignals and medical images.
Laser additive manufacturing: design, materials, processes and applications
Laser-based additive manufacturing (LAM) is a revolutionary advanced digital manufacturing technology developed in recent decades, which is also a key strategic technology for technological innovation and industrial sustainability. This technology unlocks the design and constraints of traditional manufacturing and meets the needs of complex geometry fabrication and high-performance part fabrication. A deeper understanding of the design, materials, processes, structures, properties and applications is desired to produce novel functional devices, as well as defect-free structurally sound and reliable LAM parts.The topics in this Special Issue reprint include macro- and micro-scale additive manufacturing with lasers, such as structure/material design, fabrication, modeling and simulation, in situ characterization of additive manufacturing processes and ex situ materials characterization and performance, with an overview that covers various applications in aerospace, biomedicine, optics and energy.
Autonomous vehicles technological trends
The automotive industry has always been synonymous with research and innovation, but nowadays the industry is adding pressure and is establishing the agenda of the researchers from the field. Visions have been provided, and the hardware and the software exist; the only question remaining is: “who is going to deliver”? To answer this question, we encouraged scientists, researchers, industry specialists, and academics to share their vision of autonomous vehicles. What will the platform look like? What kind of hardware and software is most suitable? Who will make the connection between these two interdependent environments (and how), so that in the end the AI will define the process? These are the pressing issues of the current moment, and this Special Issue will help all those interested in the topic to promote their vision and ideas.
Assistive technologies, robotics, and automated machines in the health domain
The field of healthcare is constantly evolving and advancing with new technologies and innovations. Among these, assistive technologies, robotics, and automated machines are rapidly gaining ground as powerful tools to improve the quality of care and enhance patient outcomes. From wearable devices that monitor vital signs to surgical robots that assist in complex procedures, these technologies have the potential to revolutionize the way we deliver healthcare. The development and the integration of assistive technologies, care robots, and automated machines are strategic both as single components, when paired together, and when interconnected in the health domain.This reprint explores the latest developments in assistive technologies, robotics, and automated machines in the health domain, providing a comprehensive overview of their applications and potential impact. The reprint is for the benefit of healthcare professionals, researchers, engineers, and students interested in these rapidly evolving fields.
Artificial intelligence techniques in hydrology and water resources management
The sustainable management of water cycles is crucial in the context of climate change and global warming. It involves managing global, regional, and local water cycles, as well as urban, agricultural, and industrial water cycles, to conserve water resources and their relationships with energy, food, microclimates, biodiversity, ecosystem functioning, and anthropogenic activities. Hydrological modeling is indispensable for achieving this goal, as it is essential for water resources management and the mitigation of natural disasters. In recent decades, the application of artificial intelligence (AI) techniques in hydrology and water resources management has led to notable advances. In the face of hydro-geo-meteorological uncertainty, AI approaches have proven to be powerful tools for accurately modeling complex, nonlinear hydrological processes and effectively utilizing various digital and imaging data sources, such as ground gauges, remote sensing tools, and in situ Internet of Things (IoT) devices.
Artificial intelligence in image-based screening, diagnostics, and clinical care of cardiopulmonary diseases
In this Special Issue, “Artificial Intelligence in Image-Based Screening, Diagnostics, and Clinical Care of Cardiopulmonary Diseases”, we have highlighted exemplary primary research studies and literature reviews focusing on novel AI/ML methods and their application in image-based screening, diagnosis, and clinical management of cardiopulmonary diseases.
Artificial intelligence for multisource geospatial information
Collects 10 original research contributions published in the Special Issue entitled “Artificial Intelligence for Multisource Geospatial Information” of the ISPRS International Journal of Geo-Information. The focus is on different methods of Geospatial Artificial Intelligence (GeoAI) based on deep learning using different network architectures, clustering, soft computing, and semantic approaches. They are proposed to deal with a variety of Geospatial Big Data (GBD), such as georeferenced texts and photos in social networks, remote sensing images, cartographic maps, multidimensional geo databases, metadata in spatial data infrastructures, and for different tasks, such as for multisource georeferenced text integration and geodata flexible querying, for social sensing by applying sentiment analysis, clustering and geo analysis, for segmentation of roads, clouds and snow, and for detection of small targets and people on the streets.
Artificial intelligence for multimedia signal processing
Artificial intelligence technologies are also actively applied to broadcasting and multimedia processing technologies. A lot of research has been conducted in a wide variety of fields, such as content creation, transmission, and security, and these attempts have been made in the past two to three years to improve image, video, speech, and other data compression efficiency in areas related to MPEG media processing technology. Additionally, technologies such as media creation, processing, editing, and creating scenarios are very important areas of research in multimedia processing and engineering. This book contains a collection of some topics broadly across advanced computational intelligence algorithms and technologies for emerging multimedia signal processing as: Computer vision field, speech/sound/text processing, and content analysis/information mining.
Artificial intelligence applied to medical imaging and computational biology
Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.
Applied mathematics and machine learning
The simultaneous availability of large datasets and high-performance computing capability in recent years has enabled the rapid development of powerful machine learning algorithms. On the one hand, state-of-the-art machine learning techniques have transformed many areas of science and engineering; on the other hand, theoretical discoveries in mathematical algorithms, differential equations, and statistical inferences, to name a few, have provided the foundation for the exploration of new multidisciplinary models for solving practical problems. This Special Issue endeavors to continue the journey that started in our previous Special Issue (Applied Mathematics and Computational Physics) by providing a platform for researchers from both academia and industry, as well as government, to present their new computational methods that have engineering and physics applications.
Applied and computational mathematics for digital environments
Contains the 11 papers that were accepted and published in the Special Issue “Applied and Computational Mathematics for Digital Environments” of the MDPI Mathematics journal. The topics of interest include, among others, scientific research, applied tasks, and problems in the following areas: The construction of mathematical and information models of intelligent computer systems for monitoring and controlling the parameters of digital environments; The development of intelligent optimization algorithms that search for optimal parameter values of mathematical and information models in digital environments; Software and mathematical technologies in the implementation of intelligent monitoring and computer control of the parameters of digital environments; The development and application of mathematical and information models, machine learning methods, and artificial intelligence for the analysis and processing of big data in digital environments.
Applications of computational intelligence
Computational intelligence (CI) is the theory, design, application, and development of biologically and linguistically motivated computational paradigms. Traditionally, the three main pillars of CI have been neural networks, fuzzy systems, and evolutionary computation. However, in time, many nature-inspired computing paradigms have evolved. Thus, CI is an evolving field, and, at present, in addition to the three main constituents, it encompasses computing paradigms such as ambient intelligence, artificial life, cultural learning, artificial endocrine networks, social reasoning, and artificial hormone networks. CI plays a major role in developing successful intelligent systems, including games and cognitive developmental systems.
Application of computational electromagnetics techniques and artificial intelligence in the engineering
Introduces the latest developments in electromagnetic computing and artificial intelligence technology. Artificial intelligence technology can be applied to the modeling, analysis, and optimization design of microwave equipment, solving the routing problem of self-organizing networks in small unmanned aerial vehicle systems, calculating the radiation characteristics of antenna arrays on large electrical platforms, analyzing the impact of electromagnetic wave coupling on electronic devices, simulating the field distribution characteristics of electronic devices, and so on. With the help of artificial intelligence, designers can more conveniently, quickly, and accurately solve engineering problems.
Application of power electronics converters in smart grids and renewable energy systems
Focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller.
Application and theory of multimedia signal processing using machine learning or advanced methods
Consists of a collection of peer-reviewed published papers on various advanced technology researches related to signal processing applications and theories for multimedia systems using machine learning or advanced methods. Multimedia signals include image, video, audio, character recognition, and communication channel optimization for networks. The specific contents included in this book are data hiding, encryption, object detection, image classification, and character recognition.
Advances in UAV detection, classification and tracking
Explores the latest techniques and advancements in unmanned aerial vehicle (UAV) detection, classification, and tracking. As UAV technology continues to evolve and become more accessible, there is a growing need for effective methods to detect, identify, and track these devices in various scenarios. This reprint provides a thorough overview of the state-of-the-art approaches for UAV detection, classification, and tracking, covering both theoretical and practical aspects.The reprint begins by introducing the basics of UAVs and their various applications, followed by a detailed overview of the challenges associated with UAV detection, classification, and tracking. The authors then present the latest techniques and algorithms used in the field, including machine-learning-based approaches, computer vision techniques, and sensor fusion techniques. The reprint also covers the challenges of real-world applications, such as dealing with occlusions, sensor noise, and environmental factors.
Advances in radar systems for target detection and tracking
Radar systems can provide the all-weather and all-time detection and tracking of targets of interest, and they have been extensively applied by the remote sensing community, in applications such as geological exploration, disaster forecasting, traffic monitoring, urban planning, environmental sciences, hydrology, littoral zones, oceans, etc. This reprint contains the several advance research studies on radar systems for target detection and tracking. It includes multipath ghost suppression, maneuvering target tracking, target detection, and other topics.
Advances in optical fiber communications
Given the increasing importance of a globally interconnected world, driven by modern digital services and the need for fast and reliable access to digital resources, communication networks are one of the key infrastructures in today’s society. In this scenario, fiber optics and optical devices play a leading role, as they allow for unprecedented growth in our capacity to cope with the ever-increasing traffic demand. Optical transmission solutions range from high-speed networks based on coherent detection and advanced modulation formats for long-haul-level communications, to networks still relying on traditional intensity modulation and direct detection receivers for short-reach communications, down to intra-data center scenarios.
Advances in image enhancement
In the era of the internet of things, images have played important roles in human–computer interactions, and with the arrival of big data technology, people have higher requirements regarding image quality, especially for images collected in dark light. This can be addressed through the development of camera hardware quality, i.e., the resolution and exposure time of cameras, which may require high computational costs. As an alternative, image enhancement techniques can exact salient features to improve the quality of captured images according to the differences in diverse features, although they suffer from some challenges, i.e., a low contrast, artifacts, and overexposure, thus making it decidedly necessary to determine how to use advanced image enhancement techniques.
