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This work develops highly efficient algorithms for analyzing large images. Applications include object-based change detection and screening. The algorithms are 10-100 times as fast as existing software, sometimes even outperforming FGPA/GPU hardware, because they are designed to suit the computer architecture. This thesis describes the implementation details and the underlying algorithm engineering methodology, so that both may also be applied to other applications.
image processing --- algorithm engineering --- SIMD --- image analysis --- lossless image compression
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This eBook is a collection of articles from a Frontiers Research Topic. Frontiers Research Topics are very popular trademarks of the Frontiers Journals Series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area! Find out more on how to host your own Frontiers Research Topic or contribute to one as an author by contacting the Frontiers Editorial Office: frontiersin.org/about/contact
RNA-seq --- algorithm --- software pipeline --- method assessment --- differenial analysis
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Relational database management systems, using as foundations a formal language, first-order logic, serve as mediators between individuals and machines. With the increase in the volume of data disseminated on the Web, a "collective intelligence" is currently emerging, shaped by large search engines whose monopoly raises ethical and political questions. One of the main challenges for the coming years is the development of technologies that will make it possible to find, evaluate, validate, verify and rank information, and thus to build tomorrow's "Web of knowledge".
Computer science. --- Data science. --- Algorithm. --- Engineering & Applied Sciences --- Computer Science --- inaugural lecture --- computer science --- data science --- Web --- knowledge --- algorithm
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The book contains 15 chapters presenting recent contributions of top researchers working with Simulated Annealing (SA). Although it represents a small sample of the research activity on SA, the book will certainly serve as a valuable tool for researchers interested in getting involved in this multidisciplinary field. In fact, one of the salient features is that the book is highly multidisciplinary in terms of application areas since it assembles experts from the fields of Biology, Telecommunications, Geology, Electronics and Medicine.
Simulated annealing (Mathematics) --- Algorithm, Annealing --- Algorithm, Probabilistic exchange --- Annealing, Monte Carlo --- Annealing, Simulated --- Annealing algorithm --- Cooling, Statistical --- Exchange algorithm, Probabilistic --- Hill climbing, Probabilistic --- Monte Carlo annealing --- Probabilistic exchange algorithm --- Probabilistic hill climbing --- Relaxation, Stochastic --- Statistical cooling --- Stochastic relaxation --- Combinatorial optimization --- Mathematical modelling
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This book provides the readers with the knowledge of Simulated Annealing and its vast applications in the various branches of engineering. We encourage readers to explore the application of Simulated Annealing in their work for the task of optimization.
Simulated annealing (Mathematics) --- Algorithm, Annealing --- Algorithm, Probabilistic exchange --- Annealing, Monte Carlo --- Annealing, Simulated --- Annealing algorithm --- Cooling, Statistical --- Exchange algorithm, Probabilistic --- Hill climbing, Probabilistic --- Monte Carlo annealing --- Probabilistic exchange algorithm --- Probabilistic hill climbing --- Relaxation, Stochastic --- Statistical cooling --- Stochastic relaxation --- Combinatorial optimization --- Mathematical modelling
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Simulated Annealing is a probabilistic meta-heuristic that is based on statistical mechanics: while at high temperatures molecules in a liquid move freely, the slow reduction of temperature decreases the thermal mobility of the molecules. The final state forms a pure crystal which also corresponds to a state of minimum energy. We encourage readers to explore SA in their work, mainly because it is simple and because it can yield very good results.
Simulated annealing (Mathematics) --- Algorithm, Annealing --- Algorithm, Probabilistic exchange --- Annealing, Monte Carlo --- Annealing, Simulated --- Annealing algorithm --- Cooling, Statistical --- Exchange algorithm, Probabilistic --- Hill climbing, Probabilistic --- Monte Carlo annealing --- Probabilistic exchange algorithm --- Probabilistic hill climbing --- Relaxation, Stochastic --- Statistical cooling --- Stochastic relaxation --- Combinatorial optimization --- Dynamics & statics
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This book presents state of the art contributes to Simulated Annealing (SA) that is a well-known probabilistic meta-heuristic. It is used to solve discrete and continuous optimization problems. The significant advantage of SA over other solution methods has made it a practical solution method for solving complex optimization problems. Book is consisted of 13 chapters, classified in single and multiple objectives applications and it provides the reader with the knowledge of SA and several applications. We encourage readers to explore SA in their work, mainly because it is simple and can determine extremely very good results.
Simulated annealing (Mathematics) --- Algorithm, Annealing --- Algorithm, Probabilistic exchange --- Annealing, Monte Carlo --- Annealing, Simulated --- Annealing algorithm --- Cooling, Statistical --- Exchange algorithm, Probabilistic --- Hill climbing, Probabilistic --- Monte Carlo annealing --- Probabilistic exchange algorithm --- Probabilistic hill climbing --- Relaxation, Stochastic --- Statistical cooling --- Stochastic relaxation --- Combinatorial optimization --- Mathematical modelling
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Relational database management systems, using as foundations a formal language, first-order logic, serve as mediators between individuals and machines. With the increase in the volume of data disseminated on the Web, a "collective intelligence" is currently emerging, shaped by large search engines whose monopoly raises ethical and political questions. One of the main challenges for the coming years is the development of technologies that will make it possible to find, evaluate, validate, verify and rank information, and thus to build tomorrow's "Web of knowledge".
Computer science. --- Data science. --- Algorithm. --- Engineering & Applied Sciences --- Computer Science --- Informatics --- Science --- inaugural lecture --- computer science --- data science --- Web --- knowledge --- algorithm
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Water is irreplaceable natural resources on the planet for people to survival and develop. Declining water quality has become a global issue of significant concern as anthropogenic activities expand and climate change threatens to cause major alterations to the hydrological cycle. Thus, monitoring the physical, chemical, and biological status of rivers, reservoirs, lakes, coastal waters, and oceans is immensely important. Remote sensing has the potential to provide an invaluable complementary source of data at local to global scales. This book—Water Optics and Water Colour Remote Sensing—provides an overview of the current state of the science on water optical properties and water colour remote sensing monitoring. Overall, the book presents a variety of applications at the global scale (with case studies in Europe, Asia, South and North America, and the Antarctic), achieved with different remote sensing instruments, such as hyperspectral field and airborne sensors, ocean colour radiometry, geostationary platforms, and the multispectral Landsat and Sentinel-2 satellites. The book is aimed at a wide audience, ranging from the graduate students, university teachers and the working scientists to policy makers and managers. Efforts have been made to highlight general principles as well as the site-specific application in the field of water optics and water colour remote sensing.
water optics --- remote sensing algorithm --- water colour remote sensing --- atmospheric correction --- chlorophyll a
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This book develops efficient methods for the application of Evolutionary Algorithms on stochastic problems. To achieve this, procedures for statistical selection are systematically analyzed with respect to different measures and significantly improved. It is shown how to adapt one of the best procedures for the needs of Evolutionary Algorithms and Evolutionary operators for efficient implementation in stochastic environments are identified.
Evolutionary Algorithm --- Uncertainty --- Simulation based optimization --- Bayes --- Ranking & Selection --- Genetic Algorithms
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