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Books on the topic 'OPTIMIZER ALGORITHM'

Author: Grafiati
Published: 11 September 2023

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1

W, Longman Richard, and Langley Research Center, eds. Optimized system identification. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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2

W, Longman Richard, and Langley Research Center, eds. Optimized system identification. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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3

C, Chung Wilson, Smith Mark J. T, and United States. National Aeronautics and Space Administration., eds. Subband image coding with jointly optimized quantizers. [Washington, DC: National Aeronautics and Space Administration, 1995.

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4

Oliva, Diego, and Erik Cuevas. Advances and Applications of Optimised Algorithms in Image Processing. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-48550-8.

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5

Elliott, Donald M. Application of a genetic algorithm to optimize quality assurance in software development. Monterey, Calif: Naval Postgraduate School, 1993.

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6

Martins, Tiago, and Rui Neves. Stock Exchange Trading Using Grid Pattern Optimized by A Genetic Algorithm with Speciation. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76680-1.

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7

Jet Propulsion Laboratory (U.S.), ed. A Doppler centroid estimation algorithm for SAR systems optimized for the quasi-homogeneous source. Pasadena, Calif: National Aeronautics and Space Administration, Jet Propulsion Laboratory, California Institute of Technology, 1990.

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8

L, Palumbo Daniel, and Langley Research Center, eds. Performance of optimized actuator and sensor arrays in an active noise control system. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1996.

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9

Cujec, Anne-Marie. An optimized bit cell design for a pipelined current-mode algorithmic A/D converter. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1992.

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10

Fenn, Sebastian. Optimised algorithms and circuit architectures for performance finite field arithmetic in Reed-Solomon codecs. Huddersfield: The University, 1993.

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11

Berihanova, Rumisa, and Inessa Minenko. Complex non-drug correction of menopausal disorders in patients with metabolic syndrome. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1599004.

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The monograph is devoted to the complex non-drug correction of menopausal disorders in patients with metabolic syndrome in the period of menopausal transition. Modern ideas about menopausal and metabolic syndromes are presented, a review of modern approaches to their treatment is carried out. A complex personalized system of non-drug correction of functional disorders in patients with metabolic syndrome and menopausal syndrome of mild and moderate severity in the period of menopausal transition is presented, including preformed therapeutic factors (vibrotherapy, chromotherapy, aeroionotherapy, musicotherapy (melotherapy), aromatherapy), physical therapy with pelvic floor muscle training, drinking balneotherapy, vitamins and minerals against the background of lifestyle modification. The algorithm of dynamic clinical and laboratory examination of women with menopausal disorders of mild and moderate severity and metabolic syndrome in the period of menopausal transition has been developed, including a general clinical examination, assessment of alimentary, thyroid, psycho-emotional, gynecological, urological statuses, the state of the intestinal microbiota, the function of the hypothalamic-pituitary complex, biochemical blood profile, hemostasis, levels of markers of inflammation, assessment of the state of the musculoskeletal system, sexual function, allowing to get an idea of the state of mental and physical health of patients, evaluate the effectiveness of the complex of measures, optimize therapeutic tactics. It is addressed to a wide range of readers interested in women's health. It can be useful for students, postgraduates, teachers of medical universities, obstetricians, gynecologists, endocrinologists, cardiologists, specialists of restorative medicine.
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12

Karny, Miroslav. Optimized Bayesian Dynamic Advising: Theory and Algorithms. Springer London, Limited, 2006.

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13

Karny, Miroslav. Optimized Bayesian Dynamic Advising: Theory and Algorithms. Springer London, Limited, 2014.

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14

Chui, Kwok Tai. Computational Methods and Algorithms for Medicine and Optimized Clinical Practice. IGI Global, 2019.

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15

Cuevas, Erik, and Diego Oliva. Advances and Applications of Optimised Algorithms in Image Processing. Springer, 2016.

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16

Cuevas, Erik, and Diego Oliva. Advances and Applications of Optimised Algorithms in Image Processing. Springer, 2017.

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17

Cuevas, Erik, and Diego Oliva. Advances and Applications of Optimised Algorithms in Image Processing. Springer, 2018.

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18

Pro .NET Performance: Optimize Your C# Applications. Apress, 2012.

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19

National Aeronautics and Space Administration (NASA) Staff. Doppler Centroid Estimation Algorithm for Sar Systems Optimized for the Quasi-Homogeneous Source. Independently Published, 2018.

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20

Karny, Miroslav. Optimized Bayesian Dynamic Advising: Theory and Algorithms (Advanced Information and Knowledge Processing). Springer, 2005.

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21

Ye, Andy Gean. Field-programmable gate array architectures and algorithms optimized for implementing datapath circuits. 2004.

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22

National Aeronautics and Space Administration (NASA) Staff. Signal Analysis Algorithms for Optimized Fitting of Nonresonant Laser Induced Thermal Acoustics Damped Sinusoids. Independently Published, 2019.

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23

Kumar, Amit. The feasibility of using neural networks and genetic algorithms to predict and optimize coated paper and paper board brightness. 1999.

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24

Neves, Rui, and Tiago Martins. Stock Exchange Trading Using Grid Pattern Optimized by a Genetic Algorithm with Speciation: The Case of S&P 500. Springer International Publishing AG, 2021.

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25

Adams, Riley. Data Analytics for Businesses 2019: Master Data Science with Optimised Marketing Strategies Using Data Mining Algorithms. Independently Published, 2019.

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26

Stinkster, Jon. Vital Introduction to Machine Learning with Python: Best Practices to Improve and Optimize Machine Learning Systems and Algorithms. Independently Published, 2016.

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27

Bi, Xiaojun, Brian Smith, Tom Ouyang, and Shumin Zhai. Soft Keyboard Performance Optimization. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198799603.003.0006.

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Optimization techniques have played a vital role in improving the performance (i.e., input speed and accuracy) of soft keyboards. This chapter introduces the challenges, methodologies, and results of keyboard performance optimization. Leveraging the robust human motor control phenomena manifested in text entry, we used the Metropolis random walk algorithm, and Pareto multi-objective optimization method to optimize the keyboard layout and a soft keyboard decoder. The optimization led to layouts that shorten finger travel distance and improve the input speed as well as accuracy over the Qwerty layout, and a soft keyboard decoder with improved correction and completion ability.
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28

Houk, Lane. Creating Killer Content for Your Audience and the Search Algorithms: 13 Tips on How to Optimize Your Content for SEO. Marketing Center of Excellence, The, 2022.

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29

Houk, Lane. Creating Killer Content for Your Audience and the Search Algorithms: 13 Tips on How to Optimize Your Content for SEO. Marketing Center of Excellence, The, 2022.

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30

Adams, Riley, and Matt Henderson. Data Science for Business 2019: Master Data Analytics & Machine Learning with Optimized Marketing Strategies (Artificial Intelligence, Neural Networks, Algorithms & Predictive Modelling. Independently Published, 2019.

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31

Adams, Riley, and Matt Henderson. Data Science for Business 2019: Master Data Analytics & Machine Learning with Optimized Marketing Strategies (Artificial Intelligence, Neural Networks, Algorithms & Predictive Modelling. This is Charlotte., 2019.

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32

Algorithms: Discover the Computer Science and Artificial Intelligence Used to Solve Everyday Human Problems, Optimize Habits, Learn Anything, and Organize Your Life. Swain, Thomas William, 2019.

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33

Genics, Trust. Algorithms: Discover the Computer Science and Artificial Intelligence Used to Solve Everyday Human Problems, Optimize Habits, Learn Anything and Organize Your Life. Independently Published, 2019.

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34

Genics, Trust. Algorithms: The Complete Guide to the Computer Science & Artificial Intelligence Used to Solve Human Decisions, Advance Technology, Optimize Habits, Learn Faster & Your Improve Life. Swain, Thomas William, 2019.

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35

Genics, Trust. Algorithms: An Introduction to the Computer Science and Artificial Intelligence Used to Solve Human Decisions, Advance Technology, Optimize Habits, Learn Faster and Your Improve Life. Independently Published, 2019.

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36

Genics, Trust. Algorithms: The Complete Guide to the Computer Science and Artificial Intelligence Used to Solve Human Decisions, Advance Technology, Optimize Habits, Learn Faster and Your Improve Life. Independently Published, 2019.

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37

Maamar, Mustapha Ben. Payload optimisation on multi-terminal trucking networks: Two algorithms are developed to optimise the availablecapacity of delivery trucks operating on multi-terminal networks ---. Bradford, 1987.

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38

Butz, Martin V., and Esther F. Kutter. Cognitive Science is Interdisciplinary. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0002.

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Cognitive Science has come a long way – even the old Greeks have put forward intricate thoughts about what our minds can know and what seems inaccessible. This chapter addresses the historical development of cognitive science. The fundamental homunculus and qualia problems are introduced, and tentative answers from embodied cognitive science are sketched-out. A look at biology emphasizes that our bodies and brains are evolutionarily shaped, making us ready to develop our minds. Psychologically, minds develop and adapt given environmental feedback, striving to optimize behavior. Only by means of constructive, generative processes, however, can a behavior-oriented “understanding” of the environment develop. These “understanding”-oriented structures also make our mind language ready. Finally, in order to comprehend how the human mind actually comes into being, based on the considered principles, it is necessary to pursue functional, computational, and where possible, algorithmic and hardware perspectives in the sense of David Marr’s three levels of understanding.
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39

Giannitsis, Evangelos, and Hugo A. Katus. Biomarkers in acute coronary syndromes. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199687039.003.0036.

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Biomarker testing in the evaluation of a patient with acute chest pain is best established for cardiac troponins that allow the diagnosis of myocardial infarction, risk estimation of short- and long-term risk of death and myocardial infarction, and guidance of pharmacological therapy, as well as the need and timing of invasive strategy. Newer, more sensitive troponin assays have become commercially available and have the capability to detect myocardial infarction earlier and more sensitively than standard assays, but they are hampered by a lack of clinical specificity, i.e. the ability to discriminate myocardial ischaemia from myocardial necrosis not related to ischaemia such as myocarditis, pulmonary embolism, or decompensated heart failure. Strategies to improve clinical specificity (including strict adherence to the universal myocardial infarction definition and the need for serial troponin measurements to detect an acute rise and/or fall of cardiac troponin) will improve the interpretation of the increasing number of positive results. Other biomarkers of inflammation, activated coagulation/fibrinolysis, and increased ventricular stress mirror different aspects of the underlying disease activity and may help to improve our understanding of the pathophysiological mechanisms of acute coronary syndromes. Among the flood of new biomarkers, there are several novel promising biomarkers, such as copeptin that allows an earlier rule-out of myocardial infarction in combination with cardiac troponin, whereas MR-proANP and MR-proADM appear to allow a refinement of cardiovascular risk. GDF-15 might help to identify candidates for an early invasive vs conservative strategy. A multi-marker approach to biomarkers becomes more and more attractive, as increasing evidence suggests that a combination of several biomarkers may help to predict individual risk and treatment benefits, particularly among troponin-negative subjects. Future goals include the acceleration of rule-in and rule-out of patients with suspected acute coronary syndrome, in order to shorten lengths of stay in the emergency department, and to optimize patient management and the use of health care resources. New algorithms using high-sensitivity cardiac troponin assays at low cut-offs alone, or in combination with additional biomarkers, allow to establish accelerated rule-out algorithms within 1 or 2 hours.
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40

Giannitsis, Evangelos, and Hugo A. Katus. Biomarkers in acute coronary syndromes. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199687039.003.0036_update_001.

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Biomarker testing in the evaluation of a patient with acute chest pain is best established for cardiac troponins that allow the diagnosis of myocardial infarction, risk estimation of short- and long-term risk of death and myocardial infarction, and guidance of pharmacological therapy, as well as the need and timing of invasive strategy. Newer, more sensitive troponin assays have become commercially available and have the capability to detect myocardial infarction earlier and more sensitively than standard assays, but they are hampered by a lack of clinical specificity, i.e. the ability to discriminate myocardial ischaemia from myocardial necrosis not related to ischaemia such as myocarditis, pulmonary embolism, or decompensated heart failure. Strategies to improve clinical specificity (including strict adherence to the universal myocardial infarction definition and the need for serial troponin measurements to detect an acute rise and/or fall of cardiac troponin) will improve the interpretation of the increasing number of positive results. Other biomarkers of inflammation, activated coagulation/fibrinolysis, and increased ventricular stress mirror different aspects of the underlying disease activity and may help to improve our understanding of the pathophysiological mechanisms of acute coronary syndromes. Among the flood of new biomarkers, there are several novel promising biomarkers, such as copeptin that allows an earlier rule-out of myocardial infarction in combination with cardiac troponin, whereas MR-proANP and MR-proADM appear to allow a refinement of cardiovascular risk. GDF-15 might help to identify candidates for an early invasive vs conservative strategy. A multi-marker approach to biomarkers becomes more and more attractive, as increasing evidence suggests that a combination of several biomarkers may help to predict individual risk and treatment benefits, particularly among normal-troponin subjects. Future goals include the acceleration of rule-in and rule-out of patients with suspected acute coronary syndrome, in order to shorten lengths of stay in the emergency department, and to optimize patient management and the use of health care resources. New algorithms using high-sensitivity cardiac troponin assays at low cut-offs alone, or in combination with additional biomarkers, allow to establish accelerated rule-out algorithms within 1 or 2 hours.
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41

Giannitsis, Evangelos, and Hugo A. Katus. Biomarkers in acute coronary syndromes. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199687039.003.0036_update_002.

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Biomarker testing in the evaluation of a patient with acute chest pain is best established for cardiac troponins that allow the diagnosis of myocardial infarction, risk estimation of short- and long-term risk of death and myocardial infarction, and guidance of pharmacological therapy, as well as the need and timing of invasive strategy. Newer, more sensitive troponin assays have become commercially available and have the capability to detect myocardial infarction earlier and more sensitively than standard assays, but they are hampered by a lack of clinical specificity, i.e. the ability to discriminate myocardial ischaemia from myocardial necrosis not related to ischaemia such as myocarditis, pulmonary embolism, or decompensated heart failure. Strategies to improve clinical specificity (including strict adherence to the universal myocardial infarction definition and the need for serial troponin measurements to detect an acute rise and/or fall of cardiac troponin) will improve the interpretation of the increasing number of positive results. Other biomarkers of inflammation, activated coagulation/fibrinolysis, and increased ventricular stress mirror different aspects of the underlying disease activity and may help to improve our understanding of the pathophysiological mechanisms of acute coronary syndromes. Among the flood of new biomarkers, there are several novel promising biomarkers, such as copeptin that allows an earlier rule-out of myocardial infarction in combination with cardiac troponin, whereas MR-proANP and MR-proADM appear to allow a refinement of cardiovascular risk. GDF-15 might help to identify candidates for an early invasive vs conservative strategy. A multi-marker approach to biomarkers becomes more and more attractive, as increasing evidence suggests that a combination of several biomarkers may help to predict individual risk and treatment benefits, particularly among normal-troponin subjects. Future goals include the acceleration of rule-in and rule-out of patients with suspected acute coronary syndrome, in order to shorten lengths of stay in the emergency department, and to optimize patient management and the use of health care resources. New algorithms using high-sensitivity cardiac troponin assays at low cut-offs alone, or in combination with additional biomarkers, allow to establish accelerated rule-out algorithms within 1 or 2 hours.
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42

Nolan, Jerry P. Advanced life support. Edited by Neil Soni and Jonathan G. Hardman. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0091.

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Anaesthetists have a central role in cardiopulmonary resuscitation (CPR). The incidence of treated out-of-hospital cardiopulmonary arrest is 40 per 100 000 population and is associated with a survival rate to hospital discharge of 8–10%. The incidence of in-hospital cardiac arrest (IHCA) is 1–5 per 1000 admissions and is associated with a survival rate to hospital discharge of 13–17%. The most effective strategy for reducing mortality from IHCA is to prevent it occurring by detecting and treating those at risk or to identify in advance those with no chance of survival and to make a decision not to attempt resuscitation. The European Resuscitation Council and the Resuscitation Council (UK) publish guidelines for CPR every 5 years and the evidence supporting these is described in the international consensus on CPR science. The advanced life support algorithm forms the core of the guidelines but the precise interventions depend on the circumstances of the cardiac arrest and the skills of the healthcare providers. High-quality CPR with minimal interruptions will optimize survival rates. Shockable rhythms are treated with defibrillation while minimizing the pause in chest compressions. Although adrenaline (epinephrine) is used in most cardiac arrests, no studies have shown that it improves long-term outcome. The post-cardiac arrest syndrome is common and requires multiple organ support in an intensive care unit. Therapy in this phase is aimed at improving neurological (e.g. targeted temperature management) and myocardial (e.g. percutaneous coronary intervention) outcomes. Based on standard outcome measurements (e.g. cerebral performance category), 75–80% of survivors will have a ‘good’ neurological outcome, but many of these will have subtle neurocognitive deficits.
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43

López, Javier. Optimización multi-objetivo. Editorial de la Universidad Nacional de La Plata (EDULP), 2015. http://dx.doi.org/10.35537/10915/45214.

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Cuando hablamos de optimización en el ámbito de las ciencias de la computación hacemos referencia al mismo concepto coloquial asociado a esa palabra, la concreción de un objetivo utilizando la menor cantidad de recursos disponibles, o en una visión similar, la obtención del mejor objetivo posible utilizando todos los recursos con lo que se cuenta. Los métodos para encontrar la mejor solución (óptima) varían de acuerdo a la complejidad del problema enfrentado. Para problemas triviales, el cerebro humano posee la capacidad de resolverlos (encontrar la mejor solución) directamente, pero a medida que aumenta la complejidad del problema, se hace necesario contar con herramientas adicionales. En esta dirección, existe una amplia variedad de técnicas para resolver problemas complejos. Dentro de estas técnicas, podemos mencionar las técnicas exactas. Este tipo de algoritmos son capaces de encontrar las soluciones óptimas a un problema dado en una cantidad finita de tiempo. Como contrapartida, requiere que el problema a resolver cumpla con condiciones bastante restrictivas. Existen además un conjunto muy amplio de técnica aproximadas, conocidas como metaheurísticas. Estas técnicas se caracterizan por integrar de diversas maneras procedimientos de mejora local y estrategias de alto nivel para crear un proceso capaz de escapar de óptimos locales y realizar una búsqueda robusta en el espacio de búsqueda del problema. En su evolución, estos métodos han incorporado diferentes estrategias para evitar la convergencia a óptimos locales, especialmente en espacios de búsqueda complejos. Este tipo de procedimientos tienen como principal característica que son aplicables a cualquier tipo de problemas, sin requerir ninguna condición particular a cumplir por los mismos. Estas técnicas no garantizan en ningún caso la obtención de los valores óptimos de los problemas en cuestión, pero se ha demostrado que son capaces de alcanzar muy buenos valores de soluciones en períodos de tiempo cortos. Además, es posible aplicarlas a problemas de diferentes tipos sin mayores modificaciones, mostrando su robustez y su amplio espectro de uso. La mayoría de estas técnicas están inspiradas en procesos biológicos y/o físicos, y tratan de simular el comportamiento propio de estos procesos que favorecen la búsqueda y detección de soluciones mejores en forma iterativa. La más difundida de estas técnicas son los algoritmos genéticos, basados en el mecanismo de evolución natural de las especies. Existen diferentes tipos de problemas, y multitud de taxonomías para clasificar los mismos. En el alcance de este trabajo nos interesa diferenciar los problemas en cuanto a la cantidad de objetivos a optimizar. Con esta consideración en mente, surge una primera clasificación evidente, los problemas mono-objetivo, donde existe solo una función objetivo a optimizar, y los problemas multi-objetivo donde existe más de una función objetivo. En el presente trabajo se estudia la utilización de metaheurísticas evolutivas para la resolución de problemas complejos, con uno y con más de un objetivo. Se efectúa un análisis del estado de situación en la materia, y se proponen nuevas variantes de algoritmos existentes, validando que las mismas mejoran resultados reportados en la literatura. En una primera instancia, se propone una mejora a la versión canónica y mono-objetivo del algoritmo PSO, luego de un estudio detallado del patrón de movimientos de las partículas en el espacio de soluciones. Estas mejoras se proponen en las versiones de PSO para espacios continuos y para espacios binarios. Asimismo, se analiza la implementación de una versión paralela de esta técnica evolutiva. Como segunda contribución, se plantea una nueva versión de un algoritmo PSO multiobjetivo (MOPSO Multi Objective Particle Swarm Optimization) incorporando la posibilidad de variar dinámicamente el tamaño de la población, lo que constituye una contribución innovadora en problemas con mas de una función objetivo. Por último, se utilizan las técnicas representativas del estado del arte en optimización multi-objetivo aplicando estos métodos a la problemática de una empresa de emergencias médicas y atención de consultas domiciliarias. Se logró poner en marcha un proceso de asignación de móviles a prestaciones médicas basado en metaheurísticas, logrando optimizar el proceso de asignación de móviles médicos a prestaciones médicas en la principal compañía de esta industria a nivel nacional.
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44

Hilgurt, S. Ya, and O. A. Chemerys. Reconfigurable signature-based information security tools of computer systems. PH “Akademperiodyka”, 2022. http://dx.doi.org/10.15407/akademperiodyka.458.297.

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The book is devoted to the research and development of methods for combining computational structures for reconfigurable signature-based information protection tools for computer systems and networks in order to increase their efficiency. Network security tools based, among others, on such AI-based approaches as deep neural networking, despite the great progress shown in recent years, still suffer from nonzero recognition error probability. Even a low probability of such an error in a critical infrastructure can be disastrous. Therefore, signature-based recognition methods with their theoretically exact matching feature are still relevant when creating information security systems such as network intrusion detection systems, antivirus, anti-spam, and wormcontainment systems. The real time multi-pattern string matching task has been a major performance bottleneck in such systems. To speed up the recognition process, developers use a reconfigurable hardware platform based on FPGA devices. Such platform provides almost software flexibility and near-ASIC performance. The most important component of a signature-based information security system in terms of efficiency is the recognition module, in which the multipattern matching task is directly solved. It must not only check each byte of input data at speeds of tens and hundreds of gigabits/sec against hundreds of thousand or even millions patterns of signature database, but also change its structure every time a new signature appears or the operating conditions of the protected system change. As a result of the analysis of numerous examples of the development of reconfigurable information security systems, three most promising approaches to the construction of hardware circuits of recognition modules were identified, namely, content-addressable memory based on digital comparators, Bloom filter and Aho–Corasick finite automata. A method for fast quantification of components of recognition module and the entire system was proposed. The method makes it possible to exclude resource-intensive procedures for synthesizing digital circuits on FPGAs when building complex reconfigurable information security systems and their components. To improve the efficiency of the systems under study, structural-level combinational methods are proposed, which allow combining into single recognition device several matching schemes built on different approaches and their modifications, in such a way that their advantages are enhanced and disadvantages are eliminated. In order to achieve the maximum efficiency of combining methods, optimization methods are used. The methods of: parallel combining, sequential cascading and vertical junction have been formulated and investigated. The principle of multi-level combining of combining methods is also considered and researched. Algorithms for the implementation of the proposed combining methods have been developed. Software has been created that allows to conduct experiments with the developed methods and tools. Quantitative estimates are obtained for increasing the efficiency of constructing recognition modules as a result of using combination methods. The issue of optimization of reconfigurable devices presented in hardware description languages is considered. A modification of the method of affine transformations, which allows parallelizing such cycles that cannot be optimized by other methods, was presented. In order to facilitate the practical application of the developed methods and tools, a web service using high-performance computer technologies of grid and cloud computing was considered. The proposed methods to increase efficiency of matching procedure can also be used to solve important problems in other fields of science as data mining, analysis of DNA molecules, etc. Keywords: information security, signature, multi-pattern matching, FPGA, structural combining, efficiency, optimization, hardware description language.
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