Algorithmic Step

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Timothy W Garvey - One of the best experts on this subject based on the ideXlab platform.

  • adiposity based chronic disease as a new diagnostic term the american association of clinical endocrinologists and american college of endocrinology position statement
    Endocrine Practice, 2017
    Co-Authors: Jeffrey I Mechanick, Daniel L Hurley, Timothy W Garvey
    Abstract:

    : The American Association of Clinical Endocrinologists (AACE) and American College of Endocrinology (ACE) have created a chronic care model, advanced diagnostic framework, clinical practice guidelines, and clinical practice algorithm for the comprehensive management of obesity. This coordinated effort is not solely based on body mass index as in previous models, but emphasizes a complications-centric approach that primarily determines therapeutic decisions and desired outcomes. Adiposity-Based Chronic Disease (ABCD) is a new diagnostic term for obesity that explicitly identifies a chronic disease, alludes to a precise pathophysiologic basis, and avoids the stigmata and confusion related to the differential use and multiple meanings of the term "obesity." Key elements to further the care of patients using this new ABCD term are: (1) positioning lifestyle medicine in the promotion of overall health, not only as the first Algorithmic Step, but as the central, pervasive action; (2) standardizing protocols that comprehensively and durably address weight loss and management of adiposity-based complications; (3) approaching patient care through contextualization (e.g., primordial prevention to decrease obesogenic environmental risk factors and transculturalization to adapt evidence-based recommendations for different ethnicities, cultures, and socio-economics); and lastly, (4) developing evidence-based strategies for successful implementation, monitoring, and optimization of patient care over time. This AACE/ACE blueprint extends current work and aspires to meaningfully improve both individual and population health by presenting a new ABCD term for medical diagnostic purposes, use in a complications-centric management and staging strategy, and precise reference to the obesity chronic disease state, divested from counterproductive stigmata and ambiguities found in the general public sphere. ABBREVIATIONS: AACE = American Association of Clinical Endocrinologists ABCD = Adiposity-Based Chronic Disease ACE = American College of Endocrinology BMI = body mass index CPG = clinical practice guidelines HCP = health care professionals.

Jeffrey I Mechanick - One of the best experts on this subject based on the ideXlab platform.

  • adiposity based chronic disease as a new diagnostic term the american association of clinical endocrinologists and american college of endocrinology position statement
    Endocrine Practice, 2017
    Co-Authors: Jeffrey I Mechanick, Daniel L Hurley, Timothy W Garvey
    Abstract:

    : The American Association of Clinical Endocrinologists (AACE) and American College of Endocrinology (ACE) have created a chronic care model, advanced diagnostic framework, clinical practice guidelines, and clinical practice algorithm for the comprehensive management of obesity. This coordinated effort is not solely based on body mass index as in previous models, but emphasizes a complications-centric approach that primarily determines therapeutic decisions and desired outcomes. Adiposity-Based Chronic Disease (ABCD) is a new diagnostic term for obesity that explicitly identifies a chronic disease, alludes to a precise pathophysiologic basis, and avoids the stigmata and confusion related to the differential use and multiple meanings of the term "obesity." Key elements to further the care of patients using this new ABCD term are: (1) positioning lifestyle medicine in the promotion of overall health, not only as the first Algorithmic Step, but as the central, pervasive action; (2) standardizing protocols that comprehensively and durably address weight loss and management of adiposity-based complications; (3) approaching patient care through contextualization (e.g., primordial prevention to decrease obesogenic environmental risk factors and transculturalization to adapt evidence-based recommendations for different ethnicities, cultures, and socio-economics); and lastly, (4) developing evidence-based strategies for successful implementation, monitoring, and optimization of patient care over time. This AACE/ACE blueprint extends current work and aspires to meaningfully improve both individual and population health by presenting a new ABCD term for medical diagnostic purposes, use in a complications-centric management and staging strategy, and precise reference to the obesity chronic disease state, divested from counterproductive stigmata and ambiguities found in the general public sphere. ABBREVIATIONS: AACE = American Association of Clinical Endocrinologists ABCD = Adiposity-Based Chronic Disease ACE = American College of Endocrinology BMI = body mass index CPG = clinical practice guidelines HCP = health care professionals.

Daniel L Hurley - One of the best experts on this subject based on the ideXlab platform.

  • adiposity based chronic disease as a new diagnostic term the american association of clinical endocrinologists and american college of endocrinology position statement
    Endocrine Practice, 2017
    Co-Authors: Jeffrey I Mechanick, Daniel L Hurley, Timothy W Garvey
    Abstract:

    : The American Association of Clinical Endocrinologists (AACE) and American College of Endocrinology (ACE) have created a chronic care model, advanced diagnostic framework, clinical practice guidelines, and clinical practice algorithm for the comprehensive management of obesity. This coordinated effort is not solely based on body mass index as in previous models, but emphasizes a complications-centric approach that primarily determines therapeutic decisions and desired outcomes. Adiposity-Based Chronic Disease (ABCD) is a new diagnostic term for obesity that explicitly identifies a chronic disease, alludes to a precise pathophysiologic basis, and avoids the stigmata and confusion related to the differential use and multiple meanings of the term "obesity." Key elements to further the care of patients using this new ABCD term are: (1) positioning lifestyle medicine in the promotion of overall health, not only as the first Algorithmic Step, but as the central, pervasive action; (2) standardizing protocols that comprehensively and durably address weight loss and management of adiposity-based complications; (3) approaching patient care through contextualization (e.g., primordial prevention to decrease obesogenic environmental risk factors and transculturalization to adapt evidence-based recommendations for different ethnicities, cultures, and socio-economics); and lastly, (4) developing evidence-based strategies for successful implementation, monitoring, and optimization of patient care over time. This AACE/ACE blueprint extends current work and aspires to meaningfully improve both individual and population health by presenting a new ABCD term for medical diagnostic purposes, use in a complications-centric management and staging strategy, and precise reference to the obesity chronic disease state, divested from counterproductive stigmata and ambiguities found in the general public sphere. ABBREVIATIONS: AACE = American Association of Clinical Endocrinologists ABCD = Adiposity-Based Chronic Disease ACE = American College of Endocrinology BMI = body mass index CPG = clinical practice guidelines HCP = health care professionals.

Bertrand Delabarre - One of the best experts on this subject based on the ideXlab platform.

  • Contributions to dense visual tracking and visual servoing using robust similarity criteria
    2014
    Co-Authors: Bertrand Delabarre
    Abstract:

    In this document, we address the visual tracking and visual servoing problems. They are crucial thematics in the domain of computer and robot vision. Most of these techniques use geometrical primitives extracted from the images in order to estimate a motion from an image sequences. But using geometrical features means having to extract and match them at each new image before performing the tracking or servoing process. In order to get rid of this Algorithmic Step, recent approaches have proposed to use directly the information provided by the whole image instead of extracting geometrical primitives. Most of these algorithms, referred to as direct techniques, are based on the luminance values of every pixel in the image. But this strategy limits their use, since the criteria is very sensitive to scene perturbations such as luminosity shifts or occlusions. To overcome this problem, we propose in this document to use robust similarity measures, the sum of conditional variance and the mutual information, in order to perform robust direct visual tracking and visual servoing processes. Several algorithms are then proposed that are based on these criteria in order to be robust to scene perturbations. These different methods are tested and analyzed in several setups where perturbations occur which allows to demonstrate their efficiency.

Maestrini Michele - One of the best experts on this subject based on the ideXlab platform.

  • Hybrid differentialdynamisk programmeringsalgoritm med exakta högre ordningens övergångsavbildningar​ för utformning av omloppsbanor för låg framdrivningskraft
    KTH Rymdteknik, 2018
    Co-Authors: Maestrini Michele
    Abstract:

    Optimal orbital trajectories are obtained through the solution of highly nonlinear large scale problems. In the case of low-thrust propulsion applications, the spacecraft benefits from high specific impulses and, hence, greater payload mass. However, these missions require a high count of orbital revolutions and, therefore, display augmented sensitivity to many disturbances. Solutions to such problems can be tackled via a discrete approach, using optimal feedback control laws. Historically, differential dynamic programming (DDP) has shown outstanding results in tackling these problems. A state of the art software that implements a variation of DDP has been developed by Whiffen and it is used by NASA’s DAWN mission [Mystic: Implementation of the Static Dynamic Optimal Control Algorithm for High-Fidelity, Low-Thrust Trajectory Design" , AAS/AIAA Astrodynamics Specialist Conference, (Keystone, Colorado), American Institute of Aeronautics and Astronautics, Aug. 21, 2006]. One of the latest techniques implemented to deal with these discrete constrained optimizations is the Hybrid Differential Dynamic Programming (HDDP) algorithm, introduced by Lantoine and Russell in [A Hybrid Differential Dynamic Programming Algorithm for Constrained Optimal Control Problems. Part 1: Theory", Journal of Optimization Theory and Applications, vol. 154, pp. 382-417, issue 2, Aug. 1, 2012]. This method complements the reliability and efficiency of classic nonlinear programming techniques with the robustness to poor initial guesses and the reduced computational effort of DDP. The key feature of the algorithm is the exploitation of a second order state transition matrix procedure to propagate the needed partials, decoupling the dynamics from the optimization. In doing so, it renders the integration of dynamical equations suitable for parallelization. Together with the possibility to treat constrained problems, this represents the greatest improvement of classic DDP. Nevertheless, the major limitation of this approach is the high computational cost to evaluate the required state transition matrices. Analytical derivatives, when available, have shown a significant reduction in the computational cost and time for HDDP application. This work applies differential algebra to HDDP to cope with this limitation. In particular, differential algebra is introduced to obtain state transition matrices as polynomial maps. These maps come directly from the integration of the dynamics of the system, removing the dedicated Algorithmic Step and reducing its computational cost. Moreover, by operating on polynomial maps, all the solutions of local optimization problems are treated through differential algebraic techniques. This approach allows us to deal with higher order expansions of the cost, without modifying the algorithm. The leading assumption of this work is that, treating higher than second order expansions, grants larger radii of convergence for the algorithm, improved robustness to initial guesses, hence faster rates of convergence. Examples are presented in this thesis to assess the performance of the newly constructed algorithm and to test the assumptions.​Optimala omloppsbanor erhålls genom lösningen av mycket storskaliga olinjära problem. I fallet med låg framdrivningskraft så drar farkosten nytta av hög specifik impuls och därmed större slutlig farkostmassa. Dock så kräver dessa rymduppdrag flera omloppsvarv och uppvisar därför ökad känslighet för olika störningskrafter. Lösningar på dessa problem kan hanteras via ett diskret tillvägagångssätt med hjälp av optimal reglering. Historiskt har differentialdynamisk programmering (DDP) visat enastående resultat för att hantera dessa problem. En toppmodern programvara som implementerar en variation av DDP har utvecklats av Whiffen i ["Mystic: Implementation of the Static Dynamic Optimal Control Algorithm for High-Fidelity, Low-Thrust Trajectory Design" , AAS/AIAA Astrodynamics Specialist Conference, (Keystone, Colorado), American Institute of Aeronautics and Astronautics, Aug. 21, 2006] och används av NASA:s rymduppdrag Dawn. En av de senaste teknikerna som implementerats för att hantera dessa diskreta och begränsade optimeringar är en hybrid differentialdynamisk programmeringsalgoritm (HDDP) som introducerades av Lantoine och Russell i ["A Hybrid Differential Dynamic Programming Algorithm for Constrained Optimal Control Problems. Part 1: Theory", Journal of Optimization Theory and Applications, vol. 154, pp. 382-417, issue 2, Aug. 1, 2012]. Denna metod kompletterar pålitligheten och effektiviteten hos klassiska olinjära programmeringstekniker med robusthet mot dåliga initiala gissningar och den reducerade beräkningskostnaden för DDP. Nyckelegenskapen hos algoritmen är utnyttjandet av en procedur för andra ordningens övergångsmatris för propagering av de erforderliga partiella derivatorna. Denna procedur frikopplar också dynamiken från optimeringen. Genom att göra så blir integration av de dynamiska ekvationerna lämpliga för parallellisering. Tillsammans med förmågan att ta itu med begränsade problem representerar detta den största förbättringen av klassisk DDP. Ändå är den stora begränsningen av detta tillvägagångssätt den höga kostnaden för beräkningar som krävs för att utvärdera tillståndsövergångsmatriserna. När de är tillgängliga, har analytiska derivatorer visat en signifikant minskning av beräkningskostnaden och tiden för HDDP-tillämpningar. Detta arbete tillämpar differentialalgebra på HDDP för att klara av denna begränsning. I synnerhet införs differentialalgebra för att erhålla tillståndsövergångsmatriser som polynomavbildningar. Dessa avbildningar kommer direkt från integrationen av systemets dynamik och därför är det möjligt att ta bort det dedikerade algoritmiska steget och minska beräkningskostnaden. Vidare behandlas alla lösningar av lokala optimeringsproblem genom olika algebraiska tekniker genom att använda polynomkartor. Detta tillvägagångssätt tillåter oss att hantera högre ordningens expansionstermer av kostnadsfunktionen utan att ändra algoritmen. Det främsta antagandet i detta arbete är att behandling av högre än andra ordningens expansionstermer ger större konvergensradier för algoritmen, förbättrad robusthet mot sämre initiala gissningar och följaktligen snabbare konvergensnivåer. Exempel presenteras i denna examensarbete för att bedöma prestandan hos den nybyggda algoritmen och för att testa antagandena