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A Geodesics-Based Surface Parameterization to Assess Aneurysm Progression

JOURNAL OF BIOMECHANICAL ENGINEERING-TRANSACTIONS OF THE ASME 2016年第5期138卷 054503-054503页

作者： Phan, Ly Courchaine, Katherine Azarbal, Amir Vorp, David Grimm, Cindy Rugonyi, Sandra Intel Corp Design & Technol Solut MS RA4 4032501 NW 229th Hillsboro OR 97124 USA Oregon Hlth & Sci Univ Biomed Engn 3303 SW Bond AveM-C CH13B Portland OR 97239 USA Oregon Hlth & Sci Univ Dept Surg Div Vasc Surg 3181 SW Sam Jackson Pk Rd Portland OR 97239 USA Univ Pittsburgh Dept Bioengn Ctr Bioengn CNBIO Suite 300300 Technol Dr Pittsburgh PA 15219 USA Oregon State Univ Mech Engn 204 Rogers Hall Corvallis OR 97331 USA Oregon Hlth & Sci Univ Biomed Engn 3303 SW Bond AveM-C CH13B Portland OR 97239 USA

Abdominal aortic aneurysm (AAA) intervention and surveillance is currently based on maximum transverse diameter, even though it is recognized that this might not be the best strategy. About 10% of patients with small AAA transverse diameters, for whom intervention is not considered, still rupture;while patients with large AAA transverse diameters, for whom intervention would have been recommended, have stable aneurysms that do not rupture. While maximum transverse diameter is easy to measure and track in clinical practice, one of its main drawbacks is that it does not represent the whole AAA and rupture seldom occurs in the region of maximum transverse diameter. By following maximum transverse diameter alone clinicians are missing information on the shape change dynamics of the AAA, and clues that could lead to better patient care. We propose here a method to register AAA surfaces that were obtained from the same patient at different time points. Our registration method could be used to track the local changes of the patient-specific AAA. To achieve registration, our procedure uses a consistent parameterization of the AAA surfaces followed by strain relaxation. The main assumption of our procedure is that growth of the AAA occurs in such a way that surface strains are smoothly distributed, while regions of small and large surface growth can be differentiated. The proposed methodology has the potential to unravel different patterns of AAA growth that could be used to stratify patient risks.

关键词： optimization Shapes Aneurysms Rupture Surveillance Relaxation (Physics) Dynamics (Mechanics) optimization algorithms

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Démarche de prélocalisation des pertes physiques sur un réseau de distribution d'eau potable par l'optimisation du modèle hydraulique via un algorithme évolutionnaire

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LHB 2016年第6期102卷 59-66页

作者： Karima Sebbagh Abdelhamid Safri Moula Zabot Olivier Narbey Laboratoire Environnement Géotechnique et hydraulique (LEG-HYD)/Université des Sciences et de la Technologie - Houari Boumediene (USTHB) Algérie - Suez Environnement -

La gestion durable des réseaux de distribution d'eau potable est un enjeu majeur surtout pour les pays émergents où les rendements de réseau sont très faibles. La localisation et la priorisation des zones fuyardes deviennent une préoccupation majeure pour les services publics afin d'optimiser les ressources et d'améliorer la continuité de service. Les fuites dans les réseaux d'eau apparaissent généralement suite au vieillissement ou à une dégradation mécanique des *** le présent document, une approche d'aide à la décision sera proposée pour prélocaliser les zones à fort débit de fuites. Elle se base sur la résolution de l'équation de FAVAD (Fixed And Variable Area Discharge) en optimisant ses paramètres (coefficients et exposant de l'émetteur) via l'utilisation d'Algorithmes Génétiques (AG) couplés à une modélisation hydraulique interfacée avec un système d'information géographique (SIG).Deux outils ont été développés ; ExpaGIS et Optim_Detect pour résoudre respectivement les problématiques d'export des données et paramètres d'entrée du modèle hydraulique depuis le système d'information géographique ainsi que la répartition spatio-temporelle des pertes physiques dans un étage de *** démarche permet une interprétation en quasi-temps réel et automatisée des données de pression notamment, en les convertissant en une suspicion de fuites. L'exemple du réseau de Zeralda à Alger, d'un linéaire de 12 km est présenté pour démontrer l'efficacité de l'approche proposé*** Sustainable management of water distribution networks is a crucial challenge especially in emerging countries where distribution networks have a very low efficiency with very high levels of Non-Revenue Water. Locating and prioritizing of water leakage areas becomes a main concern for public services to optimize the use of resources and improve constancy of supply. Leaks in water systems generally appear due to the aging of the infrastructure, generated or amplified by corrosio

关键词： algorithmes d'optimisation fuites réseau de distribution FAVAD EPANET optimization algorithms leaks distribution network FAVAD EPANET

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Application of Information Processes Applicative Modelling to Virtual Machines Auto Configuration

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Procedia Computer Science 2016年 96卷 1041-1048页

作者： Sergey Zykov Leonid Shumsky MEPhI National Research Nuclear University 31 Kashirskoe Shosse 115409 Moscow Russia Innopolis University 1 Universitetskaya St. 420500 Innopolis Russia

The paper discusses application of the algorithm based information processes modeling and Q-machine learning to the task of virtual machines auto configuration. Usage of virtual machines is one the most common solution nowadays for almost every companies. Although using of virtual machines simplifies settings of hardware landscape and allows physical servers decentralization they may cause performance decrease. To overcome this issue, we propose using method of virtual machines auto configuration. The method is based on the following premises: tracking real business process held by virtual machines, using algorithms of machine learning to investigate optimal configuration, and virtual machine configuration by independent process.

关键词： Virtual machines Process modeling optimization algorithms

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A UNIFORM ENHANCEMENT APPROACH FOR optimization algorithms: SMOOTHING FUNCTION METHOD

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2010年第7期24卷 1111-1131页

作者： Wang, Yuping Xidian Univ Sch Comp Sci & Technol Xian 710071 Peoples R China

In this paper, we propose a uniform enhancement approach called smoothing function method, which can cooperate any optimization algorithm and improve its performance. The method has two phases. In the first phase, a smoothing function is constructed by using a properly truncated Fourier series. It can preserve the overall shape of the original objective function but eliminate many of its local optimal points, thus it can well approach the objective function. Then, the optimal solution of the smoothing function is searched by an optimization algorithm (e. g. traditional algorithm or evolutionary algorithm) so that the search becomes much easier. In the second phase, we switch to optimize the original function for some iterations by using the best solution(s) obtained in phase 1 as an initial point (population). Thereafter, the smoothing function is updated in order to approximate the original function more accurately. These two phases are repeated until the best solutions obtained in several successively second phases cannot be improved obviously. In this manner, any optimization algorithm will become much easier in searching optimal solution. Finally, we use the proposed approach to enhance two typical optimization algorithms: Powell direct algorithm and a simple genetic algorithm. The simulation results on ten challenging benchmarks indicate the proposed approach can effectively improve the performance of these two algorithms.

关键词： Smoothing function method uniform enhancement approach optimization algorithms

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Economic Load Dispatch Considering Valve-point Effects Using Time Varying Constriction Factor Based Particle Swarm optimization

Economic Load Dispatch Considering Valve-point Effects Using...

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IEEE Uttar Pradesh Section Conference on Electrical Computer and Electronics (UPCON)

作者： Alam, M. N. Kumar, Kanhaiya Mathur, Akhilesh Indian Inst Technol Dept Elect Engn Roorkee Uttar Pradesh India

ISBN: (纸本)9781467385077

This paper proposes a new optimization algorithm suitable to solve economic load dispatch problem of power system considering valve-point loading effects. The new optimization algorithm is a time varying constriction factor based particle swarm optimization (VCF_PSO). In the proposed algorithm, the two acceleration coefficients of particle swarm optimization are varied in order to obtain a varying constriction as the iteration proceeds which lead to give a fast and efficient algorithm. To test the effectiveness and the robustness of the proposed algorithm, economic load dispatch problems with valve-point effects of two IEEE test systems of 3-unit and 13-unit has been solved and the results obtained have been compared with some other methods present in the literature.

关键词： Economic dispatch optimization algorithms particle swarm optimization power system operation

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SENSITIVITY ANALYSIS FOR SIMULATION-BASED optimization VIA METAMODELING TECHNIQUES

SENSITIVITY ANALYSIS FOR SIMULATION-BASED OPTIMIZATION VIA M...

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ASME Turbo Expo: Turbine Technical Conference and Exposition

作者： Liu, Haitao Ma, Ying Xu, Shengli Wang, Xiaofang Song, Yang Dalian Univ Technol Sch Energy & Power Engn Dalian Liaoning Peoples R China Aviat Ind Corp China Shenyang Engine Design & Res Inst Shenyang Liaoning Peoples R China

ISBN: (纸本)9780791856659

The sensitivity information of objective and constraint functions is required in gradient-based optimization algorithms. Usually the more accurate the gradients are estimated, the faster the convergence speed will be. Commonly used gradient estimation methods, e.g., the finite differences, either have low estimate accuracy or require much computing budget. This paper presents a metamodel-based gradient estimation (MGE) method. In our numerical investigations, the proposed MGE method achieves more accurate estimates of the sensitivity information than the forward difference method (FDM) with only one more point. This article explores the sensitivity of the proposed method to the sampling strategy, the metamodel type, the finite difference step on the metamodel and the dimensionality of the design space, and offers some recommendations. Finally, we combine the new MGE method with the method of moving asymptotes (MMA) and apply them to the shape design of a turbine disc and an axial compressor blade. The results from the two engineering examples confirm the utility of proposed method.

关键词： optimization Simulation Sensitivity analysis Shape design Design Turbines Disks Blades optimization algorithms Compressors

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Constrained optimization of Multi-color LED Light Sources for Color Temperature Control

Constrained Optimization of Multi-color LED Light Sources fo...

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12th China International Forum on Solid State Lighting (SSLCHINA)

作者： Gao, Yuan Wu, Haining Dong, Jianfei Zhang, G. Q. State Key Lab Solid State Lighting Changzhou Jiangsu Peoples R China Delft Univ Technol Delft Inst Microsyst & Nanoelect DIMES Delft Netherlands

ISBN: (纸本)9781509001767

Color temperature is one of the most significant characteristics for light sources due to its influence on human visual perception, circadian rhythm, emotion, work efficiency, and etc. Currently, it is common for LED light sources to render or tune color temperatures by mixing various color LEDs with different intensity. Existing methods can hardly take into consideration all the lighting requirements, including power consumption, luminous flux, spectrum components, and etc. In this paper, we first make a brief introduction on the significance of color temperature and emphasize the hazard of excess blue light. Then an optimization algorithm of light chromaticity is proposed for the design and control of LED light sources based on linear programming. Objective functions and constraints are described in details. In the optimal color rendering design, we simultaneously restrain the luminous flux, color temperature and the spectrum components of blue light. An example of LED light source design is taken to verify our approach. Results show that the proposed algorithm is able to fulfill the requirement of color temperature, while maintaining satisfied photometric and electrical performance comparing with conventional methods. The optimization algorithm is suitable for both color temperature control and rendering color light with targeted spectral components.

关键词： Color Light emitting diodes Light sources Lighting Linear programming optimization Power demand LIGHT SOURCES Light emitting diodes Power demand Lighting linear programming Color Constrained optimization SMIM10L2A gene optimization algorithms Temperature control

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New optimization Algorithm for Finding Distance Between Two Convex Sets

New Optimization Algorithm for Finding Distance Between Two ...

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2015 International Conference "Stability and Control Processes" in Memory of V.I. Zubov (SCP)

作者： Abbasov, Majid St Petersburg State Univ 7-9 Univ Skaya Nab St Petersburg 199034 Russia

ISBN: (纸本)9781467376983

Nature always inspires researchers of different fields. Physical analogies allow to get new efficient algorithms for various optimization problems. Well known and sufficiently studied heavy ball method is one of the representatives of such type of algorithm [1]-[8]. Another algorithm of this type is proposed in this work. It is developed for finding minimum distance between two convex sets.

关键词： optimization algorithms Convexity minimum distance SETTING FINDINGS Legislators efficient algorithm

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Low Impact Development Placement Investigation using a Multi-Objective Evolutionary optimization Algorithm

Low Impact Development Placement Investigation using a Multi...

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World Environmental and Water Resources Congress

作者： Giacomoni, Marcio H. Univ Texas San Antonio Dept Civil & Environm Engn One UTSA Circle San Antonio TX 78249 USA

ISBN: (数字)9780784479162

ISBN: (纸本)9780784479162

Low Impact Development (LID) controls, such as green roofs and pervious pavements, are alternative stormwater management strategies designed to better mimic the pre-development hydrologic flow regime and mitigate the impacts of urbanization. Many studies focused on monitoring and understanding the hydraulic behavior of individual LIDs, while the collective behavior of retrofitting urban watersheds with LID controls is less understood. This study applies a Multi-Objective Evolutionary Algorithm (MOEA) connected to a hydrologic model to find near-optimal solutions in terms of LID locations in urban watersheds. This methodology identifies the tradeoffs between the costs of retrofitting urban areas with LIDs and the environmental benefits provided by such measures, such as surface runoff volume and peak flow reduction. The benefit provided by LIDs is also evaluated through the use of the Hydrologic Footprint Residence (HFR), a new stormwater metric that better quantifies hydrologic alteration than peak flow alone. The HFR is a spatial and temporal metric that represents the dynamics of inundated areas and residence time of flood waves throughout downstream segments. The proposed methodology can help urban stormwater decision makers improve the sustainability of urban watersheds as it provides guidelines of LIDs placement under cost constraints.

关键词： Urban watersheds optimization algorithms optimal solution low impact Hydrologic models green roofs HFR REACTOR Environmental services tradeoffs Porous pavements

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Welding Parameter optimization Based on Gaussian Process Regression Bayesian optimization Algorithm 11

Welding Parameter Optimization Based on Gaussian Process Reg...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Sterling, Dillon Sterling, Tyler Zhang, YuMing Chen, Heping Texas State Univ Ingram Sch Engn San Marcos TX 78666 USA Univ Kentucky Dept Elect & Comp Engn Lexington KY 40506 USA

ISBN: (纸本)9781467381833

In welding processes, welding parameters have a significant impact on weld quality and mechanical properties of welded joints. For example, if the welding current is not tuned properly, the welding arc becomes unstable which will cause an unacceptable weld. Therefore welding parameters must be optimized in order to achieve best weld quality. However current methods have many limitations in exploring optimal welding parameters. In this paper, Gaussian Process Regression is applied to model the relationship between the welding performance indices and welding parameters. Bayesian optimization Algorithm is adopted to balance the modeling and optimization processes and optimize welding parameters. Experiments were performed for the Gas tungsten arc welding (GTAW) process and the results demonstrate the effectiveness of the proposed algorithm. Compared to the existing methods, the proposed method greatly improves the welding parameter optimization process;moreover it can be applied with fewer experiments compared with existing methods which will reduce the testing cost and effort.

关键词： Welding parameters Weld quality Parameter optimization Gas tungsten arc welding optimization Procedure Welding current performance indicators Solder Joint Device Component optimization algorithms TUNGSTEN INERT GAS WELDING Welding Welding technology Unstable Bayesian inference Gauss

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