Generalized Pattern Search

This paper presents a novel method for Multifocus image fusion that combines anisotropic diffusion PDE filtering and convolutional neural network (CNN) feature extraction. The proposed method aims to preserve image edges and details while reducing noise through the utilization of anisotropic diffusion PDE filtering. Additionally, a CNN architecture with ReLU activation function is employed for feature extraction. The method is evaluated on a dataset of Multifocus images and compared with traditional and CNN-based approaches, demonstrating superior performance in terms of visual quality and quantitative metrics, such as Normalized Mutual Information, Phase Congruency-based metric, and Structural Similarity-based metric. Furthermore, we aim to enhance our approach by incorporating machine learning techniques to optimize the parameters of the image fusion algorithm. By automatically adjusting these parameters, we strive to achieve the most reliable and accurate outcomes.

This paper describes a class of frame-based direct search methods for unconstrained and linearly constrained optimization. A template is described and analyzed using Clarke's nonsmooth calculus. This provides a unified and simple approach to earlier results for grid-and frame-based methods, and also provides partial convergence results when the objective function is not smooth, undefined in some places, or both. The template also covers many new methods which combine elements of previous ideas using frames and grids. These new methods include grid-based simple descent algorithms which allow moving to points off the grid at every iteration and can automatically control the grid size, provided function values are available. The concept of a grid is also generalized to that of an admissible set, which allows sets, for example, with circular symmetries. The method is applied to linearly constrained problems using a simple barrier approach.

A direct search method for nonlinear optimization problems with nonlinear inequality constraints is presented. A filter based approach is used, which allows infeasible starting points. The constraints are assumed to be continuously differentiable, and approximations to the constraint gradients are used. For simplicity it is assumed that the active constraint normals are linearly independent at all points of interest on the boundary of the feasible region. An infinite sequence of iterates is generated, some of which are surrounded by sets of points called bent frames. An infinite subsequence of these iterates is identified, and its convergence properties are studied by applying Clarke's non-smooth calculus to the bent frames. It is shown that each cluster point of this subsequence is a Karush-Kuhn-Tucker point of the optimization problem under mild conditions which include strict differentiability of the objective function at each cluster point. This permits the objective function to be non-smooth, infinite, or undefined away from these cluster points. When the objective function is only locally Lipschitz at these cluster points it is shown that certain directions still have interesting properties at these cluster points.

This paper reports the work done towards planning the trajectory for cooperative crane lifts. The location of the hook points between the pick and place positions are determined using a path-planner. These are inputs to the trajectory planner. The goal of the trajectory planner is to connect all the path-points while ensuring the overshoots, velocities, accelerations and jerk for each degree of freedom to be within acceptable limits for the system. A number of alternate techniques are available for defining the trajectory between the path-points. This paper reports on the evaluation of algebraic and trigonometric splines for trajectory planning. Splines of various orders were initially evaluated for a single joint. This evaluation found that 4 th order trigonometric splines were most appropriate. Hence, this was applied to a lift problem involving the 2x4 DOF cooperative manipulator system and the results are presented.

Te mapping of the OA Entry (i.e. Scheda OA), the Italian most general content standard for cataloguing works of art, to RDF is based upon a subset of cataloguing elements described in the version 3.00 of the aforementioned standard 1 , released in February 2014 by the Istituto Centrale per il Catalogo e la Documentazione (ICCD). Although the OA Entry may be mainly considered a national cataloguing reference, also international stakeholders can beneft from this mapping document, which is a set of shareable descriptive elements for works of art. Te purpose of this mapping is indeed to ensure semantic interoperability among data providers wanting to publish their structured data about works of art in RDF as Linked Open Data. Terefore, this document provides a guidance to map metadata elements name to ontology terms as defned in well-known vocabularies, e.g., the CIDOC Conceptual Reference Model (CRM) 2 , and by means of ontologies that have been appropriately developed for describing specifc aspects of the OA Entry standard. Hence, wherever needed, to avoid a lack of information, best suitable terms from other vocabularies have been adopted or created for the scope. Te result is a new ontology, the OA Entry Ontology 3 , which itself imports several other ontologies and vocabularies, including: DCTerms (Dublin Core Metadata Terms) 4 , FOAF (Friend of a Friend Vocabulary) 5 , PROV (Provenance Ontology) 6 , HiCO (Historical Context Ontology) 7 , supplemented by terms from FEO (F Entry Ontology) 8 , from an OWL2 DL version of FRBR (Functional Requirements for Bibliographic Records) 9 , and from the following SPAR (Semantic Publishing and Referencing) Ontologies 10 : CiTO (Citation Typing Ontology) 11 , FaBiO (FRBR-aligned Bibliographic Ontology) 12 , and PRO (Publishing Roles Ontology) 13 . Te OA Entry Ontology also provides new entities that were lacking elsewhere: two object properties defning a direct relation between OA Entry and the described work of art; twenty-nine classes and four object properties to describe relations between works of art (see Table ). Moreover, OA Entry extends the PRO Ontology -providing several named individual for representing specifc roles involved in cataloguing and in the arts domain, grouped in two subclasses (oaentry:CataloguingRole and oaentry:ArtisticRole) -and the HiCo Ontology with several individuals specifying types of interpretation underlying questionable information.

Tonality – or the feeling of key in music – achieved crisp theoretical definition in the early 20th century, even as the musical avant-garde pronounced it obsolete. The notion of a general collapse or loss of tonality, ca. 1910, remains influential within music historiography, and yet the textbook narrative sits uneasily with a continued flourishing of tonal music throughout the past century. Tonality, from an early 21st-century perspective, never did fade from cultural attention; but it remains a prismatic formation, defined as much by ideological-cultural valences as by its role in technical understandings of musical practice. Tonality 1900–1950: Concept and Practice brings together new essays by 15 leading American and European scholars.

This contribution focuses on the so-called “Virtual Building Explorer (VBE)”, an adapted game-engine, which is now being used for communicating architectural information as it provides an interactive display of 3D scenes. The paper discusses the handling of this software and the creation of self-running applications. It also offers a comparison with other applications with a similar 3D visualisation performance profile. The aim is to test suitability of the software packages for establishing 3D walkthrough models of sacred buildings, based on existing 3D models of destroyed Viennese synagogues. The paper explores and explains the conditions for data conversion and any follow-up uses. While certain restrictions exist, potential benefits for the virtual reconstruction context can be identified.

This contribution focuses on the so-called “Virtual Building Explorer (VBE)”, an adapted game-engine, which is now being used for communicating architectural information as it provides an interactive display of 3D scenes. The paper discusses the handling of this software and the creation of self-running applications. It also offers a comparison with other applications with a similar 3D visualisation performance profile. The aim is to test suitability of the software packages for establishing 3D walkthrough models of sacred buildings, based on existing 3D models of destroyed Viennese synagogues. The paper explores and explains the conditions for data conversion and any follow-up uses. While certain restrictions exist, potential benefits for the virtual reconstruction context can be identified.

To compare the difference between primary homoeopathic and conventional paediatric care in treating acute illnesses in children in their first 24 months of life. One hundred eight Indian singleton newborns delivered at 37 to 42 weeks gestation were randomised at birth (1:1) to receive either homoeopathic or conventional primary care for any acute illness over the study period. In the homoeopathic group, conventional medical treatment was added when medically indicated. Clinicians and parents were unblinded. Children in the homoeopathic group experienced significantly fewer sick days than those in the conventional group (RR: 0.37, 95% CI: 0.24-0.58; p < 0.001), with correspondingly fewer sickness episodes (RR: 0.53, 95% CI: 0.32-0.87; p = .013), as well as fewer respiratory illnesses over the 24-month period. They were taller (F (1, 97) = 8.92, p = .004, partial eta squared = 0.84) but not heavier than their conventionally treated counterparts. They required fewer antibiotics, and their treatment cost was lower. Conclusion: Homoeopathy, using conventional medicine as a safety backdrop, was more effective than conventional treatment in preventing sick days, sickness episodes, and respiratory illnesses in the first 24 months of life. It necessitated fewer antibiotics and its overall cost was lower. This study supports homoeopathy, using conventional medicine as a safety backdrop, as a safe and cost-effective primary care modality during the first 2 years of life. Trial registration: Clinical Trial Registry-India (2018/09/015641). https:// ctri. nic. in/ Clini caltr ials/ login. php What is Known: • Due to their holistic nature, many Complementary and Alternative Medical (CAM) modalities are not readily amenable to assessment by headto-head RCT for a given Indication. • We propose a pragmatic, RCT comparing homoeopathic with conventional medicine as a system. What is New: • Homoeopathic was apparently superior to conventional primary care in preventing sick days, sickness episodes, and respiratory illness episodes and was significantly associated with growth in height but not weight and required fewer antibiotics in children from birth to 24 months of age. Keywords Complementary and alternative medicine (CAM) • Antimicrobial resistance • Infant and toddler primary care • Homoeopathy • Respiratory illness • Diarrhoea Abbreviations ANOVA Analysis of variance CCRH Central Council for Research in Homoeopathy HC Head circumference IQR Interquartile range JIMS Jeeyar Integrated Medical Services mITT Modified intention-to-treat analysis MUAC Mid-upper arm circumference RCT Randomised controlled trial Communicated by Peter de Winter Menachem Oberbaum and Anupriya Chaudhary contributed equally to this work.

1.0 Introduction Waterflooding process is a secondary oil recovery effort that involves injection of water into an oil well reservoir to increase the underground pressure thereby increasing oil recovery (Grema and Cao, 2016). However, waterflooding processes are faced with constitutive recovery mechanism in terms of well placements, which determines the maximal recovery of oil at a given point in time. Well placements predominantly play a role as regards to production rates which serves as a consideration to which various oil companies identify in order to determine oil-water ratio (Grema and Cao, 2017). The placement of injection wells determines the oil and water production rates. It is for this reason that estimation of oil recovery in terms of well placements is considered. Reservoir models are expressed by nonlinear partial differential equations (PDEs) which constitute unsteady states and dimensions in the region of time and space (Grema and Cao, 2017). There are a lot of exor...

Background: With change in the lifestyle peoples are suffering from haemorrhoids as a major health issue. It affects anal region and creates physical and psychological disturbances resulting in significant compromise in the quality of life. Primary objective of this study was to find out the efficacy of homoeopathic management in terms of pain, bleeding and itching in haemorrhoids. Secondary objective was to measure its effect in quality of life. Materials and methods: In this observational study haemorrhoids patients were managed using proctological symptom scale for measuring complaints intensity and WHOQOL-BREF (Field Trial Version, domain 1) for assessing quality of life. Result: A total of 42 patients were intervened as per individualized Homoeopathic principles and followed up to 6 months. Intention to treat population (n = 42) was analyzed in the end. Statistically significant reductions for mean pain score from 5.88 to 1.69 (95% CI t = −9.0835, P &lt; 0.00001); reduction of ...

The purpose of this research is to determine an estimate for actual optimal oil recovery through cyclic Gas-Assisted Gravity Drainage (GAGD) process in a heterogeneous sandstone reservoir under geological uncertainties. A robust optimization approach was adopted to determine the optimal durations of gas injection, soaking, and oil production under geological uncertainties. 100 stochastic reservoir realizations of the 3D permeability and porosity distributions were created to honor geological constraints. Ranking was applied through quantifying of reservoir oil response to select P10, P50, and, P90 that represent the overall reservoir uncertainty. A compositional reservoir flow simulation was used for the GAGD process performance evaluation. Approximately 200 simulation jobs were created, including the aforementioned durations and geological uncertainty parameters, through Design of Experiments (DoE). The Latin Hypercube Sampling was adopted to create these 200 simulation jobs that then evaluated by the compositional reservoir simulation to calculate the cumulative oil production by the end of 10 prediction years. The robust optimization approach was then applied to select the true optimal solution of the highest oil recovery by taking into account the geological uncertainties in permeability, porosity, and anisotropy models. The nominal optimization of one single realization was also adopted for the comparison. The robust optimization has shown its feasibility to increase oil production through the cyclic GAGD process from 4.535 to 4.62547 billion barrels. However, the nominal optimization case increased oil production to 5.9726 billion barrels. The presented robust optimization workflow under geological uncertainties resulted in higher oil recovery and net present value than nominal realization optimization, with providing degrees of freedom for the decision-maker to significantly reduce the project risk. It was specifically concluded that the robust optimal solution represents the most economically feasible solution to obtain the highest NPV through the GAGD process for a range $(30-80) per barrel oil prices. However, the base case and nominal solution (no geological uncertainties) were not economical when the oil price declines to be less than 36 and 32, respectively.

Molluscum contagiosum (MC) is an infection caused by an antigenically different type of poxvirus called Molluscipox virus. It is also called water warts and its skin lesion is also known as Mollusca, this is prevailing in children but adults are also affected. This is a self-limiting disease but takes 6-9 month to cure. In this case a 04 years old boy suffering from molluscum contagiosum since 15 days, treated with individualized homoeopathic medicine Bromium 30C which is mention in Boericke's repertory and take cure within 02 months of treatment. The case was documented photographically at the onset and the end of the treatment. Homoeopathic medicines which were mentioned in Boericke's repertory may be effective for the treatment of molluscum contagiosum. Modified Naranjo criteria: Total score 8.

Acute Diarrhoea is a manifestation under "Gastrointestinal Disorders" and many other clinical conditions. A clinical, non-comparative, randomised study was undertaken to analyse the effect of the homoeopathic remedies in acute diarrhoeal conditions by using clinical bedside homoeopathic repertory "Bell's Diarrhoea", to reach the exact similimum of the patient and with the help of auxiliary mode of treatment i.e. proper diet management. 97% of cases were cured which clearly indicates that homoeopathic remedies definitely has the power to cure the acute diarrhoeal condition 9 .So there is a wide scope for proper management and treatment of acute infective diarrhoea in Homoeopathy. As in our system of medicine we do not treat the disease but we treat the individual who is suffering. Through individualization with constitutional remedy (Approach) we can treat both acute as well as the chronic phase of disease, to prevent further recurrence and complications of the disease. 9 articles were collected which are related to the homoeopathic management of acute infective diarrhoea. All these articles were collected from various database, year and publishers, that is from 2003 to 2022 from the database like Google scholar. All these articles supported the homoeopathic management in treatment of acute infective diarrhea.

Consider the optimization of a stochastic system in which the objective is to find a set of controllable system parameters that minimize some performance measure of the system. This situation is representative of many real-world optimization problems in which random noise is present in the evaluation of the objective function. In many cases, the system is of sufficient complexity so that the objective function, representing the performance measure of interest, cannot be formulated analytically and must be evaluated via a representative model of the system. In particular, the use of simulation is emphasized as a means of characterizing and analyzing system performance. The term simulation is used in a generic sense to indicate a numerical procedure that takes as input a set of controllable system parameters (design variables) and generates as output a response for the measure of interest. It is assumed that the variance of this measure can be reduced at the expense of additional computational effort, e.g., repeated sampling from the simulation. Applications involve the optimization of system designs where the systems under analysis are represented as simulation models, such as those used to model manufacturing systems, production-inventory situations, communication or other infrastructure networks, logistics support systems, or airline operations. In these situations, a search methodology is used to drive the search for the combination of values of the design variables that optimize a system measure of performance. A model of such a stochastic optimization methodology via simulation is depicted in Figure 1.1. 16. SECURITY CLASSIFICATION OF: 19a. NAME OF RESPONSIBLE PERSON James W. Chrissis, AFIT/ENS a. REPORT

Trajectory optimization of a robot manipulator consists of both optimization of the robot movement as well as optimization of the robot end-effector path. This paper aims to find optimum movement parameters including movement type, speed, and acceleration to minimize robot energy. Trajectory optimization by minimizing the energy would increase longevity of robotic manipulators. We utilized particle swarm optimization method to find the movement parameters leading to minimum energy consumption. The effectiveness of the proposed method is demonstrated on different trajectories. Experimental results show that 49% efficiency was obtained using a UR5 robotic arm. I.

Evaluation of the economic benefit of field development projects in the oil and gas industry is naturally subject to subsurface uncertainties and risks. While high economic returns from produced volumes compensated for the lack of robust uncertainty estimates in the past, lower margins in tight market conditions and more complex project designs require increased efforts in delivering reliable uncertainty estimates for improving reservoir management decision support in times to come. An increasing number of field development projects include rigorous uncertainty quantification workflows based on parameterized subsurface uncertainties. Estimation and reduction of prediction uncertainty has no value unless it can potentially influence a decision process. This requires an integrated workflow design across disciplines and a proper risk mitigation plan. This work presents the implementation of an uncertainty workflow in reservoir management with a focus on reservoir modeling and simulation. Practical workflow design steps and intermediate milestones are discussed for generating alternative reservoir model realizations including historical production data. Calibrated model realizations define the basis for prediction estimates of a predefined field development plan. Practical steps are discussed with application to a complex oil rim development for an existing reservoir with long production history. This study aimed at an uncertainty assessment of a field development plan and a proposal for optimized relocations of infill wells considering multiple geological realizations. In conclusion, this work describes examples, experiences, and recommendations for an industry implementation for a risk assessment of a field development plan under subsurface uncertainties.

The main goal of every investor to invest should be to get a return on the invested capital, for this purpose, investors should see the financial performance of the company before investing. The main purpose of this research is to determine whether the financial performance measured by net profit is affected by the current ratio variable, the total asset turnover ratio, the debt / asset ratio and the return on equity. The population in this study consists of 10 manufacturing companies in the pharmaceutical subsector. This study uses purposeful sampling technique to determine which sample to take, and there are 8 companies sampled because they meet the specified sampling criteria. Data collection techniques using documentation techniques. The results of the hypothesis test using the t test show that the current ratio does not have a positive effect on net profit at the t number <t table 0.375 <2.0422 and a significant 0.710> 0.05 level, the total asset turnover ratio is positive. net profit t> t table 2.248> 2.0422 and a significant level 0.031 <0.05, debt / asset ratio-t number <-t has no positive effect on net profit, i.e.-1.536 <-2.0422 and 0.134> 0.05 a significant level at the level of return on equity, t number> t table 2.109> 2.0422 and significant 0.042 <0.05 have a positive effect on net profit. The results of the hypothesis test using the F test, current ratio, total asset turnover ratio, debt / asset ratio and net profit at the same time of return on equity, 3.292> 2.69 with the table t> t and a significant 0.022 <0.05.

The efficiency of water flooding processes can be improved by installing intelligent wells which are good candidates for control and optimization. Optimal control theory based on adjoint formulations was found to be efficient for reservoir optimization. However, this solution approach is local and may not be suitable for comparing design alternatives. In this work, an approach for determining an optimal starting point for optimal control theory procedure was developed to give near global optima. The performance in terms of net present value (NPV) of two forms of five-spot pattern was compared. The method results to similar performances of the two alternatives because it was formulated to give true optimal solution trajectories. It was found that regular five-spot pattern results to a NPV in excess of $4,900 over inverted design. Respective increase in oil and water productions of 0.23% and 0.22% were recorded for former design against the later.Keywords: intelligent wells; adjoint; ...

In several robot applications the spatial trajectories of the robot motion are defined by the user, and must be tracked precisely. Executing the prescribed spatial trajectories of the motion of a robot, the dynamic properties of the robot can be considered. The maximum velocity, acceleration and jerk of each joint of the robot determine limits of the motion. Therefore, the real-time trajectory generation should consider all of these limits to produce near time-optimal motion. The proposed method of this paper is an optimized version of a jerk switching trajectory planning algorithm (MSRS), which considers the maximum joint velocity, acceleration and jerk properties. Modification of corner points at the end of the list or adding new ones can be performed real-time.

A novel continuous genetic algorithm (CGA) along with distance algorithm for solving collisions-free path planning problem for robot manipulators is presented in this paper. Given the desired Cartesian path to be followed by the manipulator, the robot configuration as described by the D-H parameters, and the available stationary obstacles in the workspace of the manipulator, the proposed approach will autonomously select a collision free path for the manipulator that minimizes the deviation between the generated and the desired Cartesian path, satisfy the joints limits of the manipulator, and maximize the minimum distance between the manipulator links and the obstacles. One of the main features of the algorithm is that it avoids the manipulator kinematic singularities due to the inclusion of forward kinematics model in the calculations instead of the inverse kinematics. The new robot path planning approach has been applied to two different robot configurations; 2R and PUMA 560, as n...

Determining optimum infill well placement has been one of most challenging events in overall field development strategy of any types of field. Because there could be a large number of possible candidates for new infill well locations, it is not practically feasible to evaluate all candidate locations, particularly at high-resolution geological models including millions of geological cells. Conventional static measure maps generally used in the industry has limited applicability as this does not address dynamic fluid flow and interference between existing wells. In contrast, direct application of stochastic search optimization methods such as genetic algorithms to large-scale field models may better account for dynamically changing reservoir conditions but can be complex to apply or computationally expensive. We propose a novel method for infill well placement optimization designed as a two-stage optimization based on both dynamic flow diagnostic characteristics and genetic algorithm optimization methods. The main advantage of the proposed method over the conventional approach of using static reservoir property maps is its ability to integrate static reservoir properties with dynamic variables such as sweep efficiencies. By incorporating sweep efficiencies, new infill well potential map is generated to guide the optimization. The other benefits of this method are its maneuverability and capability to search in a narrower and tight space making the evolutionary algorithm an appropriate choice to identify rewarding locations which was not practically applicable due to the significant computational burden. The proposed automated workflow is seamlessly integrated from building a simulation model to performing reservoir simulation and conducting the optimization process. The workflow is combined with novel engineering methods to identify best rewarding well location areas, and to identify strategies to maximize sweep efficiency through optimizing well placement and completion strategies resulting in substantial engineering time-savings. The power and utility of the proposed workflow are first demonstrated by a synthetic example and then applied to a full field model. Strategies to improve incremental oil recoveries were identified with a proposed novel, iterative and robust workflow.

A Cartesian trajectory tracking system for manipulators is developed using optimal control theory. By including the Cartesian position in the state vector, transformation of the trajectory from Cartesian space to manipulator joint space is avoided, and the Jacobian mat rix need not be inverted. The tra ck ing system may also be applied to kinematically redundant manipulators. For this type of manipulators , singularities are avoided by choosing a suitable performance index in the optimal control problem. Simulation using a simple kinematically redundant manipulator show that a small tracking er r or can be achieved with low motor torques.

A Cartesian trajectory tracking system for manipulators is developed using optimal control theory. By including the Cartesian position in the state vector, transformation of the trajectory from Cartesian space to manipulator joint space is avoided, and the Jacobian mat rix need not be inverted. The tra ck ing system may also be applied to kinematically redundant manipulators. For this type of manipulators , singularities are avoided by choosing a suitable performance index in the optimal control problem. Simulation using a simple kinematically redundant manipulator show that a small tracking er r or can be achieved with low motor torques.

This stimulating collection attempts to rethink traditional Japanese culture in sophisticated contemporary terms. A remarkable upshot is that as Japan is brought into new perspective, the Western tradition itself is subtly altered 190 Japanese Journal o f Religious Studies 23/1-2 and takes on Japanese inflections. In his keynote paper, Steve Odin draws on Zen, the Kyoto school, and Japa nese novels and films for a persuasive defence of Roland Barthes’s account of Japan as “a radically dislocated and uncentered text constituted by ‘empty’ signs ” ( p.19). Richard B. Pilgrim correlates Japanese intervals (ma) with a poststructuralist mapping of interstices and traces. In Japanese art, intervals or spaces—pregnant nothingness—serve as an empty ground against which the figures stand forth; the deep sense of the work of art shines through these gaps in its form. Japanese religion exhibits a similar texture: the sacred spaces of Shinto are “designed to be open, cleared out, and pure in an...

In this work, the well control optimization of the Olympus challenge is solved by two non-intrusive strategies that use the simulator as a black box. This reservoir model contains uncertainties on geological scenarios, in which the optimal management process is conducted through robust optimization, which can use a set of representative realizations to honor the statistics of the geological properties. The statistic considered here is the mean of the net present value (NPV). Control variables are flow rates and bottom hole pressures (BHP) of each well completion. The first strategy used here is the sequential approximate optimization (SAO) with variable reparameterization that uses polynomial control trajectories. In order to reduce the computational cost of the overall process, this strategy builds surrogate models to be used in the several function calls required in the optimization process. The other strategy is the refined ensemble-based (REB) method that computes the approximate gradient of the expected NPVas a sum of the columns of a refined sensitivity matrix obtained from ensemble-based covariance matrices of controls and cross-covariance between well NPVs and controls. The use of small-sized ensembles introduces spurious correlations that degrade gradient quality. Non-distance-based localization and competitiveness coefficients between producer wells and smoothing control trajectories are used to reduce spurious correlations. Both strategies use approximate derivatives and they are able to include any general nonlinear constraints. The SQP (sequential quadratic programming) is the algorithm used in both methodologies. The strategies produced similar results, are close to the reactive control solution, and are viable alternatives for robust optimization problem and the choice depends mostly on the number of control variables.

In this work, we present a modification (refinement) of the ensemble-based method for constrained waterflooding optimization. The problem of determining life-cycle rate controls for both producer and injector wells that maximize the net present value, NPV, subject to well and field-wide capacity constraints is formulated and solved using sequential quadratic programming, SQP. The required gradient is approximately computed by an ensemble-based method. Field NPV is decomposed as the sum of the NPVs of each well. Sensitivity matrix of well NPVs with respect to controls of all wells is obtained from ensemble-based covariance matrices of controls and of well NPVs to controls. For efficiency reasons, ensemble size should be kept small which results in sampling errors. The approximate gradient is the sum of the columns of the refined sensitivity matrix. Using small-sized ensembles introduces spurious correlations that degrade gradient quality. Novel nondistance-based localization technique is employed to mitigate the deleterious effects of spurious correlations to refine the sensitivity of NPV of production wells with respect to injector controls. The localization technique is based on the connectivity of each injector/producer pair using a producer-based capacitance resistance model (CRMP). Competitiveness coefficients are developed to refine sensitivity of NPV of production wells with respect to producer controls, obtained using an interference test. A new procedure is proposed for consideration of maximum water-cut limit resulting in producer shut-in during the optimization process. Smoothing techniques are also introduced to avoid excessive abrupt jumps in well controls and to improve the overall optimization efficiency. Procedures and refinements are applied to a realistic reservoir taken from the literature, TNO Brugge Field, to demonstrate the resulting level of objective function improvement and variability reduction of the obtained solutions. NPV solution statistics are obtained for 20 independent runs. Using proposed refinements, smoothing and water cutting techniques, NPV is improved by up to 25.4% above the traditional ensemble-based methods.

The problem of determining life-cycle rate controls for both producer and injector wells that maximize the net present value subject to well and field-wide capacity constraints is solved using an SQP algorithm. The required gradient is approximately computed by an ensemble-based method. Refinement techniques are employed to mitigate deleterious effects of spurious correlations and to improve the overall optimization efficiency. Control variables are rates of each well completion assumed independently controlled. Field NPV is decomposed as the sum of the NPV's of each well. Sensitivity matrix of well NPV's with respect to controls of all wells is obtained from ensemble-based covariance matrices of controls and of well NPV's to controls. For efficiency reasons ensemble size should be kept small which results in sampling errors. Since covariance matrixes are plagued with spurious correlations, regularization and novel non-distance-based localization techniques are required to improve the quality of the resulting sensitivity matrix. The effective approximate gradient is the sum of the columns of the refined sensitivity matrix. Three realistic reservoirs taken from the literature are used to demonstrate the efficiency of the refinement techniques. Realizations are generated from optimization iterates by adding temporally correlated random perturbations. Realizations go through a scaling procedure that ensures feasibility of all ensemble members. At the start of the optimization process simulation results of ensemble members are used to compute inter-well connectivities using a Producer-based Capacitance Resistance Model (CRMP) and competitiveness coefficients between producers using an Interference Test. Sensitivity of producer NPV's with respect to injector well controls are refined through a novel localization technique based on the connectivity of each injector/producer pair. Sensitivity of producer NPV's with respect to producer well controls is regularized by competitiveness coefficients keeping the coefficients of each well with respect to its own controls and weight averaging the effects of other producer well controls. Sensitivity of injector NPV's with respect to controls of producer and other injection wells are regularized depending on the actual realization of input injection rate controls by the simulator during control steps. NPV gains up to 15% of the average NPV values in twenty runs are obtained with much reduced scatter in comparison with solutions without refinement. The proposed regularization and novel non-distance-based localization techniques for refinement of the sensitivity matrix in ensemble-based waterflooding optimization, which automatically detects sealing faults and regions of low permeability, results in significant gains in NPV values and reduction in their variability. The added numerical cost is insignificant as previous simulation results are reused. The simulator is treated as a black-box in the optimization process and actual production history may be used in the localization criterion.

Proxy models are widely used to estimate parameters such as interwell connectivity in the development and management of petroleum fields due to their low computational cost and not require prior knowledge of reservoir properties. In this work, we propose a proxy model to determine both oil and water production to maximize reservoir profitability. The approach uses production history and the Capacitance and Resistance Model based on Producer wells (CRMP), together with the combination of two fractional flow models, Koval [Cao (2014) Development of a Two-phase Flow Coupled Capacitance Resistance Model. PhD Dissertation, The University of Texas at Austin, USA] and Gentil [(2005) The use of Multilinear Regression Models in patterned waterfloods: physical meaning of the regression coefficient. Master’s Thesis, The University of Texas at Austin, USA]. The proposed combined fractional flow model is called Kogen. The combined fractional flow model can be formulated as a constrained nonlinea...

In this work, we present a modification (refinement) of the ensemble-based method for constrained waterflooding optimization. The problem of determining life-cycle rate controls for both producer and injector wells that maximize the net present value, NPV, subject to well and field-wide capacity constraints is formulated and solved using sequential quadratic programming, SQP. The required gradient is approximately computed by an ensemble-based method. Field NPV is decomposed as the sum of the NPVs of each well. Sensitivity matrix of well NPVs with respect to controls of all wells is obtained from ensemble-based covariance matrices of controls and of well NPVs to controls. For efficiency reasons, ensemble size should be kept small which results in sampling errors. The approximate gradient is the sum of the columns of the refined sensitivity matrix. Using small-sized ensembles introduces spurious correlations that degrade gradient quality. Novel nondistance-based localization technique is employed to mitigate the deleterious effects of spurious correlations to refine the sensitivity of NPV of production wells with respect to injector controls. The localization technique is based on the connectivity of each injector/producer pair using a producer-based capacitance resistance model (CRMP). Competitiveness coefficients are developed to refine sensitivity of NPV of production wells with respect to producer controls, obtained using an interference test. A new procedure is proposed for consideration of maximum water-cut limit resulting in producer shut-in during the optimization process. Smoothing techniques are also introduced to avoid excessive abrupt jumps in well controls and to improve the overall optimization efficiency. Procedures and refinements are applied to a realistic reservoir taken from the literature, TNO Brugge Field, to demonstrate the resulting level of objective function improvement and variability reduction of the obtained solutions. NPV solution statistics are obtained for 20 independent runs. Using proposed refinements, smoothing and water cutting techniques, NPV is improved by up to 25.4% above the traditional ensemble-based methods.

The problem of determining life-cycle rate controls for both producer and injector wells that maximize the net present value subject to well and field-wide capacity constraints is solved using an SQP algorithm. The required gradient is approximately computed by an ensemble-based method. Refinement techniques are employed to mitigate deleterious effects of spurious correlations and to improve the overall optimization efficiency. Control variables are rates of each well completion assumed independently controlled. Field NPV is decomposed as the sum of the NPV's of each well. Sensitivity matrix of well NPV's with respect to controls of all wells is obtained from ensemble-based covariance matrices of controls and of well NPV's to controls. For efficiency reasons ensemble size should be kept small which results in sampling errors. Since covariance matrixes are plagued with spurious correlations, regularization and novel non-distance-based localization techniques are required to improve the quality of the resulting sensitivity matrix. The effective approximate gradient is the sum of the columns of the refined sensitivity matrix. Three realistic reservoirs taken from the literature are used to demonstrate the efficiency of the refinement techniques. Realizations are generated from optimization iterates by adding temporally correlated random perturbations. Realizations go through a scaling procedure that ensures feasibility of all ensemble members. At the start of the optimization process simulation results of ensemble members are used to compute inter-well connectivities using a Producer-based Capacitance Resistance Model (CRMP) and competitiveness coefficients between producers using an Interference Test. Sensitivity of producer NPV's with respect to injector well controls are refined through a novel localization technique based on the connectivity of each injector/producer pair. Sensitivity of producer NPV's with respect to producer well controls is regularized by competitiveness coefficients keeping the coefficients of each well with respect to its own controls and weight averaging the effects of other producer well controls. Sensitivity of injector NPV's with respect to controls of producer and other injection wells are regularized depending on the actual realization of input injection rate controls by the simulator during control steps. NPV gains up to 15% of the average NPV values in twenty runs are obtained with much reduced scatter in comparison with solutions without refinement. The proposed regularization and novel non-distance-based localization techniques for refinement of the sensitivity matrix in ensemble-based waterflooding optimization, which automatically detects sealing faults and regions of low permeability, results in significant gains in NPV values and reduction in their variability. The added numerical cost is insignificant as previous simulation results are reused. The simulator is treated as a black-box in the optimization process and actual production history may be used in the localization criterion.

In this work, the well control optimization of the Olympus challenge is solved by two non-intrusive strategies that use the simulator as a black box. This reservoir model contains uncertainties on geological scenarios, in which the optimal management process is conducted through robust optimization, which can use a set of representative realizations to honor the statistics of the geological properties. The statistic considered here is the mean of the net present value (NPV). Control variables are flow rates and bottom hole pressures (BHP) of each well completion. The first strategy used here is the sequential approximate optimization (SAO) with variable reparameterization that uses polynomial control trajectories. In order to reduce the computational cost of the overall process, this strategy builds surrogate models to be used in the several function calls required in the optimization process. The other strategy is the refined ensemble-based (REB) method that computes the approximate gradient of the expected NPVas a sum of the columns of a refined sensitivity matrix obtained from ensemble-based covariance matrices of controls and cross-covariance between well NPVs and controls. The use of small-sized ensembles introduces spurious correlations that degrade gradient quality. Non-distance-based localization and competitiveness coefficients between producer wells and smoothing control trajectories are used to reduce spurious correlations. Both strategies use approximate derivatives and they are able to include any general nonlinear constraints. The SQP (sequential quadratic programming) is the algorithm used in both methodologies. The strategies produced similar results, are close to the reactive control solution, and are viable alternatives for robust optimization problem and the choice depends mostly on the number of control variables.

Optimization in Robotics are applied to find the best solution for increasing the 3D space precision, reduce the vibrations, choose the optimal applied base point of the robots to minimize the time of application, finding constructive or functional parameters that ensure reduced energy consumption, reduce the vibration and increase the stability of the movement, choose the optimal variation of the moments in all joints, finally to optimize the dynamic behavior. In the work was developed one proper algorithm to obtain, iteratively the extreme performances to the 3D space trajectory without vibration in the desirable field of the Fourier spectrum. The research show how can be increased the accuracy of the internal coordinate by solving the inverse kinematics with proper method with the goal to touch the extreme precision better than 0.001mm. Index Terms-Forward kinematics, Inverse kinematics, fourier generator, inverse kinematics, neural network, smart damper system. I. GENERALITY ABOUT THE OPTIMIZATION WORK Optimization means finding the best solution for a problem under given circumstances. Mathematical optimization means that the problem to have solving must be respect one objective function, the constraints for all imposed parameters and one iterative algorithm that was validated by the experimental assisted research. Many problems in robotics require optimization of multiple conflicting criteria, such as the speed of a system and its energy efficiency, or precision and stability. The optimization problem can be single or multi-objective problem. In the multi-objective optimization (MOO) problem, these multiple objectives are treated independent between them. Instead of a single optimum, this gives rise to a set of Pareto optimal solutions, termed the Pareto set [1]-[7]. Another important consideration when optimizing the performance of a robotic system is that the optimization work can be expensivesuch as time of assisted research, financial cost, or use of computational resources. In this work we consider a single objective function for different optimization proposed ways. In the expensive MOO case, the goal is to reduce the number of experiments needed to find the Pareto solutions. Methods such as descent gradient method or genetic algorithms are not designed to limit the number of objective functions. When it comes to design optimization, Papalambros et al. give the following definition in [8]: "Informally, but

One of the most important problem to solve in the robots Kinematics and Dynamics is analyze of the joint's angular and linear accelerations. Because the movements of the robot's bodies going in the 3D space, the mathematical algorithm must be written in the complex matrix form. The paper show how some cases of the trapezoidal relatives' velocities characteristics in a joints determine the variation of the acceleration's vectors in the 3D space. The maximal values of these variations of the angular and linear accelerations influence the variation of the moments and forces. The analyze was made by using the Neutrosophic theory and vitual LabVIEW instrumentation. In a literature are described some methods of the assisted analyze of the acceleration without show the used mathematical model, without one critical analyze of the cases that must be avoid and finally without some conclusions for the researchers. The paper shown all LabVIEW virtual instruments (VI) used for this assisted research. By solving the assisted research of the acceleration will be open the way to the assisted research of the robots' dynamic behavior, to choose the optimal constructive and functional parameters (dimensions of the bodies, simultaneously, successive or complex configurations of the movements in the robot's joints, optimal values of the constant relative joint's velocities, etc.) of the robots to obtain the minimum variation of the forces and moments. The method that was shown in the paper solves one small part of the complex problems of the robot's kinematics and dynamics.

Direct search is a methodology for derivative-free optimization whose iterations are characterized by evaluating the objective function using a set of polling directions. In deterministic direct search applied to smooth objectives, these directions must somehow conform to the geometry of the feasible region, and typically consist of positive generators of approximate tangent cones (which then renders the corresponding methods globally convergent in the linearly constrained case). One knows however from the unconstrained case that randomly generating the polling directions leads to better complexity bounds as well as to gains in numerical efficiency, and it becomes then natural to consider random generation also in the presence of constraints. In this paper, we study a class of direct-search methods based on sufficient decrease for solving smooth linearly constrained problems where the polling directions are randomly generated (in approximate tangent cones). The random polling directions must satisfy probabilistic feasible descent, a concept which reduces to probabilistic descent in the absence of constraints. Such a property is instrumental in establishing almost-sure global convergence and worst-case complexity bounds with overwhelming probability. Numerical results show that the randomization of the polling directions can be beneficial over standard approaches with deterministic guarantees, as it is suggested by the respective worst-case complexity bounds.

Recently production optimization has achieved increasing attention in upstream petroleum industry. Here, we evaluate derivative free optimization methods for determination of the optimal production strategy using a numerical reservoir model which was prepared for a comparative study at the SPE Applied Technology Workshop in Brugge, June 2008. The pattern search Hooke-Jeeves, the reflection simplex Nelder-Mead, a new line-search derivative-free and a generalized pattern search methods are applied to the optimization problem. The line-search derivative-free algorithm is developed based on the existing line-search derivative free algorithms in combination with the Hooke-Jeeves pattern search method. The derivative free optimization results are compared with a gradient based sequential quadratic programming algorithm, but we clearly identify some issues limiting the performance of gradient based algorithms. In real applications our optimization problem is facing very costly function evaluations and at the same time one might have limitations in the computational budget. Therefore we are interested in methods that can improve the objective function with few function evaluations. The line-search derivative-free method performs more efficient and better than the other optimization methods. Ranking among the other four methods is somewhat more difficult, except that the Nelder-Mead method clearly has the slowest performance among these methods. We also observed that optimization with sequential quadratic programming had a high risk of getting trapped in a local optimum, which could be explained by properties of the objective function.

The research led us to a generalized formulation for the N-Pendulum [Simple] system, encompassing both dragless and drag-inclusive scenarios. The mathematical framework presented herein provides a comprehensive and rigorous basis for understanding the dynamic behavior of such pendulum configurations.

Our curiosity led us to explore the behavior of an infinite pendulum system. Subsequently, we engaged in a research.

This paper is concerned with waterflood optimization of oil recovery from thin oil rims of gascondensate fields. Such fields are notorious for gas and water coning problems, i.e. early gas or water breakthrough in producing wells, causing low recovery efficiency. The optimization method employed in this paper is of a steepest ascent type and may be seen as belonging to the class of stochastic optimization methods, as it involves estimation of the gradient search direction using ensembles of perturbed control strategies. The method is easy to implement and, moreover, it offers a great flexibility, as it is adjoint-free and is not restricted to the use of a specific reservoir simulator. The core of the method, named EnOpt, was recently proposed as an optimizer for the closed-loop reservoir production optimization, that is, the joint data assimilation and hydrocarbon production exercise. In this paper, the usefulness and performance of the optimization scheme are tested on a synthetic model of a homogeneous oil rim reservoir equipped with a horizontal producer and a horizontal injector placed on the opposite sides of the field. The reservoir geology is assumed known. The objective to optimize is a net present value (NPV) as a function, over a fixed production time-horizon, of the injected and produced fluid flow-rates weighted by corresponding economical factors and discount rates. Two different types of the control variables and corresponding constraints on their allowable values are considered. In both cases, the injection bottom-hole pressure is kept constant, and the freedom in controlling the fluid flow consisted in controlling the producer's bottomhole pressure and the total liquid rate, respectively, at pre-specified time-instances. Simulation results confirm the potential of the optimization scheme.

The optimization of trajectories and actuator torques for a dual arm manipulation system is considered. Given the starting and nal con gurations, we nd the trajectories that minimize (a) the integral of the norm of the vector of derivatives of the actuator forces; and (b) the integral of the norm of the actuator forces. In this way both kinematic and actuator redundancy are resolved. The optimization problem reduces to solving a two-point boundary value problem for coupled, nonlinear di erential equations. The e ect of di erent parameters such as preload and inertia are investigated and the results are compared with those obtained using other well-known cost functions.

We develop a new framework, based on the Least Constraint, for programming robots to perform a task using a fault tolerant trajectory. We take a specification of the task, expressed as a set of constraints on the robot&#39;s configuration over time, and produce a fault tolerant trajectory. The methodology encourages fault tolerant behavior at two levels: first at the task-design phase by encouraging the designer to omit extraneous constraints which reduce the potential for fault tolerant operation, and secondly, at the trajectory generation phase by avoiding critical configurations. The critical configurations are identified via a measure of fault tolerance which is global in nature. The dual optimization of fault tolerance at both the high-level design phase as well as the low-level recovery-motion generation phase allows more of the inherent fault tolerance of the robot to be exploited. We believe that combining these two processes into a single formalism is unique and beneficial....

This essay investigates how Leslie Marmon Silko, in her first novel Ceremony, envisions the politics of Native American cultural identity and sovereignty within the mainstream frame of Cold War national imperative. Attempting to reclaim Native American political and cultural sovereignty in the paranoid environments of the global Cold War, Silko takes up the rhetoric of “hybrid patriotism” and “homeland security” in order to blunt the Cold War ideologies of rational individualism, national security, and ethnic assimilation that endanger Native American self-determination and communal values. Laguna Indian protagonist Tayo’s journey of spiritual healing is presented to the mainstream as a process of transformation from “un(wanted)-American” to a “Native American.” To present her agenda of indigenous cultural sovereignty in a manner more acceptable to white American readers, Silko mobilizes some modernist literary conventions such as bildungsroman and grail romance. Ceremony’s ingenious integration of a story of Indian tribal identity formation into the familiar narrative conventions of US Cold War national self-fashioning and liberal individualism allows Silko to explore the possibility that Native American homeland can coexist and even to some extant, share communal responsibility with the white America.

Cette these propose une analyse geographique de l&#39;agriculture et de l&#39;alimentation au Senegal. Elle interroge les politiques economiques et agricoles et elle met en evidence leurs impacts dans le processus de transformation de l&#39;agriculture et de la consommation alimentaire. Par le biais des bilans agricoles et des bilans de couverture cerealiere, elle demontre la fragilite de la securite alimentaire et explique le caractere chronique de certains deficits cerealiers. Face aux besoins alimentaires, les systemes agricoles s&#39;averent inadaptes et les strategies paysannes limitees pour faire face a la crise cerealiere et alimentaire. En combinant les espaces naturels et les territoires de developpement crees depuis l&#39;accession du pays a l&#39;independance, cette these permet d&#39;envisager l&#39;agriculture senegalaise, jusque-la fondee sur le modele de agro-exportation, dans une perspective veritablement endogene pour assurer une securite alimentaire durable. Elle i...

Case Taking is an art of collecting all the facts about the patient using various tools like observation, perception, history taken as given by the patient or told by the attendant, clinical examination etc. in order to find a remedy for the patient[1]. The selection of a homoeopathic medicine depends solely on the tact of asking the exact questions while taking the case. Failure to do so results in the selection of a partially similar medicine and hence results are not as desired. This can be prevented by developing a habit of completing a symptom as was told by Dr. Boenninghausen, i.e., asking about the time modalities of the chief complaints, the aggravating and ameliorating factors, defining the location of the complain, sensations, concomitants etc [2]. In order to be able to select the correct remedy in any case, one must master the art of case taking first. The next step is conversion of symptoms into rubrics and the rest is taken care of by the different computer software repertories available for physicians' use. Study of repertory helps in understanding the symptoms and how the symptoms are modified in the form of rubrics. Here all the rubrics of cough, as given in synthesis repertory, have been tabulated in a simplified form which will aid in asking more refined questions, help in completing the symptoms and ultimately lead to a better selection of remedy.

An energy criterion for choosing the best type of manipulator for a specified task is developed. First, the energy required to perform the robotic task is calculated. Then the lower bound of the mechanical energy consumed by the various kinds of manipulators during their motion, while performing a task, is calculated. Thus, the efficiency of a manipulator for the task is determined. Some examples show that the proper selection of the manipulator configuration can reduce the required energy to a quarter of that of a less suitable one. Once the most suitable manipulator is chosen, the criterion for its most energy efficient motion is developed. The model takes into account the kinematic configuration of the robot, gravitational and other external and internal forces acting on the robot during its operation, and the electric motor driving the robot links. Energy optimization of different paths of motion in joint coordinates is discussed briefly.