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Institution

Ford Motor Company

CompanyDearborn, Michigan, United States
About: Ford Motor Company is a company organization based out in Dearborn, Michigan, United States. It is known for research contribution in the topics: Internal combustion engine & Clutch. The organization has 36123 authors who have published 51450 publications receiving 855200 citations. The organization is also known as: Ford Motor & Ford Motor Corporation.


Papers
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Journal ArticleDOI
TL;DR: Comorbidity has a major impact on survival in early‐ and late‐stage disease, and even infrequent deleterious comorbidities are important collectively.
Abstract: Lung cancer is associated with smoking and age, both of which are associated with comorbidity. We evaluated the impact of comorbidity on lung cancer survival. Data on 56 comorbidities were abstracted from the records of a cohort of 1,155 patients. Survival effects were evaluated with Cox regression (outcome crude death). The adjusted R(2) statistic was used to compare the survival variation explained by predictive variables. No comorbidity was observed in 11.7% of patients, while 54.3% had 3 or more (mean 2.97) comorbidities. In multivariate analysis, 19 comorbidities were associated with survival: HIV/AIDS, tuberculosis, previous metastatic cancer, thyroid/glandular diseases, electrolyte imbalance, anemia, other blood diseases, dementia, neurologic disease, congestive heart failure, COPD, asthma, pulmonary fibrosis, liver disease, gastrointestinal bleeding, renal disease, connective tissue disease, osteoporosis and peripheral vascular disease. Only the latter was protective. Some of the hazards of comorbidities were explained by more directly acting comorbidities and/or receipt of treatment. Stage explained 25.4% of the survival variation. In addition to stage, the 19 comorbidities explained 6.1%, treatments 9.2%, age 3.7% and histology 1.3%. Thirteen uncommon comorbidities (prevalence <6%) affected 21.2% of patients and explained 3.5% of the survival variation. Comorbidity count and the Charlson index were significant predictors but explained only 2.5% and 2.0% of the survival variation, respectively. Comorbidity has a major impact on survival in early- and late-stage disease, and even infrequent deleterious comorbidities are important collectively. Comorbidity count and the Charlson index failed to capture much information. Clinical practice and trials need to consider the effect of comorbidity in lung cancer patients.

265 citations

Journal ArticleDOI
TL;DR: In this paper, a Model Predictive Control (MPC) approach for controlling an active front steering (AFS) system in an autonomous vehicle is presented, where at each time step a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to best follow the desired trajectory on slippery roads at the highest possible entry speed.
Abstract: A Model Predictive Control (MPC) approach for controlling an Active Front Steering (AFS) system in an autonomous vehicle is presented. At each time step a trajectory is assumed to be known over a finite horizon, and an MPC controller computes the front steering angle in order to best follow the desired trajectory on slippery roads at the highest possible entry speed. We start from the results presented in [2], [6] and formulate the MPC problem based on successive on-line linearization of the nonlinear vehicle model (LTV MPC). We present a sufficient stability conditions for such LTV MPC scheme. The condition is derived for a general class of nonlinear discrete time systems and results into an additional convex constraint to be included in the LTV MPC design. For the AFS control problem, we compare the proposed LTV MPC scheme against the LTV MPC scheme in [6] where stability has been enforced with an ad-hoc constraint. Simulation and experimental tests up to 21 m/s on icy roads show the effectiveness of the LTV MPC formulation.

264 citations

Journal ArticleDOI
TL;DR: The probability for direct energy transfer from a dye molecule to the surface plasmons (SP) on a nearby metal is calculated using the classical Sommerfeld model and the coupling is demonstrated in experiments with an Ag film between a rhodamine–methanol solution and a high-index prism.
Abstract: The probability for direct energy transfer from a dye molecule to the surface plasmons (SP) on a nearby metal is calculated using the classical Sommerfeld model. For 600-nm emission from a dipole-oriented ⊥ to an Ag surface, the peak SP coupling probability is 93% at a distance of 120 nm from the metal. The coupling is demonstrated in experiments with an Ag film between a rhodamine–methanol solution and a high-index prism. The SP-coupled radiation produces an intense cone of radiation in the prism, each frequency component of which satisfies the SP dispersion relation.

264 citations

Journal ArticleDOI
Davor Hrovat1
TL;DR: The paper surveys applications of optimal control techniques to the design of active suspensions, starting from simple quarter-car, 1D models, which are followed by their half-Car, 2D, and full- car, 3D, counterparts.
Abstract: The paper surveys applications of optimal control techniques to the design of active suspensions, starting from simple quarter-car, 1D models, which are followed by their half-car, 2D, and full-car, 3D, counterparts. The emphasis is on Linear-Quadratic (LQ) optimal control and automotive vehicles

263 citations

Journal ArticleDOI
TL;DR: In this article, an integrated framework for optimization under uncertainty that can bring both the design objective robustness and the probabilistic design constraints into account is proposed, which can obtain more reasonable compound noise combinations for a robust design objective compared to using the traditional approach proposed by Taguchi.
Abstract: In this work, we propose an integrated framework for optimization under uncertainty that can bring both the design objective robustness and the probabilistic design constraints into account. The fundamental development of this work is the employment of an inverse reliability strategy that uses percentile performance for assessing both the objective robustness and probabilistic constraints. The percentile formulation for objective robustness provides us an accurate evaluation of the variation of an objective performance and a probabilistic measurement of the robustness. We can obtain more reasonable compound noise combinations for a robust design objective compared to using the traditional approach proposed by Taguchi. The proposed formulation is very efficient to solve since it only needs to evaluate the constraint functions at the required reliability levels. The other major development of this work is a new search algorithm for the Most Probable Point of Inverse Reliability (MPPIR) that can be used to efficiently evaluate percentile performances for both robustness and reliability assessments. Multiple strategies are employed in the MPPIR search, including using the steepest ascent direction and an arc search. The algorithm is applicable to general non-concave and non-convex performance functions of random variables following any continuous distributions. The effectiveness of the MPPIR search algorithm is verified using example problems. Overall, an engineering example on integrated robust and reliability design of a vehicle combustion engine piston is used to illustrate the benefits of our proposed method.

261 citations


Authors

Showing all 36140 results

NameH-indexPapersCitations
Anil K. Jain1831016192151
Markus Antonietti1761068127235
Christopher M. Dobson1501008105475
Jack Hirsh14673486332
Galen D. Stucky144958101796
Federico Capasso134118976957
Peter Stone130122979713
Gerald R. Crabtree12837160973
Douglas A. Lauffenburger12270555326
Abass Alavi113129856672
Mark E. Davis11356855334
Keith Beven11051461705
Naomi Breslau10725442029
Fei Wang107182453587
Jun Yang107209055257
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202237
2021766
20201,397
20192,195
20181,945
20171,995