Selection of Body Segment Parameters by Optimization Methods

1982 ◽  
Vol 104 (1) ◽  
pp. 38-44 ◽  
Author(s):  
C. L. Vaughan ◽  
J. G. Andrews ◽  
J. G. Hay
Keyword(s):  
Optimization Theory ◽  
Bilateral Symmetry ◽  
Optimization Methods ◽  
Body Segment ◽  
Kinematic Data ◽  
Design Variables ◽  
The Difference ◽  
Body Segment Parameters ◽  
Gamma Scanning ◽  
Selection Of

The selection of body segment parameters (BSPs) is a difficult yet essential task in many biomechanical studies. The methods used to date—cadaver, reaction board, mathematical modeling, gamma scanning, and kinematics—all have a number of drawbacks. The purpose of the present paper is to present an alternative method, based on kinematic data and optimization theory, for selecting BSPs. The design variables are the BSPs and the objective function to be minimized is based on the difference between calculated and measured distal extremity kinetics, while the equality constraints are based on Newtonian principles as well as bilateral symmetry of the BSPs. Three different activities are used to generate “optimal” sets of BSPs and these values are different, but not markedly so, from cadaver values. Further detailed investigation appears warranted.

scholarly journals Identification of a Non-Linear Landing Gear Model Using Nature-Inspired Optimization

2008 ◽  
Vol 15 (3-4) ◽  
pp. 257-272 ◽  
Author(s):  
Felipe A.C. Viana ◽  
Valder Steffen Jr. ◽  
Marcelo A.X. Zanini ◽  
Sandro A. Magalhães ◽  
Luiz C.S. Góes
Keyword(s):  
Inverse Problem ◽  
Shock Absorber ◽  
Model Updating ◽  
Optimization Technique ◽  
Optimization Methods ◽  
Initial Guess ◽  
Landing Gear ◽  
Design Variables ◽  
Non Linear ◽  
The Difference

This work deals with the application of a nature-inspired optimization technique to solve an inverse problem represented by the identification of an aircraft landing gear model. The model is described in terms of the landing gear geometry, internal volumes and areas, shock absorber travel, tire type, and gas and oil characteristics of the shock absorber. The solution to this inverse problem can be obtained by using classical gradient-based optimization methods. However, this is a difficult task due to the existence of local minima in the design space and the requirement of an initial guess. These aspects have motivated the authors to explore a nature-inspired approach using a method known as LifeCycle Model. In the present formulation two nature-based methods, namely the Genetic Algorithms and the Particle Swarm Optimization were used. An optimization problem is formulated in which the objective function represents the difference between the measured characteristics of the system and its model counterpart. The polytropic coefficient of the gas and the damping parameter of the shock absorber are assumed as being unknown: they are considered as design variables. As an illustration, experimental drop test data, obtained under zero horizontal speed, were used in the non-linear landing gear model updating of a small aircraft.

Designing Turbomachinery Blades Using Evolutionary Methods

1999 ◽  
Author(s):  
K. C. Giannakoglou
Keyword(s):  
Flow Conditions ◽  
Flow Solver ◽  
Design Variables ◽  
Circular Arcs ◽  
Combined Use ◽  
Evaluation Phase ◽  
Turbomachinery Blades ◽  
The Difference ◽  
Design Cost ◽  
Selection Of

A method based on computational intelligence is presented for the inverse design of 2D turbomachinery blades producing desirable wall pressure or velocity distributions under certain flow conditions. Blade airfoil shapes are parameterized through the combined use of circular arcs and Bezier functions. The design variables are controlled by Genetic Algorithms, employed in order to minimize the difference between target and numerically predicted distributions for each candidate shape. All numerical evaluations are carried through a primitive variable flow solver for unstructured grids. By employing Artificial Neural Networks, trained to correlate shapes and fitness scores, a great number of costly shape evaluations is overcome. The proposed combination of GAs for the optimization and ANNs for part of the evaluation phase is attractive and dramatically reduces the design cost. This paper discusses issues such as the regular re-training of the ANN or the selection of the threshold for numerical flow evaluations.

Optimum variable input speed for kinematic performance of Geneva mechanisms using teaching-learning-based optimization algorithm

2015 ◽  
Vol 231 (10) ◽  
pp. 1871-1883 ◽  
Author(s):  
WY Lin ◽  
YH Tsai ◽  
KM Hsiao
Keyword(s):  
Optimum Design ◽  
Angular Position ◽  
Angular Acceleration ◽  
Optimization Methods ◽  
Polynomial Coefficients ◽  
Design Variables ◽  
Teaching Learning Based Optimization ◽  
Kinematic Performance ◽  
The Difference ◽  
Teaching Learning

An optimum design of variable input speed for the Geneva mechanism is aimed at improving the kinematic performance of the traditional Geneva mechanism by eliminating infinite angular jerks and reducing the peak angular acceleration of the Geneva wheel during the indexing motion. The normalized angular velocity and acceleration of the Geneva wheel corresponding to the normalized time are introduced. A polynomial function of the normalized time is used to describe the normalized angular position of the crank, and therefore, the corresponding polynomial coefficients are considered as the design variables. The optimum design task is very specialized and difficult to solve with some evolutionary and swarm optimization methods because of the extremely large range for the value of the design variable, arising from the utilization of a higher order polynomial for the normalized time parameter with a value between 0 and 1. A new evolutionary algorithm termed teaching-learning-based optimization comprises a teacher phase and a learner phase. In the teacher phase, the entire population can be gradually shifted to a more promising region, which may be very far from the relatively small initial region. The obtained optimal results are compared with those obtained using the length-adjustable deriving link method discussed in the literature. The findings show that the difference in the effectiveness of the variable input speed method and the length-adjustable driving link method for the reduction of the peak angular acceleration of the Geneva wheel is small.

COMBINATORIAL POLYNOMIALLY COMPUTABLE CHARACTERISTICS OF SUBSTITUTIONS AND THEIR PROPERTIES

2020 ◽  
Vol 7 (2) ◽  
pp. 34-41
Author(s):  
VLADIMIR NIKONOV ◽  
◽  
ANTON ZOBOV ◽  
Keyword(s):  
Mathematical Expectation ◽  
Point Of View ◽  
Small Range ◽  
Computational Point ◽  
Wide Range ◽  
Bijective Function ◽  
The Difference ◽  
Element Base ◽  
Selection Of

The construction and selection of a suitable bijective function, that is, substitution, is now becoming an important applied task, particularly for building block encryption systems. Many articles have suggested using different approaches to determining the quality of substitution, but most of them are highly computationally complex. The solution of this problem will significantly expand the range of methods for constructing and analyzing scheme in information protection systems. The purpose of research is to find easily measurable characteristics of substitutions, allowing to evaluate their quality, and also measures of the proximity of a particular substitutions to a random one, or its distance from it. For this purpose, several characteristics were proposed in this work: difference and polynomial, and their mathematical expectation was found, as well as variance for the difference characteristic. This allows us to make a conclusion about its quality by comparing the result of calculating the characteristic for a particular substitution with the calculated mathematical expectation. From a computational point of view, the thesises of the article are of exceptional interest due to the simplicity of the algorithm for quantifying the quality of bijective function substitutions. By its nature, the operation of calculating the difference characteristic carries out a simple summation of integer terms in a fixed and small range. Such an operation, both in the modern and in the prospective element base, is embedded in the logic of a wide range of functional elements, especially when implementing computational actions in the optical range, or on other carriers related to the field of nanotechnology.

Color Trend Analysis using Machine Learning with Fashion Collection Images

2021 ◽  
pp. 0887302X2199594
Author(s):  
Ahyoung Han ◽  
Jihoon Kim ◽  
Jaehong Ahn
Keyword(s):  
Machine Learning ◽  
Trend Analysis ◽  
Image Data ◽  
Fashion Industry ◽  
Color Palette ◽  
Web Scraping ◽  
Design Variables ◽  
Sales Organizations ◽  
Fashion Designers ◽  
Selection Of

Fashion color trends are an essential marketing element that directly affect brand sales. Organizations such as Pantone have global authority over professional color standards by annually forecasting color palettes. However, the question remains whether fashion designers apply these colors in fashion shows that guide seasonal fashion trends. This study analyzed image data from fashion collections through machine learning to obtain measurable results by web-scraping catwalk images, separating body and clothing elements via machine learning, defining a selection of color chips using k-means algorithms, and analyzing the similarity between the Pantone color palette (16 colors) and the analysis color chips. The gap between the Pantone trends and the colors used in fashion collections were quantitatively analyzed and found to be significant. This study indicates the potential of machine learning within the fashion industry to guide production and suggests further research expand on other design variables.

scholarly journals Age-dependency in mortality of Finnish family caregivers: a nationwide register-based study

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
T M Mikkola ◽  
H Kautiainen ◽  
M Mänty ◽  
M B von Bonsdorff ◽  
T Kröger ◽  
...  
Keyword(s):  
General Population ◽  
Family Caregivers ◽  
Family Caregiver ◽  
Causes Of Death ◽  
Lower Mortality ◽  
All Cause Mortality ◽  
The Difference ◽  
Caregiver Role ◽  
Selection Of

Abstract Purpose Mortality appears to be lower in family caregivers than in the general population. However, there is lack of knowledge whether the difference in mortality between family caregivers and the general population is dependent on age. The purpose of this study was to analyze all-cause mortality in relation to age in family caregivers and to study their cause-specific mortality using data from multiple Finnish national registers. Methods The data included all individuals, who received family caregiver's allowance in Finland in 2012 (n = 42 256, mean age 67 years, 71% women) and a control population matched for age, sex, and municipality of residence (n = 83 618). Information on dates and causes of death between 2012 and 2017 were obtained from the Finnish Causes of Death Register. Flexible parametric survival modeling and competing risk regression adjusted for socioeconomic status were used. Results The total follow-up time was 717 877 person-years. Family caregivers had lower all-cause mortality than the controls over the follow-up (8.1% vs. 11.6%) both among women (hazard ratio [HR]: 0.64, 95% CI: 0.61-0.68) and men (HR: 0.73, 95% CI: 0.70-0.77). Younger adult caregivers had equal or only slightly lower mortality than their controls, but after age 60, the difference increased markedly resulting in over 10% lower mortality in favor of the caregivers in the oldest age groups. Caregivers had lower mortality for all the causes of death studied, namely cardiovascular, cancer, neurological, external, respiratory, gastrointestinal and dementia than the controls. Of these, the lowest was the risk for dementia (subhazard ratio=0.29, 95%CI: 0.25-0.34). Conclusions Older family caregivers have lower mortality than the age-matched controls from the general population while younger caregivers have similar mortality to their peers. This age-dependent advantage in mortality is likely to reflect selection of healthier individuals into the family caregiver role. Key messages The difference in mortality between family caregivers and the age-matched general population varies considerably with age. Advantage in mortality observed in family caregiver studies is likely to reflect the selection of healthier individuals into the caregiver role, which underestimates the adverse effects of caregiving.

scholarly journals A microfluidic device enabling drug resistance analysis of leukemia cells via coupled dielectrophoretic detection and impedimetric counting

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yağmur Demircan Yalçın ◽  
Taylan Berkin Töral ◽  
Sertan Sukas ◽  
Ender Yıldırım ◽  
Özge Zorlu ◽  
...  
Keyword(s):  
Drug Resistance ◽  
K562 Cells ◽  
Leukemia Cells ◽  
Drug Resistant ◽  
Wild Type ◽  
Gene Expressions ◽  
Before And After ◽  
The Difference ◽  
Selection Of ◽  
Resistant Cells

AbstractWe report the development of a lab-on-a-chip system, that facilitates coupled dielectrophoretic detection (DEP-D) and impedimetric counting (IM-C), for investigating drug resistance in K562 and CCRF-CEM leukemia cells without (immuno) labeling. Two IM-C units were placed upstream and downstream of the DEP-D unit for enumeration, respectively, before and after the cells were treated in DEP-D unit, where the difference in cell count gave the total number of trapped cells based on their DEP characteristics. Conductivity of the running buffer was matched the conductivity of cytoplasm of wild type K562 and CCRF-CEM cells. Results showed that DEP responses of drug resistant and wild type K562 cells were statistically discriminative (at p = 0.05 level) at 200 mS/m buffer conductivity and at 8.6 MHz working frequency of DEP-D unit. For CCRF-CEM cells, conductivity and frequency values were 160 mS/m and 6.2 MHz, respectively. Our approach enabled discrimination of resistant cells in a group by setting up a threshold provided by the conductivity of running buffer. Subsequent selection of drug resistant cells can be applied to investigate variations in gene expressions and occurrence of mutations related to drug resistance.

scholarly journals Weightage Effect during Back-Calculation of Rock-Mass Quality from the Installed Tunnel Support in Rock-Mass Rating and Tunneling Quality Index System

2019 ◽  
Vol 9 (10) ◽  
pp. 2065 ◽  
Author(s):  
Jonguk Kim ◽  
Hafeezur Rehman ◽  
Wahid Ali ◽  
Abdul Muntaqim Naji ◽  
Hankyu Yoo
Keyword(s):  
Rock Mass ◽  
Quality Index ◽  
Rock Bolt ◽  
Rock Mass Rating ◽  
Rock Mass Quality ◽  
Back Calculation ◽  
The Difference ◽  
Bolt Spacing ◽  
Q System ◽  
Selection Of

In extensively used empirical rock-mass classification systems, the rock-mass rating (RMR) and tunneling quality index (Q) system, rock-mass quality, and tunnel span are used for the selection of rock bolt length and spacing and shotcrete thickness. In both systems, the rock bolt spacing and shotcrete thickness selection are based on the same principle, which is used for the back-calculation of the rock-mass quality. For back-calculation, there is no criterion for the selection of rock-bolt-spacing-based rock-mass quality weightage and shotcrete thickness along with tunnel-span-based rock-mass quality weightage. To determine this weightage effect during the back-calculation, five weightage cases are selected, explained through example, and applied using published data. In the RMR system, the weightage effect is expressed in terms of the difference between the calculated and back-calculated rock-mass quality in the two versions of RMR. In the Q system, the weightage effect is presented in plots of stress reduction factor versus relative block size. The results show that the weightage effect during back-calculation not only depends on the difference in rock-bolt-spacing-based rock-mass quality and shotcrete along with tunnel-span-based rock-mass quality, but also on their corresponding values.

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