scholarly journals Selection of Posture for Time-Trial Cycling Events

2020 ◽  
Vol 10 (18) ◽  
pp. 6546
Author(s):  
Alejandra P. Polanco ◽  
Luis E. Muñoz ◽  
Alberto Doria ◽  
Daniel R. Suarez
Keyword(s):  
Time Trial ◽  
Power Delivery ◽  
Trade Off ◽  
Race Condition ◽  
Road Grade ◽  
Resistive Forces ◽  
Optimization Methodology ◽  
Posture Selection ◽  
Drag Area ◽  
Selection Of

Cyclists usually define their posture according to performance and comfort requirements. However, when modifying their posture, cyclists experience a trade-off between these requirements. In this research, an optimization methodology is developed to select the posture of cyclists giving the best compromise between performance and comfort. Performance was defined as the race time estimated from the power delivery capacity and resistive forces. Comfort was characterized using pressure and vibration indices. The optimization methodology was implemented to select the aerobars’ height for five cyclists riding on 20-km time-trial races with different wind speed and road grade conditions. The results showed that the reduction of the aerobars’ height improved the drag area (−10.7% ± 3.1%) and deteriorated the power delivery capacity (−9.5% ± 5.4%), pressure on the saddle (+16.5% ± 11.5%), and vibrations on the saddle (+6.5% ± 4.0%) for all the tested cyclists. It was observed that the vibrations on the saddle imposed the greatest constraint for the cyclists, limiting the feasible exposure time and, in some cases, modifying the result obtained if the posture was selected considering only performance. It was concluded that optimal posture selection should be performed specifically for each cyclist and race condition due to the dependence of the results on these factors.

Influence of the Cyclist’s Characteristics on the Optimal Pacing Strategy for an Ascending Road

2021 ◽  
Author(s):  
Manuel Angulo ◽  
Alejandra Polanco ◽  
Luis Muñoz
Keyword(s):  
Aerobic Capacity ◽  
Anaerobic Power ◽  
Anaerobic Capacity ◽  
Power Delivery ◽  
Race Time ◽  
Pacing Strategy ◽  
Pacing Strategies ◽  
Road Grade ◽  
Aerobic And Anaerobic ◽  
Drag Area

Abstract Pacing strategies are used in cycling to optimize the power delivered by the cyclist during a race. Gains in race time have been obtained when using these strategies compared to self-paced approaches. For this reason, this study is focused on revising the effect that the variation of the cyclist’s parameters has on the pacing strategy and its results. A numeric method was used to propose pacing strategies for a cyclist riding on an ascending 3.7 km route with a constant 6.26% road grade. The method was validated and then implemented to study the effect of aerobic and anaerobic power delivery capacity, mass, and drag area on the pacing strategies and their corresponding estimated race times. The results showed that modifying 1% of the aerobic capacity or cyclist mass value led to a change of 1% on the race time. Modifying 1% the anaerobic capacity and the drag area led to changes of 0.03% and 0.02% on the race time, respectively. These results are strongly dependent on the route characteristics. It was concluded that for the studied route (constantly ascending), the variation of the cyclist’s aerobic capacity influences the pacing strategy (i.e., the power delivery over the distance). The anaerobic capacity and mass of the cyclist also influence the pacing strategy to a lesser extent.

Optimization of turn-milling process in roughing and finishing regimes: Trade-off between productivity, cutting force and surface integrity

2021 ◽  
pp. 095440892199851
Author(s):  
Ebrahim Hosseini ◽  
Shafiqur Rehman ◽  
Ashkan Alimoradi
Keyword(s):  
Cutting Force ◽  
Desirability Function ◽  
Milling Process ◽  
Machining Process ◽  
Hybrid Machining ◽  
Trade Off ◽  
Hybrid Machining Process ◽  
Process Factors ◽  
Turn Milling ◽  
Selection Of

Turn-milling is a hybrid machining process which used benefits of interrupted cutting for proceeding of round bars. However, number of controllable parameters in the hybrid process is numerous that makes optimizing the process complicated. In the present study, an optimization work has been proposed to investigate the trade-off between production rate and cutting force in roughing regime as well surface roughness and tensile residual stress in finishing regime. Number of 43 experiments based on response surface methodology was designed and carried out to gather required data for development of quadratic empirical models. Then, the adequacy and importance of process factors were analyzed using analysis of variances. Finally, desirability function was used to optimize the process in rough and finish machining regimes. The obtained results showed that selection of eccentricity and cutter speed at their maximum working range can effectively enhance the quality characteristics in both the roughing and finishing regimes.

scholarly journals Evolutionary Multitasking-Based Multiobjective Optimization Algorithm for Channel Selection in Hybrid Brain Computer Interfacing Systems

2021 ◽  
Vol 15 ◽  
Author(s):  
Tianyu Liu ◽  
Zhixiong Xu ◽  
Lei Cao ◽  
Guowei Tan
Keyword(s):  
Multiobjective Optimization ◽  
Real Life ◽  
Channel Selection ◽  
Research Field ◽  
Neural Engineering ◽  
Computer Interfaces ◽  
Classification Tasks ◽  
Optimization Methodology ◽  
Brain Computer Interfacing ◽  
Selection Of

Hybrid-modality brain-computer Interfaces (BCIs), which combine motor imagery (MI) bio-signals and steady-state visual evoked potentials (SSVEPs), has attracted wide attention in the research field of neural engineering. The number of channels should be as small as possible for real-life applications. However, most of recent works about channel selection only focus on either the performance of classification task or the effectiveness of device control. Few works conduct channel selection for MI and SSVEP classification tasks simultaneously. In this paper, a multitasking-based multiobjective evolutionary algorithm (EMMOA) was proposed to select appropriate channels for these two classification tasks at the same time. Moreover, a two-stage framework was introduced to balance the number of selected channels and the classification accuracy in the proposed algorithm. The experimental results verified the feasibility of multiobjective optimization methodology for channel selection of hybrid BCI tasks.

FLEXIBILITY VS. SPECIALISATION IN RO-RO SHIPPING IN THE SOUTH BALTIC SEA

Transport ◽  
2012 ◽  
Vol 27 (3) ◽  
pp. 250-262 ◽  
Author(s):  
Johan Woxenius
Keyword(s):  
Baltic Sea ◽  
Transport System ◽  
Open Systems ◽  
The South ◽  
Trade Off ◽  
Short Sea Shipping ◽  
Trade Offs ◽  
Empirical Context ◽  
Selection Of

The trade-off between flexibility and specialisation implies delicate tasks for transport system designers and marketing managers. The outcome of their efforts ranges from highly specialised solutions for a restricted number of users and types of cargoes to very open systems for common use adapted to accommodate a wide variety of transport demands. The purpose of this article is to adapt theories on openness and trade-offs, characterise a selection of flexible and specialised European short sea shipping concepts and analyse how substantial changes in the future character of the competition with road and rail can affect the development of ro-ro shipping in the South Baltic Sea. A matrix with commercial openness and technological openness on the axes is used for categorising sub-segments in the empirical context of the South Baltic Sea. Foreseeable changes in key cost and competition parameters until 2020 are taken into account in discussing potential scenarios. A plausible outcome for the ferry/ro-ro shipping segment is that a branch with slow services for unaccompanied freight will be diverted from the current homogenous market offerings. During the study, the Swedish Orient Line launched a service with these characteristics, which is analysed in a case study.

Automated Component-Selection of Design Synthesis for Physical Architecture with Model-Based Systems Engineering using Evolutionary Trade-off

2018 ◽  
Vol 28 (1) ◽  
pp. 1296-1310 ◽  
Author(s):  
Habibi Husain Arifin ◽  
Nasis Chimplee ◽  
Ho Kit Robert Ong ◽  
Jirapun Daengdej ◽  
Thotsapon Sortrakul
Keyword(s):  
Systems Engineering ◽  
Design Synthesis ◽  
Trade Off ◽  
Model Based ◽  
Component Selection ◽  
Model Based Systems Engineering ◽  
Selection Of

Patient Preference for the Management of Trigger Digit

1993 ◽  
Vol 1 (3) ◽  
pp. 141-142
Author(s):  
Karen Joughin ◽  
Steven J McCabe
Keyword(s):  
Patient Preference ◽  
Steroid Injection ◽  
Treatment Options ◽  
Bimodal Distribution ◽  
Previous Experience ◽  
Cure Rate ◽  
Trade Off ◽  
Probability Of Success ◽  
Selection Of ◽  
Do So

K Joughin, SJ McCabe. Patient preference for the management of trigger digit. Can J Plast Surg 1993;1(3):141-142. Steroid injection and surgery are both accepted treatment options for trigger digit. The objective of this study was to determine which modality patients would prefer when given a choice of treatments, the strength of their preference and factors that may influence their preference. A probability trade-off technique was used in 151 subjects. On average, subjects selected injection over surgery and would do so with a probability of success by injection as low as 57%. If the probability of cure by injection was less than 57%, surgery would be the preferred method of treatment, on average. A bimodal distribution of patient preference showed that some patients may strongly prefer either surgery or injection, with many patients preferring surgery even with a high expected cure rate of the first injection. Age, gender and previous experience with injections or surgery did not correlate with preference. Patients with trigger digits should be presented with unbiased information about treatment and be allowed to take part in the selection of the type of treatment they receive.

Frontal Surface Area Versus Drag Area in Predicting Level Cycling Time Trial Performance

2005 ◽  
Vol 37 (Supplement) ◽  
pp. S86
Author(s):  
Ryan N. Ignatz ◽  
Allen C. Lim ◽  
Andy G. Edwards ◽  
Ben E. Birken ◽  
Ali Samek ◽  
...  
Keyword(s):  
Surface Area ◽  
Time Trial ◽  
Frontal Surface ◽  
Time Trial Performance ◽  
Cycling Time Trial ◽  
Drag Area ◽  
Cycling Time ◽  
Trial Performance

CHECKING ORTHOGONAL TRANSFORMATIONS AND GENETIC ALGORITHMS FOR SELECTION OF FUZZY RULES BASED ON INTERPRETABILITY-ACCURACY CONCEPTS

2012 ◽  
Vol 20 (supp02) ◽  
pp. 159-186 ◽  
Author(s):  
M. ISABEL REY ◽  
MARTA GALENDE ◽  
M. J. FUENTE ◽  
GREGORIO I. SAINZ-PALMERO
Keyword(s):  
Fuzzy System ◽  
Poor Performance ◽  
Fuzzy Modeling ◽  
Nsga Ii ◽  
Trade Off ◽  
Rule Selection ◽  
Fuzzy Models ◽  
Neuro Fuzzy ◽  
Firing Strength ◽  
Selection Of

Fuzzy modeling is one of the most known and used techniques in different areas to model the behavior of systems and processes. In most cases, as in data-driven fuzzy modeling, these fuzzy models reach a high performance from the point of view of accuracy, but from other points of view, such as complexity or interpretability, they can present a poor performance. Several approaches are found in the bibliography to reduce the complexity and improve the interpretability of the fuzzy models. In this paper, a post-processing approach is carried out via rule selection, whose aim is to choose the most relevant rules for working together on the well-known accuracy-interpretability trade-off. The rule relevancy is based on Orthogonal Transformations, such as the SVD-QR rank revealing approach, the P-QR and OLS transformations. Rule selection is carried out using a genetic algorithm that takes into account the information obtained by the Orthogonal Transformations. The main objective is to check the true significance, drawbacks and advantages of the rule selection based on the orthogonal transformations via the rule firing strength matrix. In order to carry out this aim, a neuro-fuzzy system, FasArt (Fuzzy Adaptive System ART based), and several case studies, data sets from the KEEL Project Repository, are used to tune and check this selection of rules based on orthogonal transformations, genetic selection and accuracy-interpretability trade-off. This neuro-fuzzy system generates Mamdani fuzzy rule based systems (FRBSs), in an approximative way. NSGA-II is the MOEA tool used to tune the proposed rule selection.

scholarly journals Automatic Discovery of Privacy–Utility Pareto Fronts

2020 ◽  
Vol 2020 (4) ◽  
pp. 5-23
Author(s):  
Brendan Avent ◽  
Javier González ◽  
Tom Diethe ◽  
Andrei Paleyes ◽  
Borja Balle
Keyword(s):  
Differential Privacy ◽  
Decision Makers ◽  
Bayesian Optimization ◽  
Mathematical Framework ◽  
Trade Off ◽  
Learning Tasks ◽  
Automatic Discovery ◽  
Optimization Methodology ◽  
Pareto Fronts ◽  
Analytical Utility

AbstractDifferential privacy is a mathematical framework for privacy-preserving data analysis. Changing the hyperparameters of a differentially private algorithm allows one to trade off privacy and utility in a principled way. Quantifying this trade-off in advance is essential to decision-makers tasked with deciding how much privacy can be provided in a particular application while maintaining acceptable utility. Analytical utility guarantees offer a rigorous tool to reason about this tradeoff, but are generally only available for relatively simple problems. For more complex tasks, such as training neural networks under differential privacy, the utility achieved by a given algorithm can only be measured empirically. This paper presents a Bayesian optimization methodology for efficiently characterizing the privacy– utility trade-off of any differentially private algorithm using only empirical measurements of its utility. The versatility of our method is illustrated on a number of machine learning tasks involving multiple models, optimizers, and datasets.

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