A Methodology for Variability Reduction in Manufacturing Cost Estimating in the Automotive Industry based on Design Features

Organised by: Cranfield UniversitySmall to medium manufacturing companies are coming to realise the increasing importance of performing fast and accurate cost estimates at the early stages of projects to address customers’ requests for quotation. However, they cannot afford the implementation of a knowledge-based cost estimating software. This paper explains the development and validation of a consistent methodology for the cost estimating of manufactured parts (focused on pistons) based on the design features. The research enabled the identification of the sources of variability in cost estimates, and the main one is the lack of formal procedures for the cost estimates in manufacturing SMEs. Finally, a software prototype was developed that reduces the variability in the cost estimates by defining a formal procedure, following the most appropriate cost estimating techniques.Mori Seiki – The Machine Tool Compan

Manifold analysis of the P-wave changes induced by pulmonary vein isolation during cryoballoon procedure

Background/Aim: In atrial fibrillation (AF) ablation procedures, it is desirable to know whether a proper disconnection of the pulmonary veins (PVs) was achieved. We hypothesize that information about their isolation could be provided by analyzing changes in P-wave after ablation. Thus, we present a method to detect PV disconnection using P-wave signal analysis. Methods: Conventional P-wave feature extraction was compared to an automatic feature extraction procedure based on creating low-dimensional latent spaces for cardiac signals with the Uniform Manifold Approximation and Projection (UMAP) method. A database of patients (19 controls and 16 AF individuals who underwent a PV ablation procedure) was collected. Standard 12-lead ECG was recorded, and P-waves were segmented and averaged to extract conventional features (duration, amplitude, and area) and their manifold representations provided by UMAP on a 3-dimensional latent space. A virtual patient was used to validate these results further and study the spatial distribution of the extracted characteristics over the whole torso surface. Results: Both methods showed differences between P-wave before and after ablation. Conventional methods were more prone to noise, P-wave delineation errors, and inter-patient variability. P-wave differences were observed in the standard leads recordings. However, higher differences appeared in the torso region over the precordial leads. Recordings near the left scapula also yielded noticeable differences. Conclusions: P-wave analysis based on UMAP parameters detects PV disconnection after ablation in AF patients and is more robust than heuristic parameterization. Moreover, additional leads different from the standard 12-lead ECG should be used to detect PV isolation and possible future reconnections better

Anomaly Detection from Low-dimensional Latent Manifolds with Home Environmental Sensors

Human Activity Recognition poses a significant challenge within Active and Assisted Living (AAL) systems, relying extensively on ubiquitous environmental sensor-based acquisition devices to detect user situations in their daily living. Environmental measurement systems deployed indoors yield multiparametric data in heterogeneous formats, which presents a challenge for developing Machine Learning-based AAL models. We hypothesized that anomaly detection algorithms could be effectively employed to create data-driven models for monitoring home environments and that the complex multiparametric indoor measurements can often be represented by a relatively small number of latent variables generated through Manifold Learning (MnL) techniques. We examined both linear (Principal Component Analysis) and non-linear (AutoEncoders) techniques for generating these latent spaces and the utility of core domain detection techniques for identifying anomalies within the resulting low-dimensional manifolds. We benchmarked this approach using three publicly available datasets (hh105, Aruba, and Tulum) and one proprietary dataset (Elioth) for home environmental monitoring. Our results demonstrated the following key findings: (a) Nonlinear manifold estimation techniques offer significant advantages in retrieving latent variables when compared to linear techniques; (b) The quality of the reconstruction of the original multidimensional recordings serves as an acceptable indicator of the quality of the generated latent spaces; (c) Domain detection identifies regions of normality consistent with typical individual activities in these spaces; And (d) the system effectively detects deviations from typical activity patterns and labels anomalies. This study lays the groundwork for further exploration of enhanced methods for extracting information from MnL data models and their application within the AAL and possibly other sectors

Generalization and Regularization for Inverse Cardiac Estimators

Electrocardiographic Imaging (ECGI) aims to estimate the intracardiac potentials noninvasively, hence allowing the clinicians to better visualize and understand many arrhythmia mechanisms. Most of the estimators of epicardial potentials use a signal model based on an estimated spatial transfer matrix together with Tikhonov regularization techniques, which works well specially in simulations, but it can give limited accuracy in some real data. Based on the quasielectrostatic potential superposition principle, we propose a simple signal model that supports the implementation of principled out-of-sample algorithms for several of the most widely used regularization criteria in ECGI problems, hence improving the generalization capabilities of several of the current estimation methods. Experiments on simple cases (cylindrical and Gaussian shapes scrutinizing fast and slow changes, respectively) and on real data (examples of torso tank measurements available from Utah University, and an animal torso and epicardium measurements available from Maastricht University, both in the EDGAR public repository) show that the superposition-based out-of-sample tuning of regularization parameters promotes stabilized estimation errors of the unknown source potentials, while slightly increasing the re-estimation error on the measured data, as natural in non-overfitted solutions. The superposition signal model can be used for designing adequate out-of-sample tuning of Tikhonov regularization techniques, and it can be taken into account when using other regularization techniques in current commercial systems and research toolboxes on ECG

On the Statistical and Temporal Dynamics of Sentiment Analysis

Despite the broad interest and use of sentiment analysis nowadays, most of the conclusions in current literature are driven by simple statistical representations of sentiment scores. On that basis, the generated sentiment evaluation consists nowadays of encoding and aggregating emotional information from a number of individuals and their populational trends. We hypothesized that the stochastic processes aimed to be measured by sentiment analysis systems will exhibit nontrivial statistical and temporal properties. We established an experimental setup consisting of analyzing the short text messages (tweets) of 6 user groups with different nature (universities, politics, musicians, communication media, technological companies, and financial companies), including in each group ten high-intensity users in their regular generation of traffic on social networks. Statistical descriptors were checked to converge at about 2000 messages for each user, for which messages from the last two weeks were compiled using a custom-made tool. The messages were subsequently processed for sentiment scoring in terms of different lexicons currently available and widely used. Not only the temporal dynamics of the resulting score time series per user was scrutinized, but also its statistical description as given by the score histogram, the temporal autocorrelation, the entropy, and the mutual information. Our results showed that the actual dynamic range of lexicons is in general moderate, and hence not much resolution is given within their end-of-scales. We found that seasonal patterns were more present in the time evolution of the number of tweets, but to a much lesser extent in the sentiment intensity. Additionally, we found that the presence of retweets added negligible effects over standard statistical modes, while it hindered informational and temporal patterns. The innovative Compounded Aggregated Positivity Index developed in this work proved to be characteristic for industries and at ..

Impacto del alelo APOE2 en el cambio del perfil lipídico después de un programa de pérdida de peso

Background: apolipoprotein E (ApoE) polymorphism is a genetic determinant of lipid and lipoprotein levels and the risk for coronary heart disease. Objective: to evaluate the impact of ApoE2 allele in lipid plasma levels and the influence of a healthy hypocaloric diet plus a controlled physical activity on the lipid profile, we performed a study in a cohort of overweight and obese healthy subjects (Body Mass Index (BMI) between 25 and 34.9 kg·m-2). Methods: one hundred eighty participants (96 women), aged 18-50 years participated in a 22 weeks weight loss intervention based on same dietary treatment and different controlled exercise programs. All subjects followed a hypocaloric diet (25-30% less energy intake than the daily energy expenditure). Blood samples were obtained for lipids measurements at the beginning and end of the study. Results: after intervention, men of the E2 group showed the greatest decreases in low-density lipoprotein (LDL), triglycerides (TG) and total cholesterol (TC) values (p = 0.039; p = 0.001; p = 0.001; respectively). For high-density lipoprotein (HDL), E2 group had significant differences compared with E4 at pre- (p = 0.020) and post-intervention values (p = 0.024). Conclusion: our results show great changes in men carrying ApoE2, mainly in TG and TC concentrations after treatment with hypocaloric diet and controlled exercise. Therefore, adding supervised training to nutritional intervention seems to be a good alternative for the reinforcement of the effect of the treatment.Antecedentes: el polimorfismo de la apolipoproteína E (ApoE) es un determinante genético de los niveles de lípidos y lipoproteínas y el riesgo de enfermedad coronaria. Objetivo: para evaluar el impacto del alelo ApoE2 en los niveles de lípidos plasmáticos y la influencia de una dieta hipocalórica sana más una actividad física controlada en el perfil lipídico, se realizó un estudio en una cohorte de sujetos sanos con sobrepeso y obesidad (índice de masa corporal entre 25-34,9 kg·m-2). Métodos: ciento ochenta participantes (96 mujeres), de 18-50 años participaron en una intervención de pérdida de peso de 22 semanas basada en el mismo tratamiento dietético y diferentes programas de ejercicios controlados. Todos los sujetos siguieron una dieta hipocalórica (consumo de energía entre 25-30% inferior que el gasto energético total diario). Se obtuvieron muestras de sangre para las mediciones de lípidos al inicio y al final del estudio. Resultados: después de la intervención, los hombres del grupo E2 mostraron las mayores disminuciones en los valores de lipoproteína de baja densidad (LDL), triglicéridos (TG) y colesterol total (TC) (p = 0,039; p = 0,001; p = 0,001). Para las lipoproteínas de alta densidad (HDL), el grupo E2 presentó diferencias significativas en comparación con E4 en los valores previos (p = 0,020) y postintervención (p = 0,024). Conclusión: nuestros resultados muestran grandes cambios en los hombres que portan ApoE2, principalmente en las concentraciones de TG y TC después del tratamiento con dieta hipocalórica y ejercicio controlado. Por lo tanto, la adición de entrenamiento supervisado a la intervención nutricional parece ser una buena alternativa para el refuerzo del efecto del tratamiento.FUNDING SOURCE: The PRONAF Study took place with the financial support of the Ministerio de Ciencia e Innovación, Convocatoria de Ayudas I+D 2008, Proyectos de Investigación Fundamental No Orientada, del VI Plan de Investigación Nacional 2008-2011, (Contract: DEP2008-06354-C04-01). We acknowledge and thank all of the subjects who participated in the study. We thank Víctor Díaz Molina, PhD for valuable discussion

Body composition changes after a weight loss intervention: A 3-year follow-up study

Studies comparing different types of exercise-based interventions have not shown a consistent effect of training on long-term weight maintenance. The aim of this study was to compare the effects of exercise modalities combined with diet intervention on body composition immediately after intervention and at 3 years’ follow-up in overweight and obese adults. Two-hundred thirty-nine people (107 men) participated in a 6-month diet and exercise-based intervention, split into four randomly assigned groups: strength group (S), endurance group (E), combined strength and endurance group (SE), and control group (C). The body composition measurements took place on the first week before the start of training and after 22 weeks of training. In addition, a third measurement took place 3 years after the intervention period. A significant interaction effect (group × time) (p = 0.017) was observed for the fat mass percentage. It significantly decreased by 5.48 ± 0.65%, 5.30 ± 0.65%, 7.04 ± 0.72%, and 4.86 ± 0.65% at post-intervention for S, E, SE, and C, respectively. Three years after the intervention, the fat mass percentage returned to values similar to the baseline, except for the combined strength and endurance group, where it remained lower than the value at pre-intervention (p < 0.05). However, no significant interaction was discovered for the rest of the studied outcomes, neither at post-intervention nor 3 years later. The combined strength and endurance group was the only group that achieved lower levels of fat mass (%) at both post-intervention and 3 years after intervention, in comparison with the other groups.This work received financial support from the Ministerio de Ciencia e Innovación, Convocatoria de Ayudas I+D 2008, Proyectos de Investigación Fundamental No Orientada, del VI Plan de Investigación Nacional 2008–2011 (Contract: DEP2008-06354-C04-01). This study is registered at www.clinicaltrials.gov (ID: NCT0111685

Determining physiological and performance variables during a time trial in a first category mountain pass

Physiology and performance of uphill time-trials (TT) in professional road cycling have been previously described (Lucia A et al., 2004; Padilla S, Mujika I, Orbañanos J, & Angulo F, 2000; Padilla S, Mujika I, Santisteban J, Impellizzeri FM, & Goiriena JJ, 2008). Recent field-based uphill trials focused on power output due to its reliability and accuracy to assess aerobic and anaerobic performance (Bossi AH, Lima P, Perrout de Lima J, & Hopker J, 2016; Vogt et al., 2008; Vogt et al., 2007). However few studies have attempted to correlate the different physiological and performances variables in field conditions

Nutrition and physical activity programs for obesity treatment (PRONAF study). methodological approach of the project

Este trabajo aborda la metodología seguida para llevar a cabo el proyecto de investigación PRONAF (Clinical Trials Gov.: number NCT01116856.) Background: At present, scientific consensus exists on the multifactorial etiopatogenia of obesity. Both professionals and researchers agree that treatment must also have a multifactorial approach, including diet, physical activity, pharmacology and/or surgical treatment. These two last ones should be reserved for those cases of morbid obesities or in case of failure of the previous ones. The aim of the PRONAF study is to determine what type of exercise combined with caloric restriction is the most appropriate to be included in overweigth and obesity intervention programs, and the aim of this paper is to describe the design and the evaluation methods used to carry out the PRONAF study. Methods/design: One-hundred nineteen overweight (46 males) and 120 obese (61 males) subjects aged 18–50 years were randomly assigned to a strength training group, an endurance training group, a combined strength + endurance training group or a diet and physical activity recommendations group. The intervention period was 22 weeks (in all cases 3 times/wk of training for 22 weeks and 2 weeks for pre and post evaluation). All subjects followed a hypocaloric diet (25-30% less energy intake than the daily energy expenditure estimated by accelerometry). 29–34% of the total energy intake came from fat, 14–20% from protein, and 50–55% from carbohydrates. The mayor outcome variables assesed were, biochemical and inflamatory markers, body composition, energy balance, physical fitness, nutritional habits, genetic profile and quality of life. 180 (75.3%) subjects finished the study, with a dropout rate of 24.7%. Dropout reasons included: personal reasons 17 (28.8%), low adherence to exercise 3 (5.1%), low adherence to diet 6 (10.2%), job change 6 (10.2%), and lost interest 27 (45.8%). Discussion: Feasibility of the study has been proven, with a low dropout rate which corresponds to the estimated sample size. Transfer of knowledge is foreseen as a spin-off, in order that overweight and obese subjects can benefit from the results. The aim is to transfer it to sports centres. Effectiveness on individual health-related parameter in order to determine the most effective training programme will be analysed in forthcoming publications

Rich oleocanthal and oleacein extra virgin olive oil and inflammatory and antioxidant status in people with obesity and prediabetes. The APRIL study: A randomised, controlled crossover study

Background: Oleocanthal and oleacein are olive oil phenolic compounds with well known anti inflammatory and anti-oxidant properties. The main evidence, however, is provided by experimental studies. Few human studies have examined the health benefits of olive oils rich in these biophenols. Our aim was to assess the health properties of rich oleocanthal and oleacein extra virgin olive oil (EVOO), compared to those of common olive oil (OO), in people with prediabetes and obesity. Methods: Randomised, double-blind, crossover trial done in people aged 40e65 years with obesity (BMI 30e40 kg/m2 ) and prediabetes (HbA1c 5.7e6.4%). The intervention consisted in substituting for 1 month the oil used for food, both raw and cooked, by EVOO or OO. No changes in diet or physical activity were recommended. The primary outcome was the inflammatory status. Secondary outcomes were the oxidative status, body weight, glucose handling and lipid profile. An ANCOVA model adjusted for age, sex and treatment administration sequence was used for the statistical analysis. Results: A total of 91 patients were enrolled (33 men and 58 women) and finished the trial. A decrease in interferon-g was observed after EVOO treatment, reaching inter-treatment differences (P ¼ 0.041). Total antioxidant status increased and lipid and organic peroxides decreased after EVOO treatment, the changes reaching significance compared to OO treatment (P < 0.05). Decreases in weight, BMI and blood glucose (p < 0.05) were found after treatment with EVOO and not with OO. Conclusions: Treatment with EVOO rich in oleocanthal and oleacein differentially improved oxidative and inflammatory status in people with obesity and prediabetes.Funding for open access charge: Universidad de Málaga/CBU