1RM prediction: a data mining case study

In the last few years there has been a heightened interest in data treatment and analysis with the aim of discovering hidden knowledge and eliciting relationships and patterns within this data. Data mining techniques (also known as Knowledge Discovery in Databases) have been applied over a wide range of fields such as marketing, investment, fraud detection, manufacturing, telecommunications and health. In this study, well-known data mining techniques such as artificial neural networks (ANN), genetic programming (GP), forward selection linear regression (LR) and k-means clustering techniques, are proposed to the health and sports community in order to aid with resistance training prescription. Appropriate resistance training prescription is effective for developing fitness, health and for enhancing general quality of life. Resistance exercise intensity is commonly prescribed as a percent of the one repetition maximum. 1RM, dynamic muscular strength, one repetition maximum or one execution maximum, is operationally defined as the heaviest load that can be moved over a specific range of motion, one time and with correct performance. The safety of the 1RM assessment has been questioned as such an enormous effort may lead to muscular injury. Prediction equations could help to tackle the problem of predicting the 1RM from submaximal loads, in order to avoid or at least, reduce the associated risks. We built different models from data on 30 men who performed up to 5 sets to exhaustion at different percentages of the 1RM in the bench press action, until reaching their actual 1RM. Also, a comparison of different existing prediction equations is carried out. The LR model seems to outperform the ANN and GP models for the 1RM prediction in the range between 1 and 10 repetitions. At 75% of the 1RM some subjects (n = 5) could perform 13 repetitions with proper technique in the bench press action, whilst other subjects (n = 20) performed statistically significant (p < 0:05) more repetitions at 70% than at 75% of their actual 1RM in the bench press action. Rate of perceived exertion (RPE) seems not to be a good predictor for 1RM when all the sets are performed until exhaustion, as no significant differences (p < 0:05) were found in the RPE at 75%, 80% and 90% of the 1RM. Also, years of experience and weekly hours of strength training are better correlated to 1RM (p < 0:05) than body weight. O'Connor et al. 1RM prediction equation seems to arise from the data gathered and seems to be the most accurate 1RM prediction equation from those proposed in literature and used in this study. Epley's 1RM prediction equation is reproduced by means of data simulation from 1RM literature equations. Finally, future lines of research are proposed related to the problem of the 1RM prediction by means of genetic algorithms, neural networks and clustering techniques. RESUMEN En los últimos años ha habido un creciente interés en el tratamiento y análisis de datos con el propósito de descubrir relaciones, patrones y conocimiento oculto en los mismos. Las técnicas de data mining (también llamadas de \Descubrimiento de conocimiento en bases de datos\) se han aplicado consistentemente a lo gran de un gran espectro de áreas como el marketing, inversiones, detección de fraude, producción industrial, telecomunicaciones y salud. En este estudio, técnicas bien conocidas de data mining como las redes neuronales artificiales (ANN), programación genética (GP), regresión lineal con selección hacia adelante (LR) y la técnica de clustering k-means, se proponen a la comunidad del deporte y la salud con el objetivo de ayudar con la prescripción del entrenamiento de fuerza. Una apropiada prescripción de entrenamiento de fuerza es efectiva no solo para mejorar el estado de forma general, sino para mejorar la salud e incrementar la calidad de vida. La intensidad en un ejercicio de fuerza se prescribe generalmente como un porcentaje de la repetición máxima. 1RM, fuerza muscular dinámica, una repetición máxima o una ejecución máxima, se define operacionalmente como la carga máxima que puede ser movida en un rango de movimiento específico, una vez y con una técnica correcta. La seguridad de las pruebas de 1RM ha sido cuestionada debido a que el gran esfuerzo requerido para llevarlas a cabo puede derivar en serias lesiones musculares. Las ecuaciones predictivas pueden ayudar a atajar el problema de la predicción de la 1RM con cargas sub-máximas y son empleadas con el propósito de eliminar o al menos, reducir los riesgos asociados. En este estudio, se construyeron distintos modelos a partir de los datos recogidos de 30 hombres que realizaron hasta 5 series al fallo en el ejercicio press de banca a distintos porcentajes de la 1RM, hasta llegar a su 1RM real. También se muestra una comparación de algunas de las distintas ecuaciones de predicción propuestas con anterioridad. El modelo LR parece superar a los modelos ANN y GP para la predicción de la 1RM entre 1 y 10 repeticiones. Al 75% de la 1RM algunos sujetos (n = 5) pudieron realizar 13 repeticiones con una técnica apropiada en el ejercicio press de banca, mientras que otros (n = 20) realizaron significativamente (p < 0:05) más repeticiones al 70% que al 75% de su 1RM en el press de banca. El ínndice de esfuerzo percibido (RPE) parece no ser un buen predictor del 1RM cuando todas las series se realizan al fallo, puesto que no existen diferencias signifiativas (p < 0:05) en el RPE al 75%, 80% y el 90% de la 1RM. Además, los años de experiencia y las horas semanales dedicadas al entrenamiento de fuerza están más correlacionadas con la 1RM (p < 0:05) que el peso corporal. La ecuación de O'Connor et al. parece surgir de los datos recogidos y parece ser la ecuación de predicción de 1RM más precisa de aquellas propuestas en la literatura y empleadas en este estudio. La ecuación de predicción de la 1RM de Epley es reproducida mediante simulación de datos a partir de algunas ecuaciones de predicción de la 1RM propuestas con anterioridad. Finalmente, se proponen futuras líneas de investigación relacionadas con el problema de la predicción de la 1RM mediante algoritmos genéticos, redes neuronales y técnicas de clustering.

Validation of the SenseWear armband in circuit resistance training with different loads

The use of the SenseWear™ armband (SWA), an objective monitor of physical activity, is a relatively new device used by researchers to measure energy expenditure. These monitors are practical, relatively inexpensive and easy-to-use. The aim of the present study was to assess the validity of SWAs for the measurement of energy expenditure (EE) in circuit resistance training (CRT) at three different intensities in moderately active, healthy subjects. The study subjects (17 females, 12 males) undertook CRT at 30, 50 and 70% of the 15 repetition maximum for each exercise component wearing an SWA as well as an Oxycon Mobile (OM) portable metabolic system (a gold standard method for measuring EE). The EE rose as exercise intensity increased, but was underestimated by the SWAs. For women, Bland-Altman plots showed a bias of 1.13 ± 1.48 METs and 32.1 ± 34.0 kcal in favour of the OM system, while for men values of 2.33 ± 1.82 METs and 75.8 ± 50.8 kcal were recorded.

Effects of increasing levels of pea hulls in the diet on productive performance, development of the gastrointestinal tract, and nutrient retention of broilers from one to eighteeen days of age

The effects of inclusion of pea hulls (PH) in the diet on growth performance, development of the gastrointestinal tract and nutrient retention were studied in broilers from 1 to 18d of age. There were a control diet based on low fibre ingredients (69.3 total dietary fibre (16.1g crude fibre/kg)) and three additional diets that resulted from the dilution of the basal diet with 25, 50 and 75g PH/kg (81.2, 93.2, and 105.1g total dietary fibre/kg diet, respectively). Each treatment was replicated six times and the experimental unit was a cage with 12 chicks. Growth performance, development of the gastrointestinal tract and the coefficients of total tract apparent retention (CTTAR) of nutrients were recorded at 6, 12 and 18d of age. In addition, jejunal morphology was measured at 12 and 18d and the coefficients of apparent ileal digestibility (CAID) of nutrients at 18d of age. Pea hulls inclusion affected all the parameters studied. The inclusion of 25 and 50g PH/kg diet improved growth performance as compared to the control diet. The relative weight (g/kg body weight) of proventriculus (P≤0.01), gizzard (P≤0.001) and ceca (P≤0.05) increased linearly as the level of PH in the diet increased. The inclusion of PH affected quadratically (P≤0.01) villus height:crypt depth ratio with the highest value shown at 25g PH/kg. In general, the CTTAR and CAID of nutrients increased linearly and quadratically (P≤0.05) with increasing levels of PH, showing maximum values with PH level between 25 and 50g/kg diet. We conclude that the size of the digestive organs increases with increasing levels of PH in the diet. In general, the best performance and nutrient digestibility values were observed with levels of PH within the range of 25 and 50g/kg. Therefore, young broilers have a requirement for a minimum amount of dietary fibre. When pea hulls are used as a source of fibre, the level of total dietary fibre required for optimal performance is within the range of 81.2–93.2g/kg diet (25.6–35.0g crude fibre/kg diet). An excess of total dietary fibre (above 93.2g/kg diet) might reduce nutrient digestibility and growth performance to values similar to those observed with the control diet.

Power output fluctuations in large scale PV plants: one year observations with one second resolution and a derived analytic model

The variable nature of the irradiance can produce significant fluctuations in the power generated by large grid-connected photovoltaic (PV) plants. Experimental 1 s data were collected throughout a year from six PV plants, 18 MWp in total. Then, the dependence of short (below 10 min) power fluctuation on PV plant size has been investigated. The analysis focuses on the study of fluctuation frequency as well as the maximum fluctuation value registered. An analytic model able to describe the frequency of a given fluctuation for a certain day is proposed

Synchrotron X-ray photoabsorption spectroscopy of plasmas

Theoretical X-ray opacities are used in numerous radiative transfer simulations of plasmas at different temperatures and densities, for example astrophysics, fusion, metrology and EUV and X-rays radiation sources. However, there are only a reduced number of laboratories working on the validation of those theoretical results empirically, in particular for high temperature plasmas (mayor que 1eV). One of those limitations comes from the use of broad band EUV- X ray sources to illuminate the plasma which, among other issues, present low reproducibility and repetition rate [1]. Synchrotron radiation facilities are a more appropriate radiation source in that sense, since they provide tunable, reproducible and high resolution photons. Only their ?low? photon intensity for these experiments has prevented researchers to use it for this purpose. However, as new synchrotron facilities improve their photon fluxes, this limitation not longer holds [2]. This work evaluates the experimental requirements to use third generation synchrotron radiation sources for the empirical measurement of opacities of plasmas, proposing a pausible experimental set-up to carry them out. Properties of the laser or discharge generated plasmas to be studied with synchrotron radiation will be discussed in terms of their maximum temperatures, densities and temporal evolution. It will be concluded that there are encouraging reasons to pursue these kind of experiments which will provide with an appropriate benchmark for theoretical opacities

One-watt fiber-based power-by-light system for satellite applications

In this work, a fiber-based optical powering (or power-by-light) system capable of providing more than 1 W is developed. The prototype was used in order to power a shunt regulator for controlling the activation and deactivation of solar panels in satellites. The work involves the manufacture of a light receiver (a GaAs multiple photovoltaic converter (MPC)), a power conditioning block, and a regulator and the implementation and characterization of the whole system. The MPC, with an active area of just 3.1 mm2, was able to supply 1 W at 5 V with an efficiency of 30%. The maximum measured device efficiency was over 40% at an input power (Pin) of 0.5 W. Open circuit voltage over 7 V was measured for Pin over 0.5 W. A system optoelectronic efficiency (including the optical fiber, connectors, and MPC) of 27% was measured at an output power (Pout) of 1 W. At Pout = 0.2 W, the efficiency was as high as 36%. The power conditioning block and the regulator were successfully powered with the system. The maximum supplied power in steady state was 0.2 W, whereas in transient state, it reached 0.44 W. The paper also describes the characterization of the system within the temperature range going from -70 to +100?°C.

Maximum likelihood estimation of new state space models for operational modal analysis

The modal analysis of a structural system consists on computing its vibrational modes. The experimental way to estimate these modes requires to excite the system with a measured or known input and then to measure the system output at different points using sensors. Finally, system inputs and outputs are used to compute the modes of vibration. When the system refers to large structures like buildings or bridges, the tests have to be performed in situ, so it is not possible to measure system inputs such as wind, traffic, . . .Even if a known input is applied, the procedure is usually difficult and expensive, and there are still uncontrolled disturbances acting at the time of the test. These facts led to the idea of computing the modes of vibration using only the measured vibrations and regardless of the inputs that originated them, whether they are ambient vibrations (wind, earthquakes, . . . ) or operational loads (traffic, human loading, . . . ). This procedure is usually called Operational Modal Analysis (OMA), and in general consists on to fit a mathematical model to the measured data assuming the unobserved excitations are realizations of a stationary stochastic process (usually white noise processes). Then, the modes of vibration are computed from the estimated model. The first issue investigated in this thesis is the performance of the Expectation- Maximization (EM) algorithm for the maximum likelihood estimation of the state space model in the field of OMA. The algorithm is described in detail and it is analysed how to apply it to vibration data. After that, it is compared to another well known method, the Stochastic Subspace Identification algorithm. The maximum likelihood estimate enjoys some optimal properties from a statistical point of view what makes it very attractive in practice, but the most remarkable property of the EM algorithm is that it can be used to address a wide range of situations in OMA. In this work, three additional state space models are proposed and estimated using the EM algorithm: • The first model is proposed to estimate the modes of vibration when several tests are performed in the same structural system. Instead of analyse record by record and then compute averages, the EM algorithm is extended for the joint estimation of the proposed state space model using all the available data. • The second state space model is used to estimate the modes of vibration when the number of available sensors is lower than the number of points to be tested. In these cases it is usual to perform several tests changing the position of the sensors from one test to the following (multiple setups of sensors). Here, the proposed state space model and the EM algorithm are used to estimate the modal parameters taking into account the data of all setups. • And last, a state space model is proposed to estimate the modes of vibration in the presence of unmeasured inputs that cannot be modelled as white noise processes. In these cases, the frequency components of the inputs cannot be separated from the eigenfrequencies of the system, and spurious modes are obtained in the identification process. The idea is to measure the response of the structure corresponding to different inputs; then, it is assumed that the parameters common to all the data correspond to the structure (modes of vibration), and the parameters found in a specific test correspond to the input in that test. The problem is solved using the proposed state space model and the EM algorithm. Resumen El análisis modal de un sistema estructural consiste en calcular sus modos de vibración. Para estimar estos modos experimentalmente es preciso excitar el sistema con entradas conocidas y registrar las salidas del sistema en diferentes puntos por medio de sensores. Finalmente, los modos de vibración se calculan utilizando las entradas y salidas registradas. Cuando el sistema es una gran estructura como un puente o un edificio, los experimentos tienen que realizarse in situ, por lo que no es posible registrar entradas al sistema tales como viento, tráfico, . . . Incluso si se aplica una entrada conocida, el procedimiento suele ser complicado y caro, y todavía están presentes perturbaciones no controladas que excitan el sistema durante el test. Estos hechos han llevado a la idea de calcular los modos de vibración utilizando sólo las vibraciones registradas en la estructura y sin tener en cuenta las cargas que las originan, ya sean cargas ambientales (viento, terremotos, . . . ) o cargas de explotación (tráfico, cargas humanas, . . . ). Este procedimiento se conoce en la literatura especializada como Análisis Modal Operacional, y en general consiste en ajustar un modelo matemático a los datos registrados adoptando la hipótesis de que las excitaciones no conocidas son realizaciones de un proceso estocástico estacionario (generalmente ruido blanco). Posteriormente, los modos de vibración se calculan a partir del modelo estimado. El primer problema que se ha investigado en esta tesis es la utilización de máxima verosimilitud y el algoritmo EM (Expectation-Maximization) para la estimación del modelo espacio de los estados en el ámbito del Análisis Modal Operacional. El algoritmo se describe en detalle y también se analiza como aplicarlo cuando se dispone de datos de vibraciones de una estructura. A continuación se compara con otro método muy conocido, el método de los Subespacios. Los estimadores máximo verosímiles presentan una serie de propiedades que los hacen óptimos desde un punto de vista estadístico, pero la propiedad más destacable del algoritmo EM es que puede utilizarse para resolver un amplio abanico de situaciones que se presentan en el Análisis Modal Operacional. En este trabajo se proponen y estiman tres modelos en el espacio de los estados: • El primer modelo se utiliza para estimar los modos de vibración cuando se dispone de datos correspondientes a varios experimentos realizados en la misma estructura. En lugar de analizar registro a registro y calcular promedios, se utiliza algoritmo EM para la estimación conjunta del modelo propuesto utilizando todos los datos disponibles. • El segundo modelo en el espacio de los estados propuesto se utiliza para estimar los modos de vibración cuando el número de sensores disponibles es menor que vi Resumen el número de puntos que se quieren analizar en la estructura. En estos casos es usual realizar varios ensayos cambiando la posición de los sensores de un ensayo a otro (múltiples configuraciones de sensores). En este trabajo se utiliza el algoritmo EM para estimar los parámetros modales teniendo en cuenta los datos de todas las configuraciones. • Por último, se propone otro modelo en el espacio de los estados para estimar los modos de vibración en la presencia de entradas al sistema que no pueden modelarse como procesos estocásticos de ruido blanco. En estos casos, las frecuencias de las entradas no se pueden separar de las frecuencias del sistema y se obtienen modos espurios en la fase de identificación. La idea es registrar la respuesta de la estructura correspondiente a diferentes entradas; entonces se adopta la hipótesis de que los parámetros comunes a todos los registros corresponden a la estructura (modos de vibración), y los parámetros encontrados en un registro específico corresponden a la entrada en dicho ensayo. El problema se resuelve utilizando el modelo propuesto y el algoritmo EM.

Development of One Meter Long Double-Sided CeO2 Buffered Ni-5at.W Templates by Reel-to-Reel Chemical Solution Deposition Route

High performance long-length coated conductors fabricated using various techniques have attracted a lot of interest recently. In this work, a reel-to-reel design for depositing double-sided coatings on long-length flexible metallic tapes via a chemical solution method is proposed and realized. The major achievement of the design is to combine the dip coating and drying processes in order to overcome the technical difficulties of dealing with the wet films on both sides of the tape. We report the successful application of the design to fabricate a one-meter-long double side coated CeO2/Ni-5at%W template. The CeO2 films on both sides exhibit a dense, crack-free morphology, and a high fraction of cube texture on the surface. Homogeneity studies on global texture over the length also reveal that the average full width at half maximum values of the in-plane and out-of-plane orientation on the CeO2 layer are 7.2 ° and 5.8° with standard deviation of 0.26° and 0.34°, respectively, being indicative of the high quality epitaxial growth of the films prepared in the continuous manner. An all chemical solution derived YBCOLow-TFA/Ce0.9La0.1O2 /Gd2Zr2O7/CeO2 structure is obtained on a short sample, demonstrating the possibility of producing long-length texture templates for coated conductors by this low cost deposition route.