Evaluation of the Efficiency of an ARM-based Beowulf Cluster versus Traditional Desktop Computing for High Performance Computing

In the realm of scientific computing, it has become increasingly important to focus on results driven growth (Kamil, Shalf and Storhmaier). Doing this enables researchers to continue building the rapidly expanding area of scientific discovery. However, with the growth comes a cost of the amount of resources consumed to accomplish these results. Large supercomputers are consuming power at a rate roughly fourteen thousand times that of a traditional American household (U.S. Energy Information Administration). Parallel to this, public consumers have been driving the mobile industry and the research behind it. The need to have faster and faster mobile devices that can last all day long on a single battery charge has driven the development of Advanced Reduced Instruction Set processors developed by ARM. These processors are built to perform efficiently while still maintaining the ability to perform the necessary calculations. This study looked at combining these two parallel realms and analyzing the overall efficiency and energy consumption of multiple ARM processors as compared to a traditional desktop computer. The results showed that the ARM processors were less efficient roughly by an order of two when compared to the slowest possible trial on the desktop. Several variables played a significant role in these results including the limitation on network speed and bandwidth, idle energy consumption, and individual power regulators

Fracture toughness of acrylic resins: Viscoelastic effects and deformation mechanisms

The time dependence of fracture toughness of two different acrylic resins, one plain and one toughened, intended to be used as continuous fiber composite matrices was studied. By performing fracture tests following the fracture mechanics approach, the energy release rate, GIc, was determined at different temperatures and displacement rates and by applying the time-temperature superposition it was possible to obtain GIc as a function of crack speed, math formula, over a wide range of speeds. The trends obtained for the two resins were different. For the plain resin it could be well described by J. G. Williams' viscoelastic fracture theory while for the toughened resin, the trend obtained was attributed to a change in the damage mechanism occurring at the crack tip during fracture. From measurements of the process zone size it was deduced that the damage mechanism at the crack tip for the plain resin was the same irrespective of time and temperature, for the toughened resin instead, different mechanisms seem to take place. This hypothesis was supported by results of volume strain measurements in tensile tests at different temperature and strain rates

Aplicació d'una xarxa neuronal per a la predicció de paraules en pacients neurodegeneratius

Els sistemes de reconeixement de veu basats en Machine Learning han pres una gran importància en els darrers anys. Aplicar aquests sistemes quan un pacient amb una malaltia neurodegenerativa ha perdut part de la parla es presenta com una solució per millorar la seva capacitat de comunicació; una tasca complicada degut, sobretot, a la gran variabilitat entre malalties i graus d’afectació en la parla. En aquest projecte es proposa un sistema de predicció de paraules individuals a partir d’anàlisi fonètic, implementat per la llengua castellana. Per fer això, s’ha dissenyat una xarxa neuronal classificadora entrenada amb fonemes etiquetats, i s’ha elaborat un bucle que recorre una gravació, n’extreu els fonemes, genera un string i, mitjançant la distància de Jaccard, el compara amb una llista de 28 paraules per retornar-ne la correcta. Els resultats mostren una efectivitat de classificació de fonemes del 46% i una exactitud de predicció de paraules del 40%. L’avaluació de l’algorisme el presenta com una solució poc precisa. Tot i així, part dels problemes que produeixen aquesta baixa efectivitat podrien ser compensats amb un augment del nombre de mostres d’entrenament, o bé, aplicant tècniques més avançades, com els Models Ocults de Markov, per millorar la classificació de fonemes.Los sistemas de reconocimiento de voz basados en Machine Learning han tomado una gran importancia en los últimos años. La aplicación de estos sistemas en pacientes que han perdido parte del habla por una enfermedad neurodegenerativa se presenta como una solución para mejorar su capacidad de comunicación. Esto es una tarea complicada debido, sobre todo, a la gran variabilidad entre enfermedades i grados de afectación en el habla. En este trabajo se propone un sistema de predicción de palabras individuales a partir de su análisis fonético, implementado para la lengua castellana. Para hacer esto, se ha diseñado una red neuronal clasificadora entrenada con fonemas etiquetados, y se ha elaborado un bucle que recorre una grabación, extrae los fonemas, genera un string y, usando la distancia de Jaccard, lo compara con una lista de 28 palabras para retornar la correcta. Los resultados muestran una efectividad de clasificación de fonemas del 46% y una exactitud de predicción de palabras del 40%. La evaluación del algoritmo lo presenta como una solución poco precisa. Aun así, parte de los problemas que producen la baja efectividad se podrían corregir aumentado el número de datos de entrenamiento, o bien, implementando técnicas más avanzadas, como podrían ser los Modelos Ocultos de Markov, para mejorar la clasificación de fonemas.Machine Leaning-based speech recognition systems have gained importance in the past few years. Using these models with patients who suffer from partial speech impairment due to a neurodegenerative disorder seems to be a good solution to improve their communication capabilities. However, this is a difficult task due to the wide variability between diseases and the severity of the speech loss. In this project, a single-word prediction system for Spanish language is proposed by using phonetic analysis. To do this, a classificatory neural network is designed and trained with labeled phonemes. Then, a simple loop is programmed to iterate over a speech recording, extract the phonemes, generate a string, and compare it with a 28-word list using the Jaccard distance to return the correct word. Results have shown a 46% accuracy at phoneme classification and 40% accuracy for word prediction. Consequently, the algorism has shown to be an imprecise solution. Anyway, some of the problems that caused this low effectiveness could be solved by augmenting the number of training samples or by using more advanced techniques, as the Hidden Markov Models, to improve the phoneme classification

Development and introduction of recombinant factor VIII – a clinician’s experience

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92006/1/hae2804.pd

The First Year: Development of Preservice Teacher Beliefs About Teaching and Learning During Year One of an MA TESOL Program

This qualitative, longitudinal study followed four first-year MA TESOL students through their initial year in a teacher training program with the goal of determining whether their overall beliefs about teaching and learning changed over time as a result of program curriculum and other outside factors. An analysis of semi-structured interviews with each participant, conducted one to two times per quarter, revealed that participants\u27 beliefs appeared to evolve as a result of coursework and teaching practice. Participants\u27 identities as teachers also showed signs of evolution and development. The participants attributed the majority of their development to hands-on teaching practice, though there was evidence that they began to integrate more theoretical aspects of program curriculum by the end of the year. However, the participants also demonstrated a lack of interest in theoretical and research-related coursework that persisted throughout their first year. Participants\u27 lack of interest and stress brought on by unfamiliar material may have limited the amount of integration of research and theory into their practice. Findings suggest a mismatch between program goals and student goals, with students being focused on teaching practice and the program being focused on both the practical and theoretical aspects of the curriculum

Devenires de la carne: la intervención de la tecnología en la configuración del cuerpo monstruoso dentro del discurso cinematográfico de David Cronenberg

En esta tesis se estudia el cuerpo monstruoso, una entidad compleja, desbordada y trasgresora que atenta contra la ley natural y social. La construcción de este análisis se organiza bajo la concepción de un cuerpo simbólico (situado en un contexto determinado por las lógicas de las sociedades de control capitalistas contemporáneas) configurado a partir de su constante interacción con la tecnología y observado desde su representación espectacular cinematográfica en el discurso del director y guionista David Cronenberg. Bajo la premisa que la emergencia del monstruo forma parte de mecanismos de poder vinculados con la tecnociencia, se analizan las maneras en que el monstruo desafía el equilibrio del cuerpo, la coherencia interna de los sujetos y los referentes de sentido que componen un orden social.Consejo Nacional de Ciencia y Tecnologí

Failure mechanism analysis based on laser-based surface treatments for aluminum-polyamide laser joining

The development of strong metal to polymer assemblies is currently an important research subject thanks to its prominence to develop lightweight structures. Furthermore, laser welding is known to be a fast, reliable, and versatile joining process, and it was demonstrated recently that it can be applied to such metal to polymer systems. To enhance the mechanical properties of the laser-joined aluminum-polyamide (Al-PA) specimens, laser polishing and laser ablation processes have been implemented on the aluminum surface before joining. The polyamide surface was also treated with the laser beam, separately. The surfaces were tested by several characterization techniques before and after each surface treatment. Then aluminum and polyamide samples with different surface treatments have been joined with an identical laser joining process. The mechanical properties of the joints in single lap shear configuration are reported and the failure mechanisms are discussed based on micro-computed x-ray tomography imaging of joined specimens and microscopic analysis before failure. Results show that both surface treatments of aluminum significantly improve the shear load of the joint; however, with different failure mechanisms. Polyamide surface treatment and increasing degree of crystallinity are effective when combined with the laser polishing of the Al surface. This combination is responsible for further enhancement of the shear load of the joint to the limit of base metal strength which is approximately 60 % improvement compared to the untreated samples. Finally, energy dispersive X-ray mapping shows the physicochemical bonding between aluminum oxide and polyamide at the interface

Direct observation of elemental fluctuation and oxygen octahedral distortion-dependent charge distribution in high entropy oxides

The enhanced compositional flexibility to incorporate multiple-principal cations in high entropy oxides (HEOs) offers the opportunity to expand boundaries for accessible compositions and unconventional properties in oxides. Attractive functionalities have been reported in some bulk HEOs, which are attributed to the long-range compositional homogeneity, lattice distortion, and local chemical bonding characteristics in materials. However, the intricate details of local composition fluctuation, metal-oxygen bond distortion and covalency are difficult to visualize experimentally, especially on the atomic scale. Here, we study the atomic structure-chemical bonding-property correlations in a series of perovskite-HEOs utilizing the recently developed four-dimensional scanning transmission electron microscopy techniques which enables to determine the structure, chemical bonding, electric field, and charge density on the atomic scale. The existence of compositional fluctuations along with significant composition-dependent distortion of metal-oxygen bonds is observed. Consequently, distinct variations of metal-oxygen bonding covalency are shown by the real-space charge-density distribution maps with sub-ångström resolution. The observed atomic features not only provide a realistic picture of the local physico-chemistry of chemically complex HEOs but can also be directly correlated to their distinctive magneto-electronic properties