752 resultados para Engineering -- Data processing -- Study and teaching
Resumo:
Current scientific applications have been producing large amounts of data. The processing, handling and analysis of such data require large-scale computing infrastructures such as clusters and grids. In this area, studies aim at improving the performance of data-intensive applications by optimizing data accesses. In order to achieve this goal, distributed storage systems have been considering techniques of data replication, migration, distribution, and access parallelism. However, the main drawback of those studies is that they do not take into account application behavior to perform data access optimization. This limitation motivated this paper which applies strategies to support the online prediction of application behavior in order to optimize data access operations on distributed systems, without requiring any information on past executions. In order to accomplish such a goal, this approach organizes application behaviors as time series and, then, analyzes and classifies those series according to their properties. By knowing properties, the approach selects modeling techniques to represent series and perform predictions, which are, later on, used to optimize data access operations. This new approach was implemented and evaluated using the OptorSim simulator, sponsored by the LHC-CERN project and widely employed by the scientific community. Experiments confirm this new approach reduces application execution time in about 50 percent, specially when handling large amounts of data.
Resumo:
Methodological evaluation of the proteomic analysis of cardiovascular-tissue material has been performed with a special emphasis on establishing examinations that allow reliable quantitative analysis of silver-stained readouts. Reliability, reproducibility, robustness and linearity were addressed and clarified. In addition, several types of normalization procedures were evaluated and new approaches are proposed. It has been found that the silver-stained readout offers a convenient approach for quantitation if a linear range for gel loading is defined. In addition, a broad range of a 10-fold input (loading 20-200 microg per gel) fulfills the linearity criteria, although at the lowest input (20 microg) a portion of protein species will remain undetected. The method is reliable and reproducible within a range of 65-200 microg input. The normalization procedure using the sum of all spot intensities from a silver-stained 2D pattern has been shown to be less reliable than other approaches, namely, normalization through median or through involvement of interquartile range. A special refinement of the normalization through virtual segmentation of pattern, and calculation of normalization factor for each stratum provides highly satisfactory results. The presented results not only provide evidence for the usefulness of silver-stained gels for quantitative evaluation, but they are directly applicable to the research endeavor of monitoring alterations in cardiovascular pathophysiology.
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This study adapted the current model of science undergraduate research experiences (URE's) and applied this novel modification to include community college students. Numerous researchers have examined the efficacy of URE's in improving undergraduate retention and graduation rates, as well as matriculation rates for graduate programs. However, none have detailed the experience for community college students, and few have employed qualitative methodologies to gather relevant descriptive data from URE participants. This study included perspectives elicited from both non-traditional student participants and the established laboratory community. The purpose of this study was to determine the effectiveness of the traditional model for a non-traditional student population. The research effort described here utilized a qualitative design and an explanatory case study methodology. Six non-traditional students from the Maine Community College System participated in this study. Student participants were placed in six academic research laboratories located throughout the state. Student participants were interviewed three times during their ten-week internship and asked to record their personal reflections in electronic format. Participants from the established research community were also interviewed. These included both faculty mentors and other student laboratory personnel. Ongoing comparative analysis of the textual data revealed that laboratory organizational structure and social climate significantly influence acculturation outcomes for non-traditional URE participants. Student participants experienced a range of acculturation outcomes from full integration to marginalization. URE acculturation outcomes influenced development of non-traditional students? professional and academic self-concepts. Positive changes in students? self-concepts resulted in greater commitment to individual professional goals and academic aspirations. The findings from this study suggest that traditional science URE models can be successfully adapted to meet the unique needs of a non-traditional student population – community college students. These interpretations may encourage post-secondary educators, administrators, and policy makers to consider expanded access and support for non-traditional students seeking science URE opportunities.
Resumo:
This study intended to measure teacher mathematical content knowledge both before and after the first year of teaching and taking graduate teacher education courses in the Teach for America (TFA) program, as well as measure attitudes toward mathematics and teaching both before and after TFA teachers’ first year. There was a significant increase in both mathematical content knowledge and attitudes toward mathematics over the TFA teachers’ first year teaching. Additionally, several significant correlations were found between attitudes toward mathematics and content knowledge. Finally, after a year of teaching, TFA teachers had significantly better attitudes toward mathematics and teaching than neutral.
Resumo:
An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^
Resumo:
In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.
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Area, launched in 1999 with the Bologna Declaration, has bestowed such a magnitude and unprecedented agility to the transformation process undertaken by European universities. However, the change has been more profound and drastic with regards to the use of new technologies both inside and outside the classroom. This article focuses on the study and analysis of the technology’s history within the university education and its impact on teachers, students and teaching methods. All the elements that have been significant and innovative throughout the history inside the teaching process have been analyzed, from the use of blackboard and chalk during lectures, the use of slide projectors and transparent slides, to the use of electronic whiteboards and Internet nowadays. The study is complemented with two types of surveys that have been performed among teachers and students during the school years 1999 - 2011 in the School of Civil Engineering at the Polytechnic University of Madrid. The pros and cons of each of the techniques and methodologies used in the learning process over the last decades are described, unfolding how they have affected the teacher, who has evolved from writing on a whiteboard to project onto a screen, the student, who has evolved from taking handwritten notes to download information or search the Internet, and the educational process, that has evolved from the lecture to acollaborative learning and project-based learning. It is unknown how the process of learning will evolve in the future, but we do know the consequences that some of the multimedia technologies are having on teachers, students and the learning process. It is our goal as teachers to keep ourselves up to date, in order to offer the student adequate technical content, while providing proper motivation through the use of new technologies. The study provides a forecast in the evolution of multimedia within the classroom and the renewal of the education process, which in our view, will set the basis for future learning process within the context of this new interactive era.
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This paper addresses the historical evolution of, from its inception, to the present day, within the changing context of EHEA and linked to professional competences. The research methodology, although it is mainly a historical document review, expert opinions on university educational planning of university education of forestry engineering in Spain are also included. The results show the evolution of centralized planning, based on technical knowledge transmission to an approach based on competences (technical, contextual and behavioral) focusing on learning for improving employability.
Resumo:
We describe the use of singular value decomposition in transforming genome-wide expression data from genes × arrays space to reduced diagonalized “eigengenes” × “eigenarrays” space, where the eigengenes (or eigenarrays) are unique orthonormal superpositions of the genes (or arrays). Normalizing the data by filtering out the eigengenes (and eigenarrays) that are inferred to represent noise or experimental artifacts enables meaningful comparison of the expression of different genes across different arrays in different experiments. Sorting the data according to the eigengenes and eigenarrays gives a global picture of the dynamics of gene expression, in which individual genes and arrays appear to be classified into groups of similar regulation and function, or similar cellular state and biological phenotype, respectively. After normalization and sorting, the significant eigengenes and eigenarrays can be associated with observed genome-wide effects of regulators, or with measured samples, in which these regulators are overactive or underactive, respectively.
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A mathematical model for regulation of the tryptophan operon is presented. This model takes into account repression, feedback enzyme inhibition, and transcriptional attenuation. Special attention is given to model parameter estimation based on experimental data. The model's system of delay differential equations is numerically solved, and the results are compared with experimental data on the temporal evolution of enzyme activity in cultures of Escherichia coli after a nutritional shift (minimal + tryptophan medium to minimal medium). Good agreement is obtained between the numeric simulations and the experimental results for wild-type E. coli, as well as for two different mutant strains.
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Aerobic Gymnastic is the ability to perform complex movements produced by the traditional aerobic exercises, in a continuous manner, with high intensity, perfectly integrated with soundtracks. This sport is performed in an aerobic/anaerobic lactacid condition and expects the execution of complex movements produced by the traditional aerobic exercises integrated with difficulty elements performed with a high technical level. An inaccuracy about this sport is related to the name itself “aerobic” because Aerobic Gymnastic does not use just the aerobic work during the competition, due to the fact that the exercises last among 1’30” and 1’45” at high rhythm. Agonistic Aerobics exploit the basic movements of amateur Aerobics and its coordination schemes, even though the agonistic Aerobics is so much intense than the amateur Aerobics to need a completely different mix of energetic mechanisms. Due to the complexity and the speed with which you perform the technical elements of Aerobic Gymnastic, the introduction of video analysis is essential for a qualitative and quantitative evaluation of athletes’ performance during the training. The performance analysis can allow the accurate analysis and explanation of the evolution and dynamics of a historical phenomenon and motor sports. The notational analysis is used by technicians to have an objective analysis of performance. Tactics, technique and individual movements can be analyzed to help coaches and athletes to re-evaluate their performance and gain advantage during the competition. The purpose of the following experimental work will be a starting point for analyzing the performance of the athletes in an objective way, not only during competitions, but especially during the phases of training. It is, therefore, advisable to introduce the video analysis and notational analysis for more quantitative and qualitative examination of technical movements. The goal is to lead to an improvement of the technique of the athlete and the teaching of the coach.