Accelerating FIU’s science research and education towards discovery and innovation by leveraging FIU’s Science DMZ

Research faculty and their students are spending too much time on data management issues related to the transfer of data between networks. As the campus cyberinfrastructure increases data production, the transport capacity of the network must increase proportionally to deliver the data to the High-Performance Computing centers for analysis. This work presents the experience of a research project in implementing Science DMZ at Florida International University, which added six researchers and their laboratories to the Science Network and Science DMZ. The study applied a qualitative approach to assessing the researcher’s science workflows in order to create a Science DMZ implementation plan and followed the Energy Sciences Network implementation guide

Metodología de desarrollo de técnicas de agrupamiento de datos usando aprendizaje automático

Context: Today, the usage of large amounts of data acquired from various electronic, optical, or other measurement devices and equipment brings the problem of data analysis at the time of extracting the aimed information from the acquired samples. Where to correctly group the data is necessary to obtain relevant and accurate information to evidence the physical phenomenon that you want to address. Methodology: The work presents the development and evolution of a five-stage methodology for the development of a data grouping technique, using machine learning techniques and artificial intelligence. It consists of five phases called analysis, design, development, evaluation, and distribution, using open-source standards, and based on unified languages for the interpretation of software in engineering. Results: The validation of the methodology was developed through the creation of two data analysis methods, with an average execution time of 20 weeks, obtaining precision values 40% and 29% higher with the classic data grouping algorithms of k-means and fuzzy cmeans. Additionally, there is a massive experimentation methodology on automated unit tests, which managed to group, label, and validate 3.6 million samples accumulated in the total of 100 group runs of 900 samples in approximately 2 hours. Conclusions: Finally, with the results of the research was determined that the methodology intends to guide the systematic development in specific problems in quantitative databases, such as the channel parameters in a communication system or the segmentation of images using the RGB values of the pixels. Even when software is developed both hardware, the execution will be more versatile than in cases with theoretical applications.Contexto: Hoy en día, el uso de grandes cantidades de datos adquiridos desde diversos dispositivos y equipos electrónicos, ópticos u otra tecnología de medición, generan un problema de análisis de datos en el momento de extraer la información de interés desde las muestras adquiridas. En ellos, agrupar correctamente los datos es necesario para obtener información relevante y precisa para evidenciar el fenómeno físico que se desea abordar. Metodología: El trabajo presenta la evolución de una metodología de cinco etapas para el desarrollo de una técnica de agrupamiento de datos, a través de técnicas de aprendizaje automático e inteligencia artificial. Esta se compone de cinco fases denominadas análisis, diseño, desarrollo, evaluación y distribución, con estándares de código abierto y fundamentadas en los lenguajes unificados para la interpretación del software en ingeniería. Resultados: La validación de la metodología se ha desarrollado mediante la creación de dos métodos de análisis de datos, con un tiempo de ejecución promedio de 20 semanas, obteniendo valores de precisión 40 % y 29 % superiores con los algoritmos clásicos de agrupamiento de datos de k-means y fuzzy c-means. Adicionalmente, se encuentra una metodología de experimentación masiva sobre pruebas unitarias automatizadas, las cuales lograron agrupar, etiquetar y validar 3,6 millones de muestras, acumulado un total de 100 ejecuciones de grupos de 900 muestras, en aproximadamente 2 horas. Conclusiones: Con los resultados de la investigación se ha determinado que la metodología pretende orientar el desarrollo sistemático de técnicas de agrupamiento de datos, en problemas específicos para bases integradas por muestras con atributos cuantitativos, como los casos de parámetros de canal en un sistema de comunicaciones o la segmentación de imágenes usando los valoras RGB de los pixeles; incluso, cuando se desarrolla software y hardware, la ejecución será más versátil que en casos con aplicaciones teóricas

Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method

We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications

Evaluación de diferentes tipos de controles de roya (Hemileia vastatrix Berk. & Broome) y pestalotiopsis (Pestalotia sp.), en el cultivo de la fruta milagrosa (Synsepalum dulcificum ADC)

In Ecuador, production of non-traditional fruits increases annually in 4%. The miraculous fruit (Synsepalum dulcificum) has become an excellent option as a non-traditional natural sweetener. However, this plant is susceptible to diseases such as rust (Hemileia vastatrix) and pestalotiopsis (Pestalotia sp), which affect the leaf area decreasing metabolic processes and the photosynthetic development. Silicon in plants affects pathogen infection and can contribute in this crop with rust and pestalotiosis control. In this study, different treatments were evaluated for rust and pestalotiosis control: 1) soil silicon application, 2) foliar silicon application, 3) chemical control, 4) biological control and 5) the control without any treatment. Variables evaluated were: a) incidence of rust and pestalotiopsis on leaves, b) incidence of rust and pestalotiopsis on fruits; c) fruit quality (healthy and fruits with high quality); and d) yield of fruits. Incidence of rust and pestalotiopsis on leaves and fruits were lower with the chemical control, reducing the diseases incidence to less than 2%. In addition, a positive relationship was obtained between the chemical control and fruit quality, since no damage were observed were observed, and the yield reached 202 kg ha-1 year-1 of miraculous fruits.En el Ecuador, la tendencia de la producción de frutas no tradicionales se incrementa anualmente en un 4%. La fruta milagrosa (Synsepalum dulcificum) se ha convertido en una excelente opción al momento de incursionar en la explotación de frutas no tradicionales para edulcorantes naturales. Sin embargo, esta planta es susceptible a enfermedades como la roya (Hemileia vastatrix) y pestalotiopsis (Pestalotia sp), afectando el área foliar y los frutos, los procesos metabólicos y el desarrollo fotosintético. Por otra parte, el silicio en las plantas evita la infección de patógenos, y en este caso podría utilizarse para el control de la roya. En este estudio se evaluó el manejo de roya y pestalotiopsis en el cultivo de la fruta milagrosa. Se evaluaron los siguientes tratamientos: 1) aplicaciones de silicio al suelo, 2) aplicaciones foliares de silicio, 3) control químico, 4) control biológico, y 5) testigo sin aplicación. Las variables evaluadas fueron: a) incidencia de roya y pestalotiopsis en hojas; b) incidencia de roya y pestalotiopsis en frutos; c) calidad del fruto (porcentaje de frutos sanos y de buena calidad); y d) rendimiento del cultivo. La incidencia de roya y pestalotiopsis en hojas y frutos fue menor en el control químico, y fue el mejor tratamiento para el control de estas enfermedades, con una incidencia menor a 2%. Adicionalmente, hubo una relación directa y positiva entre el control químico y la calidad de la fruta, ya que no existieron frutos dañados en dicho tratamiento, y el rendimiento llego a 202 kg ha-1 año-1 de fruta milagrosa

City of Hitchcock Comprehensive Plan 2020-2040

Hitchcock is a small town located in Galveston County (Figure 1.1), nestled up on the Texas Gulf Coast. It lies about 40 miles south-east of Houston. The boundaries of the city encloses an area of land of 60.46 sq. miles, an area of water of 31.64 sq. miles at an elevation just 16 feet above sea level. Hitchcock has more undeveloped land (~90% of total area) than the county combined. Its strategic location gives it a driving force of opportunities in the Houston-Galveston Region.The guiding principles for this planning process were Hitchcock’s vision statement and its corresponding goals, which were crafted by the task force. The goals focus on factors of growth and development including public participation, development considerations, transportation, community facilities, economic development, parks, and housing and social vulnerabilityTexas Target Communitie

Temas Socio-Jurídicos. Volumen 20 No. 43 Diciembre 2002

Con la edición del número 43 de la Revista Temas Socio-Jurídicos se cierra el ciclo de los primeros veinte años, continuos, de labores de este medio académico destinado a divulgar la labor intelectual de docentes y discentes de la Facultad de Derecho de la Universidad Autónoma de Bucaramanga. En medio del convulso e inestable escenario jurídico del país, se pretende contribuir a la construcción de un pensamiento jurídico ligado a la realidad social que plantea desde las distintas vertientes de la opinión tópicos inquietantes para el medio académico, procurando decantamiento y comprensión de los fenómenos al tiempo que propicia la controversía y la libre expresión de los diferentes puntos de vista, en desarrollo de los principios que orientan esta casa de estudios.With the edition of number 43 of the Socio-Legal Issues Magazine, the cycle of the first twenty continuous years of work of this academic environment is closed, aimed at disseminating the intellectual work of teachers and students of the Faculty. of Law of the Autonomous University of Bucaramanga. In the midst of the convulsive and unstable legal scenario in the country, intends to contribute to the construction of a legal thought linked to the social reality that raises from the different slopes of the opinion disturbing topics for the academic environment, seeking decantation and understanding of the phenomena while fostering controversy and the free expression of the different points of view, in development of the principles that guide this house of studies

The 13th Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the SDSS-IV Survey Mapping Nearby Galaxies at Apache Point Observatory

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) began observations in July 2014. It pursues three core programs: APOGEE-2,MaNGA, and eBOSS. In addition, eBOSS contains two major subprograms: TDSS and SPIDERS. This paper describes the first data release from SDSS-IV, Data Release 13 (DR13), which contains new data, reanalysis of existing data sets and, like all SDSS data releases, is inclusive of previously released data. DR13 makes publicly available 1390 spatially resolved integral field unit observations of nearby galaxies from MaNGA,the first data released from this survey. It includes new observations from eBOSS, completing SEQUELS. In addition to targeting galaxies and quasars, SEQUELS also targeted variability-selected objects from TDSS and X-ray selected objects from SPIDERS. DR13 includes new reductions ofthe SDSS-III BOSS data, improving the spectrophotometric calibration and redshift classification. DR13 releases new reductions of the APOGEE-1data from SDSS-III, with abundances of elements not previously included and improved stellar parameters for dwarf stars and cooler stars. For the SDSS imaging data, DR13 provides new, more robust and precise photometric calibrations. Several value-added catalogs are being released in tandem with DR13, in particular target catalogs relevant for eBOSS, TDSS, and SPIDERS, and an updated red-clump catalog for APOGEE.This paper describes the location and format of the data now publicly available, as well as providing references to the important technical papers that describe the targeting, observing, and data reduction. The SDSS website, http://www.sdss.org, provides links to the data, tutorials and examples of data access, and extensive documentation of the reduction and analysis procedures. DR13 is the first of a scheduled set that will contain new data and analyses from the planned ~6-year operations of SDSS-IV.PostprintPeer reviewe

Sloan Digital Sky Survey IV: mapping the Milky Way, nearby galaxies, and the distant universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median ). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July

Sloan Digital Sky Survey IV: Mapping the Milky Way, Nearby Galaxies, and the Distant Universe

We describe the Sloan Digital Sky Survey IV (SDSS-IV), a project encompassing three major spectroscopic programs. The Apache Point Observatory Galactic Evolution Experiment 2 (APOGEE-2) is observing hundreds of thousands of Milky Way stars at high resolution and high signal-to-noise ratios in the near-infrared. The Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey is obtaining spatially resolved spectroscopy for thousands of nearby galaxies (median $z\sim 0.03$). The extended Baryon Oscillation Spectroscopic Survey (eBOSS) is mapping the galaxy, quasar, and neutral gas distributions between $z\sim 0.6$ and 3.5 to constrain cosmology using baryon acoustic oscillations, redshift space distortions, and the shape of the power spectrum. Within eBOSS, we are conducting two major subprograms: the SPectroscopic IDentification of eROSITA Sources (SPIDERS), investigating X-ray AGNs and galaxies in X-ray clusters, and the Time Domain Spectroscopic Survey (TDSS), obtaining spectra of variable sources. All programs use the 2.5 m Sloan Foundation Telescope at the Apache Point Observatory; observations there began in Summer 2014. APOGEE-2 also operates a second near-infrared spectrograph at the 2.5 m du Pont Telescope at Las Campanas Observatory, with observations beginning in early 2017. Observations at both facilities are scheduled to continue through 2020. In keeping with previous SDSS policy, SDSS-IV provides regularly scheduled public data releases; the first one, Data Release 13, was made available in 2016 July