Minería de opinión: un análisis en tiempo real de tweets para Zacatecas

The Twitter social network has become an excellent tool to know in real time the opinions that users express on a great variety of topics. The formal analysis of the texts in tweets is the subject of numerous studies, derived from them, the emergence of emerging technologies such as Opinion Mining, where sentiment analysis is inert; which refers to the use of natural language processing to identify and extract subjective information from the texts [1]. By definition, sentiment analysis seeks to generate automatic tools capable of extracting subjective information to create structured and actionable knowledge [2]. In other words, this is a bulk document classification task automatically, depending on the positive or negative connotation of the language used in the document. This work focuses on performing sentiment analysis of Twitter comments georeferenced to the city of Zacatecas, such as a ranking of tweets tagged with their polarity, cleaning up the text of tweets, as well as extracting characteristics typical of the text don positive and negative polarity, using machine learning especially supervised learning algorithms to perform the classification. From the algorithms used it was obtained that Random Forest had a better accuracy by having 0.977, then Decision Trees with 0.9735 and SVM with 0.9551. With the results obtained it can be concluded that the improvement of the accuracy was achieved thanks to the features that were added, in addition it is shown that the supervised learning algorithms are classifying the tweets appropriately given the results obtained.La red social Twitter se ha convertido en una excelente herramienta para conocer en tiempo real las opiniones que los usuarios expresan sobre una gran variedad de temas. El análisis formal de los textos en los tweets es objeto de numerosos estudios, derivado de ellos, se ha impulsado la aparición de tecnologías emergentes como la Minería de Opinión, donde está inerte el análisis de sentimientos; el cual se refiere al uso del procesamiento del lenguaje natural para identificar y extraer información subjetiva de los textos [1]. Por definición, el análisis de sentimientos busca generar herramientas automáticas capaces de extraer información subjetiva para crear conocimiento estructurado y procesable [2]. En otras palabras, se trata de una tarea de clasificación masiva de documentos de manera automática, en función de la connotación positiva o negativa del lenguaje utilizado en el documento. Este trabajo se centra en realizar análisis de sentimientos de comentarios de Twitter georreferenciado a la ciudad de Zacatecas, como una clasificación de los tweets etiquetados con su polaridad, realizando una limpieza del texto de los tweets, así como la extracción de características propias del texto como polaridad positiva y negativa, utilizando el machine learning en especial los algoritmos de aprendizaje supervisado para realizar la clasificación. De los algoritmos utilizados se obtuvo que Random Forest tuvo un mejor accuracy al tener 0.977, después Arboles de Decisión con 0.9735 y SVM con 0.9551. Con los resultados obtenidos se puede concluir que la mejora del accuracy se logró gracias a las características que se fueron agregando, además se demuestra que los algoritmos de aprendizaje supervisado están clasificando los tweets de manera adecuada dado los resultados obtenidos

Click chemistry of multi-walled carbon nanotubes-G-1,3-diazido-2-isopropanol with alkyne groups

The click chemistry was employed on oxidized multiwall carbon nanotubes for their functionalization with 1,3-diazido-2-isopropanol (2N3OH). Phenylacetylene and propargylamine are used as alkyne groups, catalyzed with copper iodide (I). The chemical and structural characterization are described starting from the Raman and infrared spectroscopy as well as the realization of an elemental combustion analysis, transmission electron microscopy and nuclear magnetic resonance (NMR)CONACY

Acoustic individual identification in birds based on the band-limited phase-only correlation function

A new technique based on the Band-Limited Phase-Only Correlation (BLPOC) function to deal with acoustic individual identification is proposed in this paper. This is a biometric technique suitable for limited data individual bird identification. The main advantage of this new technique, in contrast to traditional algorithms where the use of large-scale datasets is assumed, is its ability to identify individuals by the use of only two samples from the bird species. The proposed technique has two variants (depending on the method used to analyze and extract the bird vocalization from records): automatic individual verification algorithm and semi-automatic individual verification algorithm. The evaluation of the automatic algorithm shows an average precision that is over 80% for the identification comparatives. It is shown that the efficiencies of the algorithms depend on the complexity of the vocalizations

Chlorophyll fluorescence emission of tomato plants as a response to pulsed light based LEDs

The effects of pulsed light based-LEDs at eleven frequencies (0.1, 1, 10, 50, 100, 500 Hz, 1, 5, 10, 50 and 100 kHz) programmed at 50 % duty cycle were analyzed, obtaining important parameters of the fluorescence emission of chlorophyll such as: maximum fluorescence (Fm0), minimum fluorescence, the fluorescence emission in steady state, maximum efficiency of PSII (Fv0/Fm0), the fraction of PSII centers that are open, photochemical quenching, nonphotochemical quenching (NPQ), quantum efficiency of photosystem II (UPSII), electron transport rate (ETR) and quantum yield of CO2 assimilation (/CO2). For the study and validation of the results obtained in the experiments, the analysis of variance (ANOVA) was applied 0for each parameter with confidence intervals of 95 %. The results show that the frequencies of pulsed light had positive and negative effects on the fluorescence parameters with respect to the control treatment (continuous light). The frequencies that generated the best performance of Fv0/Fm0, NPQ, UPSII, ETR, /CO2 in tomato plants were 0.1, 1, 100 Hz, and 1 kHz. The increase obtained in these parameters can represent an optimal growth and productivity conditions for optimal energy consumption

An alternative approach to the tomographic reconstruction of smooth refractive index distributions

Continuous, mathematically smooth Phase Objects with radial symmetry are reconstructed from cross sections of their refractive index distribution by a novel method, consisting of a linear combination of Gaussian basis functions, whose technical details are discussed. As an application example, this approach is used to get a fast and accurate estimation of the temperature distribution of an actual soldering tip

Development of a remote sensing and control system for greenhouse applications

Real-time monitoring provides reliable, timely information of crop and soil status, important in taking decisions for crop production improvement. This work presents a real-time monitoring and control system for climatological variables in greenhouse. The system has wireless communication capabilities, which allow it to cover extensive surfaces in real-time, without extra resources. The system implementation is based on the micro controllers “PIC18F4550” and “DSPIC 30F5011”, user interface was programmed under LINUX. The proposed system performance was compared with commercial Data Loggers, readings present a linear adjustment with R2=0.9656

Development of a remote sensing and control system for greenhouse applications

Real-time monitoring provides reliable, timely information of crop and soil status, important in taking decisions for crop production improvement. This work presents a real-time monitoring and control system for climatological variables in greenhouse. The system has wireless communication capabilities, which allow it to cover extensive surfaces in real-time, without extra resources. The system implementation is based on the micro controllers “PIC18F4550” and “DSPIC 30F5011”, user interface was programmed under LINUX. The proposed system performance was compared with commercial Data Loggers, readings present a linear adjustment with R2=0.9656