Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

El gasto público como herramienta primordial de un Gobierno en busca de satisfacer necesidades sociales es el aditamento necesario para generar valor público, mismo que confluye en aspectos de gobernanza y gobernabilidad para conseguir los objetivos óptimos en una sociedad. En tal virtud, la disciplina fiscal ha sido enunciada durante mucho tiempo en varias de las economías emergentes y en desarrollo, tales reglas, en lugar de ser neutrales o de compensar los efectos negativos del ciclo económico, han dado lugar a un aumento ciertamente desmedido del gasto en función de los ingresos, por lo que su diseño e implementación deben responder aspectos estructurales y al entorno de un país, lo que conlleva a decir que tener reglas fiscales no es la panacea universal, sino que depende de las particularidades de cada país.

El propósito es realizar un análisis reflexivo sobre la “autonomía universitaria responsable” determinada en la ley, para establecer en qué medida afecta a la autonomía universitaria real, ya que esta nueva forma de  autonomía descrita en las normas, estaría sujeta a juicios de valor. Para esto se reflexionó respecto a: el concepto de autonomía universitaria y  la legislación de la República del Ecuador en su parte pertinente;  la reflexión nos permitió determinar que la Constitución y sus normas son ambiguas, afectando a la concepción de autonomía universitaria real, al permitir juicios de valor.  Concluyendo que la autonomía universitaria resulta vulnerada con la aplicación de esta legislación.

En el marco de la Teoría de las Obligaciones, se ha desarrollado el concepto, caracteres, elementos de las obligaciones y sus fuentes; y, en el orden metodológico se los ha correlacionado  con la doctrina y diversas normas jurídicas establecidas en el Libro Cuarto del Código Civil ecuatoriano, situación que ha permitido identificar limitaciones en la legislación civil ecuatoriana respecto a la confusión de las categorías jurídicas obligación, contrato y convención. En materia de las fuentes de las obligaciones: contrato, cuasicontrato, delito, cuasidelito y la ley, luego de caracterizar a cada una de ellas, se han identificado desde del enfoque doctrinario dos vertientes centrales: la ley y el contrato.

El presente artículo de ensayo tiene como propósito reflexionar y analizar el poder constituyente, que no es otra cosa que, la potestad o facultad de elaborar o reformar la Constitución de un Estado, para ello, utilizaremos principalmente los métodos analítico, hermenéutico e histórico. Al finalizar el presente trabajo investigativo, el lector podrá tener una visión clara respecto de los mecanismos que el Derecho Constitucional y sus doctrinarios han desarrollado para la elaboración o reforma de una Carta Política, esto es, el poder constituyente originario y derivado.

The world beef market is in full growth and with unsatisfied demands and prices up and these depend very much on their quality when arriving at the final consumer, while the national market, our country also has a future potential in the meat industry. In the present investigation is to evaluate the sensory characteristics of color and texture by means of the presence of a bovine meat sample in the system whose final result will be the acceptance or negation of its organoleptic quality. The system is constituted by a transport band in charge of taking the sample to a capsule where both the Lighting System (LS) and the Computer Vision System (CVS) are located, and when leaving there it will be automatically classified by an actuator, guaranteeing less manipulation and estimation of time by human intervention throughout the process while providing greater security to the final consumer about the meat that is entering their home.  

One of the most relevant problems in Bioinformaticsand Computational Biology is the search and reconstruction ofthe most accurate phylogenetic tree that explains, as exactly aspossible, the evolutionary relationships among species from agiven dataset. Different criteria have been employed to evaluatethe accuracy of evolutionary hypothesis in order to guide a searchalgorithm towards the best tree. However, these criteria may leadto distinct phylogenies, which are often conflicting among them.Therefore, a multi-objective approach can be useful. In this work,we present a phylogenetic adaptation of a multiobjective variablemesh optimization algorithm for inferring phylogenies, to tacklethe phylogenetic inference problem according to two optimalitycriteria: maximum parsimony and maximum likelihood. Theaim of this approach is to propose a complementary view ofphylogenetics in order to generate a set of trade-off phylogenetictopologies that represent a consensus between both criteria.Experiments on four real nucleotide datasets show that ourproposal can achieve promising results, under both multiobjectiveand biological approaches, with regard to other classical andrecent multiobjective metaheuristics from the state-of-the-art.  

Built equipment has a 3D scanner with a principle in laser triangulation, integrated to a 3D printer based on fused deposition modeling. The same printer hardware has been used to integrate the peripherals of the scanner: lasers and rotating platform, the camera connects directly to a computer that has software developed to handle the functionalities of the scanner, which obtains a point cloud, and due to integration of postprocessing (surface reconstruction) and laminate tools (g-code), a file is automatically generated ready for interpretation in the 3D printer, closing the reproduction cycle of a model. Due to its low cost and open source, this prototype made accessible performing reverse engineer of an object by means of digital acquisition (3D scanner) and allows its total reproduction (3D printing).  

In the process of oil extraction, specifically in therefinement and industrialization of hydrocarbons, as is known,multiple wastes are highly polluting for the soil, water and air.In this work, the risk level of these wastes in affected areasis estimated thanks to the application of statistical models inthe field of functional data analysis. These models have beenimplemented in a statistical software called RStudio that allowsan early measurement and evaluation of the level of risk by usingsemiquantitative and quantitative methods. This measurement iscarried out by the staff of PETROECUADOR close to the affectedplace. It was used the laser-induced fluorescence technique (LIF).The data obtained using this technique was used to adjust thefollowing models: Generalized Functional Linear Model (MLFG),which makes it possible to classify the spectrum generated intwo pollution levels: Low and High. Functional linear regressionmodel with scalar response and functional explanatory variablewith the aim of directly estimating the percentage of contaminationlevel. With these results it is verified that the shape ofthe laser fluorescence spectrum is highly related to the gasolinecontent in the sample.  

Taking into account the chaotic characteristic of gas production within power transformers, a Least Square Support Vector Machine (LSSVM) model is implemented to forecast dissolved gas content based on historical chromatography samples. Additionally, an extending approach is developed with a correlation between oil temperature and Dissolved Gas Analysis (DGA), where a multi-input LSSVM is trained with the utilization of DGA and temperature datasets. The obtained DGA prediction from the extending model illustrates more accurate results, and the previous algorithm uncertainties are reduced.A favourable correlation between hydrogen, methane, ethane, ethylene, and acetylene and oil temperature is achieved by the application of the proposed multi-input model.  

In this research work, the results of applying DeepLearning prediction models to identify the digit of an image,that contains a handwritten number of the MNIST database, arepresented. This set of dataset was acquired from the competitionof Kaggle: Digit Recognizer. The following process was applied:First, image preprocessing techniques were used, which focuson obtaining a pretty clear image and to reduce the size ofthe same, these objectives that are achieved with Otsu Method,transformed from Haar Wavelet and the Principal ComponentAnalysis (PCA), thus obtaining as a result, one set of new datasetto be evaluated. Second, the Deep Learning MxNET and H2omodels, which were executed in the statistical language R, wereapplied to these datasets obtained, this way, several predictionswere acquired. Finally, the best obtained predictions in theexperiment were sent to the Digit Recognizer competition, andthe results of this evaluation scored 99,129% of prediction.