Generador de exámenes de test aleatorio

En este documento se detalla, la planificación y elaboración de un paquete que respeta el estándar S4 de programación en lenguaje R. El paquete consiste en una serie de métodos y clases para la generación de exámenes tipos test y soluciones a partir de un archivo xls, que hace las funciones de una base de datos. El diseño propuesto está orientado a objetos y desarrolla un conjunto de clases que representan los contenidos de una prueba de evaluación tipo test: enunciados, peguntas y respuestas. Se ha realizado una implementación sencilla de un prototipo con las funciones básicas necesarias para generar los tests. Además se ha generado la documentación necesaria para crear el paquete, esto significa que cada método tiene una página de ayuda, que se podrá consultar desde un terminal con R, dicha documentación incluye ejemplos de ejecución de cada método.---ABSTRACT---In this document is detailed the elaboration and development of a package that meets the standard S4 of programming language R. This package consists of a group of methods and classes used for the generation of test exams and their solutions starting from a xls format file wich plays the role of a data base at the same time. These classes have been grouped in a way that the user could have a complete and easy vision of them. This division has been done by using data storage and functions whose tasks are more or less the same. Furthermore, the necessary documentation to create this package has also been generated, that means that every method has a help page wich can be called from a R terminal if necessary. This documentation has examples of the execution of every method.

Generation of human computational models with machine learning

Services in smart environments pursue to increase the quality of people?s lives. The most important issues when developing this kind of environments is testing and validating such services. These tasks usually imply high costs and annoying or unfeasible real-world testing. In such cases, artificial societies may be used to simulate the smart environment (i.e. physical environment, equipment and humans). With this aim, the CHROMUBE methodology guides test engineers when modeling human beings. Such models reproduce behaviors which are highly similar to the real ones. Originally, these models are based on automata whose transitions are governed by random variables. Automaton?s structure and the probability distribution functions of each random variable are determined by a manual test and error process. In this paper, it is presented an alternative extension of this methodology which avoids the said manual process. It is based on learning human behavior patterns automatically from sensor data by using machine learning techniques. The presented approach has been tested on a real scenario, where this extension has given highly accurate human behavior models,

Implications of data-intensive applications for next generation mobile networks

Lately, the mobile data market has moved into a growth stage triggered by two facts: affordability of mobile broadband, and availability of data-friendly devices. At this stage, market growth is no longer dependent on push strategies from suppliers; on the contrary, demand is now driving the market. However, it will not be easy for mobile operating companies to cope up with the demand to come in the near future. The infrastructure that is needed to support corresponding demand is far from completion. Operators are forced to make heavy investments to upgrade and expand their networks. To decide how to handle the present and upcoming demand, they need to identify and understand the characteristics of the scenarios they face. This is precisely the aim of this article, which provides figures on the consequences for mobile infrastructures of a generalised mobile media uptake. Data from the Spanish mobile deployment case have been used to arrive at practical figures and illustration of results, but the conclusions are easily extended to other countries and regions

Spontaneous mutations recovered as mosaics in the mouse specific-locus test

The specific-locus test (SLT) detects new mutants among mice heterozygous for seven recessive visible markers. Spontaneous mutations can be manifested not only as singleton whole-body mutants in controls (for which we report new data), but as mosaics—either visible (manifesting mottled coat color) in the scored generation (G2) or masked, among the wild-type parental generation (G1). Masked G1 mosaics reveal themselves by producing clusters of whole-body mutants in G2. We provide evidence that most, if not all, mosaics detected in the SLT (both radiation and control progenies) result from a single-strand spontaneous mutation subsequent to the last premeiotic mitosis and before the first postmeiotic one of a parental genome—the “perigametic interval.” Such events in the genomes of the G1 and G0 result, respectively, in visible and masked 50:50 mosaics. Per cell cycle, the spontaneous mutation rate in the perigametic interval is much higher than that in pregamete mitotic divisions. A clearly different locus spectrum further supports the hypothesis of different origin, and casts further doubt on the validity of the doubling-dose risk-estimation method. Because mosaics cannot have arisen in mitotic germ cells, and are not induced by radiation exposure in the perigametic interval, they should not be included in calculations of radiation-induced germ-line mutation rates. For per-generation calculations, inclusion of mosaics yields a spontaneous frequency 1.7 times that calculated from singletons alone for mutations contributed by males; including both sexes, the multiple is 2.2.

Verb generation in patients with focal frontal lesions: A neuropsychological test of neuroimaging findings

What are the neural bases of semantic memory? Traditional beliefs that the temporal lobes subserve the retrieval of semantic knowledge, arising from lesion studies, have been recently called into question by functional neuroimaging studies finding correlations between semantic retrieval and activity in left prefrontal cortex. Has neuroimaging taught us something new about the neural bases of cognition that older methods could not reveal or has it merely identified brain activity that is correlated with but not causally related to the process of semantic retrieval? We examined the ability of patients with focal frontal lesions to perform a task commonly used in neuroimaging experiments, the generation of semantically appropriate action words for concrete nouns, and found evidence of the necessity of the left inferior frontal gyrus for certain components of the verb generation task. Notably, these components did not include semantic retrieval per se.

A Simple RVoG Test for PolInSAR Data

In this paper, we present a simple algorithm for assessing the validity of the RVoG model for PolInSAR-based inversion techniques. This approach makes use of two important features characterizing a homogeneous random volume over a ground surface, i.e., the independence on polarization states of wave propagation through the volume and the structure of the polarimetric interferometric coherency matrix. These two features have led to two different methods proposed in the literature for retrieving the topographic phase within natural covers, i.e., the well-known line fitting procedure and the observation of the (1, 2) element of the polarimetric interferometric coherency matrix. We show that differences between outputs from both approaches can be interpreted in terms of the PolInSAR modeling based on the Freeman-Durden concept, and this leads to the definition of a RVoG/non-RVoG test. The algorithm is tested with both indoor and airborne data over agricultural and tropical forest areas.

A Finite Element Numerical Algorithm for Modelling and Data Fitting in Complex Systems

Numerical modelling methodologies are important by their application to engineering and scientific problems, because there are processes where analytical mathematical expressions cannot be obtained to model them. When the only available information is a set of experimental values for the variables that determine the state of the system, the modelling problem is equivalent to determining the hyper-surface that best fits the data. This paper presents a methodology based on the Galerkin formulation of the finite elements method to obtain representations of relationships that are defined a priori, between a set of variables: y = z(x1, x2,...., xd). These representations are generated from the values of the variables in the experimental data. The approximation, piecewise, is an element of a Sobolev space and has derivatives defined in a general sense into this space. The using of this approach results in the need of inverting a linear system with a structure that allows a fast solver algorithm. The algorithm can be used in a variety of fields, being a multidisciplinary tool. The validity of the methodology is studied considering two real applications: a problem in hydrodynamics and a problem of engineering related to fluids, heat and transport in an energy generation plant. Also a test of the predictive capacity of the methodology is performed using a cross-validation method.

Boston, Massachusetts Region LIDAR First Return Elevation Data, 2002

LIDAR (LIght Detection And Ranging) first return elevation data of the Boston, Massachusetts region from MassGIS at 1-meter resolution. This LIDAR data was captured in Spring 2002. LIDAR first return data (which shows the highest ground features, e.g. tree canopy, buildings etc.) can be used to produce a digital terrain model of the Earth's surface. This dataset consists of 74 First Return DEM tiles. The tiles are 4km by 4km areas corresponding with the MassGIS orthoimage index. This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). The area of coverage corresponds to the following MassGIS orthophoto quads covering the Boston region (MassGIS orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 233906, 233910, 237890, 237894, 237898, 237902, 237906, 237910, 241890, 241894, 241898, 241902, 245898, 245902). The geographic extent of this dataset is the same as that of the MassGIS dataset: Boston, Massachusetts Region 1:5,000 Color Ortho Imagery (1/2-meter Resolution), 2001 and was used to produce the MassGIS dataset: Boston, Massachusetts, 2-Dimensional Building Footprints with Roof Height Data (from LIDAR data), 2002 [see cross references].

Boston, Massachusetts, 2-Dimensional Building Footprints with Height Data (from LIDAR data), 2002

This dataset consists of 2D footprints of the buildings in the metropolitan Boston area, based on tiles in the orthoimage index (orthophoto quad ID: 229890, 229894, 229898, 229902, 233886, 233890, 233894, 233898, 233902, 237890, 237894, 237898, 237902, 241890, 241894, 241898, 241902, 245898, 245902). This data set was collected using 3Di's Digital Airborne Topographic Imaging System II (DATIS II). Roof height and footprint elevation attributes (derived from 1-meter resolution LIDAR (LIght Detection And Ranging) data) are included as part of each building feature. This data can be combined with other datasets to create 3D representations of buildings and the surrounding environment.

Stickleback F2 generation transgenerational plasticity experiment: egg and body size data

Nongenetic inheritance mechanisms such as transgenerational plasticity (TGP) can buffer populations against rapid environmental change such as ocean warming. Yet, little is known about how long these effects persist and whether they are cumulative over generations. Here, we tested for adaptive TGP in response to simulated ocean warming across parental and grandparental generations of marine sticklebacks. Grandparents were acclimated for two months during reproductive conditioning, whereas parents experienced developmental acclimation, allowing us to compare the fitness consequences of short-term vs. prolonged exposure to elevated temperature across multiple generations. We found that reproductive output of F1 adults was primarily determined by maternal developmental temperature, but carry-over effects from grandparental acclimation environments resulted in cumulative negative effects of elevated temperature on hatching success. In very early stages of growth, F2 offspring reached larger sizes in their respective paternal and grandparental environment down the paternal line, suggesting that other factors than just the paternal genome may be transferred between generations. In later growth stages, maternal and maternal granddam environments strongly influenced offspring body size, but in opposing directions, indicating that the mechanism(s) underlying the transfer of environmental information may have differed between acute and developmental acclimation experienced by the two generations. Taken together, our results suggest that the fitness consequences of parental and grandparental TGP are highly context dependent, but will play an important role in mediating some of the impacts of rapid climate change in this system.

Test site instrumentation study. Volume II: Crash 1 and Crash 2 "raw" data. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Statistical analysis of preliminary data for the safe performance curriculum driving knowledge test. Interim report.

DeKalb County School System, Decatur, Ga.

Cost analysis methodology and protocol estimates : OECD minimum pre-market data test protocols /

"EPA-560/4-81-002."

Safety compliance test for FMVSS 301-75 and Accident Investigation Division data. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.