Unit Root Model Selection

Some limit properties for information based model selection criteria are given in the context of unit root evaluation and various assumptions about initial conditions. Allowing for a nonparametric short memory component, standard information criteria are shown to be weakly consistent for a unit root provided the penalty coefficient C_n -> infinity and C_n/n -> 0 as n -> infinity. Strong consistency holds when C_n/(loglog n)^3 -> infinity under conventional assumptions on initial conditions and under a slightly stronger condition when initial conditions are infinitely distant in the unit root model. The limit distribution of the AIC criterion is obtained.AIC, Consistency, Model selection, Nonparametric, Unit root

Investigating Retrieval Method Selection with Axiomatic Features

We consider algorithm selection in the context of ad-hoc information retrieval. Given a query and a pair of retrieval methods, we propose a meta-learner that predicts how to combine the methods' relevance scores into an overall relevance score. Inspired by neural models' different properties with regard to IR axioms, these predictions are based on features that quantify axiom-related properties of the query and its top ranked documents. We conduct an evaluation on TREC Web Track data and find that the meta-learner often significantly improves over the individual methods. Finally, we conduct feature and query weight analyses to investigate the meta-learner's behavior

A multicriteria decision model for the selection of information system for a logistics company using MMASSI/TI

The aim of this work is to apply a methodology of decision support based on a multi-criteria decision analyses (MCDA), model that allows the evaluation and selection of an information system in a Logistics context. We carried out a literature review on supply chain management, logistics and decision theory to support all the practical work. A multi-criteria methodology for decision making support – Multi-criteria Methodology for the Assessment and Selection of Information Systems / Information Technologies (MMASSI / IT) based on logistics processes was applied during the MCDA, supported by a computer application. The ranking of the information systems best suited the decisional context was obtained and its sensitivity and robustness analyses performed.info:eu-repo/semantics/publishedVersio

A Method for Evaluating End-User Development Technologies

End-user development (EUD) is a strategy that can reduce a considerable amount of business demand on IT departments. Empowering the end-user in the context of software development is only possible through technologies that allow them to manipulate data and information without the need for deep programming knowledge. The successful selection of appropriate tools and technologies is highly dependent on the context in which the end-user is embedded. End-users should be a central piece in any software package evaluation, being key in the evaluation process in the end-user development context. However, little research has empirically examined software package evaluation criteria and techniques in general, and in the end-user development context in particular. This paper aims to provide a method for technology evaluation in the context of end-user development and to present the evaluation of two platforms. We conclude our study proposing a set of suggestions for future research

REDUCCIÓN DEL COSTE COMPUTACIONAL DE LA INFERENCIA DE CONTEXTO BAYESIANA MEDIANTE EL USO DE RANGOS DE VALORES DINÁMICOS

This paper shows how to reduce evaluation time for context inference. Probabilistic Context Inference has proven to be more powerful and better adapted to the challenges of the physical reality with uncertain or missing information. As the inference complexity is very high, the complexity of the to be evaluated rule (representing a share of the real world) should be reduced as far as possible. Therefore we present an approach to select only relevant values of context types and to adapt this selection during its usage time. In an evaluation we show that with only a few evaluations of the reduced inference rules the reduction costs will have amortized and the system brings significant benefit to context aware computing

Feature selection for microarray gene expression data using simulated annealing guided by the multivariate joint entropy

In this work a new way to calculate the multivariate joint entropy is presented. This measure is the basis for a fast information-theoretic based evaluation of gene relevance in a Microarray Gene Expression data context. Its low complexity is based on the reuse of previous computations to calculate current feature relevance. The mu-TAFS algorithm --named as such to differentiate it from previous TAFS algorithms-- implements a simulated annealing technique specially designed for feature subset selection. The algorithm is applied to the maximization of gene subset relevance in several public-domain microarray data sets. The experimental results show a notoriously high classification performance and low size subsets formed by biologically meaningful genes.Postprint (published version

Material Considerations in Architectural Design: A Study of the Aspects Identified by Architects for Selecting Materials

Material selection in architecture is not only about choosing the strongest, cheapest, or most obvious materials available. Architects also choose warm, formal, functional, or local materials for buildings. And the material options are not limited by only these considerations. The material selection process is a complex process that is influenced and determined by numerous preconditions, decisions and considerations. The current material selection tools, however, focus mainly on the technical aspects of materials. In order to make well-considered and justifiable material choices, architects have a need for information on the whole spectrum of aspects considered during the design and selection process. Earlier work presented a framework, based on a literature study and the analysis of in-depth interviews, in which the different attributes of materials that contribute to a design project were identified and organized. To refine this framework and make it available for architects during the material selection process, a group of architects was selected and assembled into a focus group. This study presents how the focus group identified, classified and commented on the considerations that are made by architects while selecting materials for a project. The evaluation of the collected data, and the discussion within the group, permitted the formulation of comments and resulted in a revised framework of material considerations, useful during the design and selection process of a material. Material properties (1), Experience (2), Manufacturing process (3), and Context (4) were identified as the different elements that are related to the material selection process. The four groups are presented here in detail. Keywords: Material Selection; Design Aspects; Architectural Experience; Material Attributes; Focus Group; Design Process</p

Effects of alcohol and gender on social information processing of sexual aggression

The purpose of this study was to examine the effects of alcohol intoxication and gender on social information processing in the context of a sexual coercion scenario. It was hypothesized that alcohol intoxication would affect social information processing patterns related to sexually aggressive behavior. One hundred and three participants were recruited for this study, 48 female and 55 male. These participants were grouped into either a high BAC condition or a low BAC condition using a BAC cutoff of .06. Participants completed a demographics questionnaire, an alcohol quantity frequency assessment and a social information processing protocol. The social information processing protocol consisted of a written sexually coercive scenario. Participants answered questions after reading the scenario which assessed the domains of response representation, goal selection, response evaluation and response selection. Multivariate Analysis of Variance (MANOVA) was used to test the 3 hypotheses for both men and women. No significant results were found for women for any areas of social information processing. Significant results were found in the areas of goal selection and response evaluation for men. These results point to the utility of using social information processing models in the study of sexual aggression