Scalar gain interpretation of large order filters

A technique is developed which demonstrates how to interpret a large fully-populated filter gain matrix as a set of scalar gains. The inverse problem is also solved, namely, how to develop a large-order filter gain matrix from a specified set of scalar gains. Examples are given to illustrate the method

Similarity Structure Analysis and Structural Equation Modeling in Studying Latent Structures: An Application to the Attitudes towards Portuguese Language Questionnaire

Several international studies such as PISA and PILRS (Progress in International Reading Literacy Study), have stressed the importance of positive attitudes and behaviours as facilitators of individuals reading literacy during the school years and throughout their lives. Considering that there are not available instruments for assessing attitudes Towards Portuguese Language, it was proposed the development of the Attitudes towards Portuguese Language Questionnaire – ATPLQ (Questionário de Atitudes Face à Língua Portuguesa: QAFLP, Neto et al., 2011; Rebelo, 2012). The questionnaire has 22 Likert-type items, with four levels of response (Strongly Disagree, Disagree, Agree, Strongly Agree), spread, through exploratory factor analysis (EFA), over three attitudinal dimensions: Behavioural, Affective, and Motivational.In this study we aimed to analyse the ATPLQ’s latent structure with a pooled sample data of 1441 participants, applying similarity structure analysis (SSA) and confirmatory factor analysis of ordinal data (CFA). The SSA was carried out with Hudap in order to identify the structural properties of the questionnaire and to assess its adequacy in a Portuguese population. The CFA was carried out with LISREL in order to assure structural validity, i.e., accounting for factorial validity, but also for factors’ convergent and discriminant validity, and composite reliability. These psychometric features allowed the comparison of both the EFA derived model and the SSA derived model. We justify the selection of the SSA’s model, and we discuss the similarities between the results generated by SSA and LISREL procedures, highlighting their use in modeling constructs with ordinal indicators

Mobile apps usage and dynamic capabilities: A structural equation model of SMEs in Lagos, Nigeria.

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Significant knowledge exists regarding the application of dynamic capability (DC) frameworks in large firms, but their impact on smaller organisations is yet to be fully researched. This study surveyed 1162 small and medium sized enterprises (SMEs) in Lagos in an effort to understand how SMEs in developing country contexts use mobile apps to enhance their businesses through DCs. Through the use of the covariance-based structural equation modelling (SEM) technique, the study explored the fitness of a conceptual formative model for SMEs. The model assembled 7 latent variables namely: mobile app usage, adaptive capability, absorptive capability, innovative capability, opportunity sensing ability, opportunity shaping ability and opportunity seizing ability. Subsequently, 15 hypotheses aimed at testing the relationships between the latent variables were developed and tested. The findings revealed that mobile app usage increases the adaptive, absorptive and innovative capabilities of SMEs. Absorptive capabilities help SMEs to maximise opportunities, while innovative capabilities negatively influence SMEs’ tendency to maximise opportunities. The results failed to establish a direct relationship between mobile app usage and SMEs’ ability to maximise opportunities. The research outcomes indicate that SMEs in Lagos respond to opportunities innovatively but they seldom exhibit innovation in order to create opportunities. The heterogeneous nature of SMEs complicates any clear-cut narrative as to how SMEs in Lagos should employ mobile apps to create and maximise opportunities. However, mobile apps could induce innovation and, as such, impact significantly when developed and applied to the contextual requirements of SMEs. The research revealed the untapped potential of SMEs’ mobile app usage in Lagos

Design of general-purpose sampling strategies for geometric shape measurement

Quality inspection is a preliminary step for different further analyses (process monitoring, control and optimisation) and requires one to select a measuring strategy, i.e., number and location of measurement points. This phase of data gathering usually impacts on inspection times and costs (via sample size) but it also affects the performance of the following tasks (process monitoring, control and optimisation). While most of the approaches for sampling design are specifically presented with reference to a target application (namely, monitoring, control or optimisation), this paper presents a general-purpose procedure, where the number and location of measurement points are selected in order to retain most of the information related to the feature under study. The procedure is based on principal component analysis and its application is shown with reference to a real case study concerning the left front window of a car. A different approach based on multidimensional scaling is further applied as validation tool, in order to show the effectiveness of the PCA solution

URBAN PLANNING WITH THE AID OF FACTOR ANALYSIS APPROACH: THE CASE OF ISFAHAN MUNICIPALITY

Nowadays municipalities play an important role in offering urban services to the citizens. To investigate performance of regional municipalities, different data on living situation must be considered. Thus, we face a multivariate analysis. In this research regarding capabilities of "Factor Analysis" technique in the area of multivariate analysis, we used this technique to construct latent factors for comparison of different districts of a city. Along these lines we examined the real case of Isfahan municipality. Isfahan is a major city in Iran. The results of our analysis show that instead of evaluating different variables in each region we can concentrate on two simple and informative criteria representing common welfare situation and development situation in each region. The proposed approach shows which factors are more important for each region of the city and how different regional municipalities can apply cost effective policies to improve their performance.Regional Municipalities, Multivariate Analysis, Factor Analysis, Isfahan.

Constraining cosmology and ionization history with combined 21 cm power spectrum and global signal measurements

Improvements in current instruments and the advent of next-generation instruments will soon push observational 21 cm cosmology into a new era, with high significance measurements of both the power spectrum and the mean ("global") signal of the 21 cm brightness temperature. In this paper we use the recently commenced Hydrogen Epoch of Reionization Array as a worked example to provide forecasts on astrophysical and cosmological parameter constraints. In doing so we improve upon previous forecasts in a number of ways. First, we provide updated forecasts using the latest best-fit cosmological parameters from the Planck satellite, exploring the impact of different Planck datasets on 21 cm experiments. We also show that despite the exquisite constraints that other probes have placed on cosmological parameters, the remaining uncertainties are still large enough to have a non-negligible impact on upcoming 21 cm data analyses. While this complicates high-precision constraints on reionization models, it provides an avenue for 21 cm reionization measurements to constrain cosmology. We additionally forecast HERA's ability to measure the ionization history using a combination of power spectrum measurements and semi-analytic simulations. Finally, we consider ways in which 21 cm global signal and power spectrum measurements can be combined, and propose a method by which power spectrum results can be used to train a compact parameterization of the global signal. This parameterization reduces the number of parameters needed to describe the global signal, increasing the likelihood of a high significance measurement.Comment: 16 pages, 8 figures. Revised to match accepted MNRAS version: expanded discussion of covariances between astrophysics and cosmology in Section 2.2, including two new figures; short discussion relating to KL modes added to Section 4; final results unchange