No abstract

No abstract

Background The aim of this study is to validate the Arabic version of the Basic Psychological Need Satisfaction and Frustration Scale (BPNSFS), and to investigate the extent of its invariance across five Arab countries and gender. Methods A back-translated version of the BPNSFS, the second version of the Beck Depression Inventory (BDI-II), and the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS) were administered to a sample consisting of 1082 undergraduate students affiliated with universities in five Arab countries (487 males and 595 females: Mage = 20.04 ± 1.87 years). The data of the BPNSFS were examined for univariate and multivariate normality using Shapiro–Wilk tests and Mardia’s coefficient, respectively. To evaluate and compare the four models with confirmatory factor analysis (CFA), we used the following goodness-of-fit indices: the chi-square value (χ2), comparative fit index (CFI), Tucker-Lewis index (TLI), Root Mean-Square Error of Approximation (RMSEA), and Baysian Information Criterion (BIC). A multi-group CFA [Byrne in Structural equation modeling with EQS: basic concepts, applications, and programming, Routledge, Abingdon, 2013] on the BPNSFS structure to examine its invariance across the five Arab countries and across genders. Results The results of confirmatory factor analysis supported the generalizability of the BPNSFS’s six-factor model to the five Arab countries. The relationships between the six psychological needs satisfaction and frustrations and both mental health and symptoms of depression provide additional evidence on the construct validity of the BPNSFS through cross cultural data. The findings of BPNSFS’s measurement invariance across males and females and across the five Arab countries help ensure that the latent means are comparable across these different groups. Conclusions The study concluded that the Arabic version of the BPNSFS which measures satisfaction and frustration of the three basic needs (autonomy, competency, and relatedness) is proved to be invariant across the five Arab countries and gender and can be used to compare the basic psychological needs in the Arab context.

We propose a new model for speaker naming in movies that leverages visual, textual, and acoustic modalities in an unified optimization framework. To evaluate the performance of our model, we introduce a new dataset consisting of six episodes of the Big Bang Theory TV show and eighteen full movies covering different genres. Our experiments show that our multimodal model significantly outperforms several competitive baselines on the average weighted F-score metric. To demonstrate the effectiveness of our framework, we design an end-to-end memory network model that leverages our speaker naming model and achieves state-of-the-art results on the subtitles task of the MovieQA 2017 Challenge.

We introduce an interactive interface that aims to help English as a Second Language (ESL) students overcome language related hindrances while reading a text. The interface allows the user to find supplementary information on selected difficult words. The interface is empowered by our lexical substitution engine that provides context-based synonyms for difficult words. We also provide a practical solution for a real-world usage scenario. We demonstrate using the lexical substitution engine -as a browser extension that can annotate and disambiguate difficult words on any webpage.