Digital resources such as smart applications reviews and online feedback information are important sources to seek customers’ feedback and input. This paper aims to help government entities gain insights on the needs and expectations of their customers. Towards this end, we propose an aspect-based sentiment analysis hybrid approach that integrates domain lexicons and rules to analyse the entities smart apps reviews. The proposed model aims to extract the important aspects from the reviews and classify the corresponding sentiments. This approach adopts language processing techniques, rules, and lexicons to address several sentiment analysis challenges, and produce summarized results. According to the reported results, the aspect extraction accuracy improves significantly when the implicit aspects are considered. Also, the integrated classification model outperforms the lexicon-based baseline and the other rules combinations by 5% in terms of Accuracy on average. Also, when using the same dataset, the proposed approach outperforms machine learning approaches that uses support vector machine (SVM). However, using these lexicons and rules as input features to the SVM model has achieved higher accuracy than other SVM models.

Crowd evacuation in emergencies may lead to fatalities if the evacuation plans were not test-ed and evaluated. Traditionally, evacuation drills have been, and still are, being used to assess evacuation plans. However, in recent years the simulation of evacuation plans during emergencies has emerged as a strong alternative that is cost effective and potentially more accurate. Agent-Based Simulation (ABS) is the preferred type of simulation for evacuation scenarios, due to its ability to model individual decision-making and social behaviour. In this paper we conduct meta-analysis of eighty-one peer-reviewed papers published between 2009 and 2019 that used ABS to model pedestrian evacuation. Our analysis assesses the current state-of-art and identifies opportunities for improvement. We identify seven dimensions over which the surveyed papers agree or differ. The dimensions include purpose of the simulation, type of emergency and environment considerations, type and scale of evacuated space, simulation software used, agents’ character-istics and behaviour, support of evacuation policies, and analysis and validation. We conduct meta-analysis of the surveyed papers along the identified dimensions. One of the main findings of our analysis is the lack of a standardized validation methodology for ABS of emergency evacuation.

The integration of technology in education is essential for enhancing learning experiences and preparing students for a technology-driven world. However, many teachers lack the necessary skills and confidence to effectively incorporate technology into their classroom practices. This paper investigates the impact of technology-related professional development (PD) on teachers' self-reported technology competencies and their application of technology in classroom practices, addressing the critical need for effective PD programs that can bridge this gap. The study involved the development and administration of a self-reported Information and Communication Technology (ICT) competencies survey, the observation of classroom practices using a custom-developed observation tool, and the implementation of a comprehensive PD program followed by a subsequent reassessment using the same instruments. The findings demonstrate significant improvements in teachers' self-reported competencies and classroom practices following the PD sessions. The validated self-rating technology skills survey and classroom observation tool proved to be reliable and effective measures for assessing teachers' ICT competencies and the integration of technology in teaching. The study underscores the necessity of well-designed PD programs that incorporate active learning, collaboration, and sustained support to enhance teachers' technology integration skills.