This study fills a significant need in the literature by exploring the efficacy of wearable technologies as helpful aids for special needs students in Saudi Arabia. This 12-month quantitative study used a purposive sample of 150 kids representing a range of disability classifications. This study examines the effects of wearable technology, such as smartwatches and augmented reality goggles, on students’ concentration and performance in the classroom. Wearable technology offers great promise, as descriptive statistics show that the experimental group had better involvement and academic achievement. The experimental and control groups vary significantly in terms of academic performance and engagement, as shown by independent samples t-tests. Wearable technology’s distinct benefits are further shown by regression analysis, which shows a favorable correlation with academic achievement after the intervention. According to the results, wearable tech has great promise for inclusive education in Saudi Arabia. Strategic integration, teacher professional development, ongoing research, better accessibility, and wearable gadget customization are some of the suggestions. Stakeholders may use these recommendations as a road map to build a welcoming and technologically sophisticated classroom. This study adds to the growing body of knowledge on assistive technology, especially in Saudi Arabia, and has important implications for academics, politicians, and educators.

The carbon footprint, which measures greenhouse gas emissions, is a good environmental indicator for choosing the best sustainable mode of transportation. The available emission factors depend heavily on the calculation methodology and are hardly comparable. The minimum and maximum scenarios are one way of making the results comparable. The best sustainable passenger transport modes between Rijeka and Split were investigated and compared by calculating the minimum and maximum available emission factors. The study aims to select the best sustainable mode of transport on the chosen route and to support the decision-making process regarding the electrification of the Lika railroad, which partially connects the two cities. In the minimum scenario, ferry transport without vehicles was the best choice when the transportation time factor was not relevant, and electric rail transport when it was. In the maximum scenario, the electric train and the ferry with vehicles were equally good choices. Road transportation between cities was not competitive at all. The comparison of the carbon footprint based on minimum and maximum scenarios gives a clear insight into the ratio of greenhouse gas emissions from vehicles in passenger transport. It supports the electrification of the Lika railroad as the best sustainable transport solution on the route studied.

The purpose of this research is to deeply examine the factors that support and hinder green economic growth in South Papua, with a specific focus on increasing awareness and capacity among local communities, developing sustainable infrastructure, and adopting clean technologies. This research utilizes a case study approach to uncover the dynamics and elements supporting the development of green economy in South Papua, particularly in Merauke Regency. Through surveys, in-depth interviews, and document analysis, data were gathered from various stakeholders, including government, communities, and the private sector. Sampling was done using purposive sampling method, ensuring the inclusion of respondents relevant to the research topic to provide a holistic understanding of the factors influencing green economy in the region. The research reveals that in Merauke Regency, the understanding of the concept of green economy among the community is still limited, highlighting the need for broader education and socialization. Factors such as government support, infrastructure availability, and community participation play a key role in driving green economic growth. However, challenges such as resource limitations and differences in perceptions among stakeholders highlight the complexity in implementing green economy. Therefore, holistic and collaborative policy recommendations need to be considered to strengthen support and effectiveness of sustainable development efforts in this region.

In light of swift urbanization and the lack of precise land use maps in urban regions, comprehending land use patterns becomes vital for efficient planning and promoting sustainable development. The objective of this study is to assess the land use pattern in order to catalyze sustainable township development in the study area. The procedure adopted involved acquiring the cadastral layout plan of the study area, scanning, and digitizing it. Additionally, satellite imagery of the area was obtained, and both the cadastral plan and satellite imagery were geo-referenced and digitized using ArcGIS 9.2 software. These processes resulted in reasonable accuracy, with a root mean square (RMS) error of 0.002 inches, surpassing the standard of 0.004 inches. The digitized cadastral plan and satellite imagery were overlaid to produce a layered digital map of the area. A social survey of the area was conducted to identify the specific use of individual plots. Furthermore, a relational database system was created in ArcCatalog to facilitate data management and querying. The research findings demonstrated the approach's effectiveness in enabling queries for the use of any particular plot, making it adaptable to a wide range of inquiries. Notably, the study revealed the diverse purposes for which different plots were utilized, including residential, commercial, educational, and lodging. An essential aspect of land use mapping is identifying areas prone to risks and hazards, such as rising sea levels, flooding, drought, and fire. The research contributes to sustainable township development by pinpointing these vulnerable zones and providing valuable insights for urban planning and risk mitigation strategies. This is a valuable resource for urban planners, policymakers, and stakeholders, enabling them to make informed decisions to optimize land use and promote sustainable development in the study area.

This research analyzes the relationship between political stability, renewable energy utilization, economic progress, and tourism in Indonesia from 1990 to 2020. We employ advanced econometric techniques, including the Fourier Bootstrap Autoregressive Distributed Lag (ARDL) approach and Fourier Toda-Yamamoto causality testing, to ensure the robustness of our results while accounting for smooth structural changes in the data. The analysis uncovers a long-term equilibrium relationship between tourism and its fundamental determinants. Our research reveals significant positive impacts of political stability and renewable energy consumption on tourism in Indonesia. A stable political environment creates a favorable climate for tourism development, instilling confidence in both domestic and international tourists. Promoting renewable energy usage aligns with sustainable tourism practices, attracting environmentally conscious travelers. Furthermore, our findings demonstrate a bi-directional causal relationship between these variables over time. Changes in political stability, renewable energy consumption, and economic growth profoundly influence the tourism sector, while the growth of tourism itself can also stimulate economic development and foster political stability. Our findings underscore the need for environmentally sustainable and politically stable tourism policies. Indonesia’s tourism sector can grow sustainably with renewable energy and stability. Policymakers can develop strategies with tourism, political stability, renewable energy, and economic prosperity in mind.

Using the United Nations’ Online Services Indicator (OSI) as a benchmark, the study analyzes Jordan’s e-government performance trends from 2008 to 2022, revealing temporal variations and areas of discontent. The research incorporates diverse testing strategies, considering technological, organizational, and environmental factors, and aligns with global frameworks emphasizing usability, accessibility, and security. The proposed model unfolds in three stages: data collection, performing data operations, and target selection using the Generalized Linear Model (GLM). Leveraging web crawling techniques, the data collection process extracts structured information from the Jordanian e-government portal. Results demonstrate the model’s efficacy in assessing accessibility and predicting web crawler behavior, providing valuable insights for policymakers and officials. This model serves as a practical tool for the enhancement of e-government services, addressing citizen concerns and improving overall service quality in Jordan and beyond.