Recently, Agile project management has received significant academic and industry attention from due to its advantages, such as decreased costs and time, increased effectiveness, and adaptiveness towards challenging business environments. This study primarily aims to investigate the relationship between the success factors and Agile project management methodology adoption and examine the moderating effect of perceived compatibility. The technology-organization-environment (TOE) framework and technology acceptance theories (UTAUT, IDT, and TAM) were applied as the theoretical foundation of the current study. A survey questionnaire method was employed to achieve the study objectives, while quantitative primary data were gathered using a carefully designed methodological approach focusing on Omani oil and gas industry. The PLS-SEM technique and SmartPLS software were used for hypotheses testing and data analysis. Resultantly, readiness, technology utilization, organizational factors, and perceived compatibility were the significant factors that promoted Agile methodology adoption in the oil and gas industry. Perceived compatibility moderated the relationship between success factors and Agile methodology. The findings suggested that people, technology, and organizational factors facilitate the Agile methodology under the technology acceptance theories and frameworks. Relevant stakeholders should adopt the study outcomes to improve Agile methodology adoption.

As cities continue to face the increasing demands of urban transportation and the need for sustainable mobility solutions, the integration of intelligent transportation systems (ITS) with smart city infrastructure emerges as a promising approach. This paper presents a novel framework for integrating ITS with smart city infrastructure, aiming to address the challenges of urban transportation and promote sustainable mobility. The framework is developed through a comprehensive literature review, case studies, and stakeholder interviews, providing significant insights into the integration process. Our research outlines the key components of smart city infrastructure that can be integrated with ITS, highlights the benefits of integration, and identifies the challenges and barriers that need to be addressed. Additionally, we propose and apply evaluation methods to assess the effectiveness of ITS integration with smart city infrastructure. The results demonstrate the novelty and significance of this framework, as it significantly reduces traffic congestion, improves air quality, and enhances citizen satisfaction. This paper contributes to the existing literature by providing a comprehensive approach to integrating ITS with smart city infrastructure, offering a transformative solution for urban transportation challenges.

Working Capital Management (hereafter WCM) is the strategic tool that helps a company navigate through challenging economic growth, and influence its competitive performance. Thus, this study examines the impact of WCM on the competitiveness of firms operating in the non-financial sectors in Pakistan. We use the Generalized Method of Moments (GMM) technique to ensure the robustness of our results. The study findings reveal that both a large net trade cycle and surplus working capital have a substantial negative impact on firms’ competitiveness within their respective industries. These results suggest that companies should streamline their investments in working capital accounts and concentrate more resources on long-term projects that maximize value to improve their competitiveness compared to other companies. Therefore, firms that are effectively managing their short-term financial affairs are experiencing much better performance in all aspects of firm performance. The research findings highlight the urgent need for governmental initiatives designed to improve WCM practices in these industries. It is imperative for the management of  companies with excess net working capital to maximize their working capital efficiency, aligning it with industry standards to enhance competitiveness. Moreover, policymakers should prioritize easing access to financial alternatives that allow enterprises to maintain an efficient working capital structure without relying on excessive measures. Furthermore, policymakers should be cautious when determining minimum cash balance requirements in a cash-strapped economy where external financing is relatively more expensive than in other regional economies.

Mapping land use and land cover (LULC) is essential for comprehending changes in the environment and promoting sustainable planning. To achieve accurate and effective LULC mapping, this work investigates the integration of Geographic Information Systems (GIS) with Machine Learning (ML) methodology. Different types of land covers in the Lucknow district were classified using the Random Forest (RF) algorithm and Landsat satellite images. Since the research area consists of a variety of landforms, there are issues with classification accuracy. These challenges are met by combining supplementary data into the GIS framework and adjusting algorithm parameters like selection of cloud free images and homogeneous training samples. The result demonstrates a net increase of 484.59 km² in built-up areas. A net decrement of 75.44 km² was observed in forest areas. A drastic net decrease of 674.52 km² was observed for wetlands. Most of the wastelands have been converted into urban areas and agricultural land based on their suitability with settlements or crops. The classifications achieved an overall accuracy near 90%. This strategy provides a reliable way to track changes in land cover, supporting resource management, urban planning, and environmental preservation. The results highlight how sophisticated computational methods can enhance the accuracy of LULC evaluations.

The electro-magnetic (EM) waves transmitted through a thin object with fine structures are observed by a microsphere located above the thin object. The EM radiation transmitted through the object produces both evanescent waves, which include information on the fine structures of the object (smaller than a wavelength), and propagating waves, which include the large image of the object (with dimensions larger than a wavelength). The super-resolutions are calculated by using the Helmholtz equation. According to this equation, evanescent waves have an imaginary component of the wavevector in the z direction, leading the components of the wavevector in the transversal directions to become very large so that the fine structures of the object can be observed. Due to the decay of the evanescent waves, only a small region near the contact point between the thin object and the microsphere is effective for producing the super resolution effects. The image with super-resolution can be increased by a movement of the microsphere over the object or by using arrays of microspheres. Both propagating and evanescent waves arrive at the inner surface of the microsphere. A coupling between the transmitted EM waves and resonances produced in the dielectric sphere, possibly obtained by the Mie method, leads to a product of the EM distribution function with the transfer function. While this transfer function might be calculated by the Mie method, it is also possible to use it as an experimental function. By Fourier transform of the above product, we get convolution between the EM spatial modes and those of the transfer function arriving at the nano-jet, which leads the evanescent waves to become propagating waves with effective very small wavelengths and thus increase the resolution.