Spiritual Intelligence (SI) has become a key contributor towards enhancing employee well-being and job satisfaction (JS) in the modern competitive business world. This study examines the impact of SI on JS among Sri Lankan IT professionals, considering gender’s role in this relationship. Analyzing data from 383 respondents using Partial Least Square Structural Equation Modeling (PLS-SEM), the study reveals a strong positive correlation between SI and JS, with no moderating effect on gender. The study highlights the importance of embedding SI into HR and organizational policies to enhance workforce resilience and retention while contributing to broader industry development and global competitiveness in the IT sector.

The range migration algorithm (RMA) is an accurate imaging method for processing synthetic aperture radar (SAR) signals. However, this algorithm requires a big amount of computation when performing Stolt mapping. In high squint and wide beamwidth imaging, this operation also requires big memory size to store the result spectrum after Stolt mapping because the spectrum will be significantly expanded. A modified Stolt mapping that does not expand the signal spectrum while still maintains the processing accuracy is proposed in this paper to improve the efficiency of the RMA when processing frequency modulated continuous wave (FMCW) SAR signals. The modified RMA has roughly the same computational load and required the same memory size as the range Doppler algorithm (RDA) when processing FMCW SAR data. In extreme cases when the original spectrum is significantly modified by the Stolt mapping, the modified RMA achieves better focusing quality than the traditional RMA. Simulation and real data is used to verify the performance of the proposed RMA.

This study aims to examine the impact of an innovative self-directed professional development (SDPD) model on fostering teachers’ professional development and improving their ability to manage this development independently. A quantitative research method was adopted, involving 60 participants from Almaty State Humanitarian and Pedagogical College No. 2, Almaty, Kazakhstan. Descriptive and inferential statistics were used to assess the SDPD model’s effectiveness, specifically in promoting teacher engagement, adoption of new pedagogical techniques, and improvement in reflective practices. The study findings reveal that teachers, particularly in developing regions, often face challenges in accessing formal professional development programs. The implementation of the SDPD model addresses these barriers by providing teachers with the tools and strategies required for self-improvement, regardless of geographic or economic constraints. The study participants in the pilot phase showed increased engagement with new pedagogical methods, improved reflective practices, and greater adaptability to emerging educational technologies. The algorithmic aspect of the model streamlined the professional development process, while the activity-based approach ensured that learning remained practical and relevant to teachers’ everyday needs. By offering a clear framework for continuous improvement, the model addresses the gaps in formal training access and cultivates a culture of lifelong learning. These findings suggest that the SDPD model can contribute to elevating teaching standards globally, particularly in regions with limited professional development resources.

Telecommunications markets have a giant impact on countries’ economies. An example of this is the great potential offered by the internet service, which allows growth in various aspects such as productivity, education, health, and connectivity. A few companies dominate telecommunications markets, so there is a high market concentrations risk. In that sense, the state has to generate strong regulation in the sector. Models for measuring competition in telecommunications markets allow the state to monitor the concentration performance in these markets. The prediction of competition in the telecommunications market based on artificial intelligence techniques would allow the state to anticipate the necessary controls to regulate the market and avoid monopolies and oligopolies. This work’s added value and the main objective is to measure the current concentration level in the Colombian telecommunications market, this allows for competitive analysis in order to propose effective strategies and methodologies to improve competition in the future of Colombian telecommunications services operators. The main result obtained in the research is the existence of concentration in the Colombian telecommunications market.

To address the escalating online romance scams within telecom fraud, we developed an Adaptive Random Forest Light Gradient Boosting (ARFLGB)-XGBoost early warning system. Our method involves compiling detailed Online Romance Scams (ORS) incident data into a 24-variable dataset, categorized to analyze feature importance with Random Forest and LightGBM models. An innovative adaptive algorithm, the Adaptive Random Forest Light Gradient Boosting, optimizes these features for integration with XGBoost, enhancing early Online romance scams threat detection. Our model showed significant performance improvements over traditional models, with accuracy gains of 3.9%, a 12.5% increase in precision, recall improvement by 5%, an F1 score increase by 5.6%, and a 5.2% increase in Area Under the Curve (AUC). This research highlights the essential role of advanced fraud detection in preserving communication network integrity, contributing to a stable economy and public safety, with implications for policymakers and industry in advancing secure communication infrastructure.