Nearly 3.5 billion humans have oral health issues, including dental caries, which requires dentist-patient exposure in oral examinations. The automated approaches identify and locate carious regions from dental images by localizing and processing either colored photographs or X-ray images taken via specialized dental photography cameras. The dentists’ interpretation of carious regions is difficult since the detected regions are masked using solid coloring and limited to a particular dental image type. The software-based automated tools to localize caries from dental images taken via ordinary cameras requires further investigation. This research provided a mixed dataset of dental photographic (colored or X-ray) images, instantiated a deep learning approach to enhance the existing dental image carious regions’ localization procedure, and implemented a full-fledged tool to present carious regions via simple dental images automatically. The instantiation mainly exploits the mixed dataset of dental images (colored photographs or X-rays) collected from multiple sources and pre-trained hybrid Mask RCNN to localize dental carious regions. The evaluations performed by the dentists showed that the correctness of annotated datasets is up to 96%, and the accuracy of the proposed system is between 78% and 92%. Moreover, the system achieved the overall satisfaction level of dentists above 80%.

In an era marked by digital transformation and organisational complexity, multinational corporations (MNCs) strive to build flexible systems that can harness and share knowledge effectively across diverse cultural and geographic contexts. This study investigates the strategic role of organisational culture in enabling the adoption and utilisation of knowledge management systems (KMSs) and how this relationship influences knowledge sharing and organisational effectiveness. Drawing upon the Technology Acceptance and Denison’s cultural framework, this research positions organisational culture as a key driver of system flexibility, enhancing user perceptions of usefulness and ease of use, and thereby fostering greater engagement with KMSs. Survey data from 221 respondents across Europe and the Middle East were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). The findings reveal that cultural adaptability, involvement, and mission significantly impact KMSs usage and knowledge sharing, which are critical for organisational agility and sustained performance. This study contributes to the literature on flexible systems management by demonstrating how culturally embedded knowledge practices enhance technological adoption and strategic responsiveness. It offers practical insights for global firms seeking to develop adaptive knowledge infrastructures that support innovation, collaboration, and resilience in dynamic international environments.

The effects of mutual coupling on the scanning characteristics of a four-element linear rectangular dielectric resonator antenna array (RDRA) are investigated for different inter-element spacing in this work. In particular, the gain and half-power beam width (HPBW) of an RDRA are studied for various scan angles in the E- and H-plane configurations. It is shown that for both the E and H planes, mutual coupling has an adverse effect on the performance of both phased array configurations. The H-plane array, however, is more stable than the E-plane array in terms of a gain and beam width performance comparison. The HPBW increases and gain decreases more in the E plane than the H plane when the scan angle is increased.