Modern civilization increasingly relies on sustainable and eco-friendly data centers as the core hubs of intelligent computing. However, these data centers, while vital, also face heightened vulnerability to hacking due to their role as the convergence points of numerous network connection nodes. Recognizing and addressing this vulnerability, particularly within the confines of green data centers, is a pressing concern. This paper proposes a novel approach to mitigate this threat by leveraging swarm intelligence techniques to detect prospective and hidden compromised devices within the data center environment. The core objective is to ensure sustainable intelligent computing through a colony strategy. The research primarily focusses on the

In architectural learning, it is difficult to stimulate cultural awareness through the traditional education approaches, which results in historic places being neglected as knowledge sources. This research explores the premise that sketch-based visual storytelling may act as a generative approach to connect cognition, emotion, and behavior in historical contexts. The study adopts a qualitative methodology to explore a learning experience comprising two phases: the first is a formal educational setting, and the second is a historical and cultural context, aiming to investigate the role of sketch-based storytelling in enhancing cultural awareness. MAXQDA was employed to code the students’ storyboards on three levels of cultural awareness, m

The purpose of this research is to improve the organizational performance of the Oil Projects Company by adopting an approach to strategic change، and finding appropriate solutions to the problems facing the company. The researcher adopted in designing his research by conducting a survey of previous literature that dealt with approaches to strategic change، as the results of the survey showed that most researchers agree on the approach of renewal and modernization، Which formed a starting point for the researcher to identify the extent of the company's management interest in renewal and modernization to improve its level of performance، and the quality of the procedures followed on the ground that is related to

Background: Diagnosis and treatment planning can be difficult with conventional radiographic methods as the orthodontic-surgical management of impacted canines requires accurate diagnosis and precise localization of the impacted canine and the surrounding structures. This study was aimed to localize and evaluate weather there is any differences in the diagnostic information provided by multi-slice computed tomography three dimensional volumetric CT images and two dimensional reconstructed panorama images (derived from CT) in subjects with impacted maxillary canines. Materials and Methods: Thirty patients including 24 female and 6 male with mean age of 18 years with suspected unilaterally or bilaterally impacted maxillary canines were evalu

The research endeavors to harness the benefits stemming from the integration of constraint theory into construction project management, with the primary goal of mitigating project completion delays. Additionally, it employs fuzzy analysis to determine the relative significance of fundamental constraints within projects by assigning them appropriate weights. The research problem primarily revolves around two key issues. Firstly, the persistent utilization of outdated methodologies and a heavy reliance on workforce experience without embracing modern computerized technologies. Secondly, the recurring problem of project delivery delays. Construction projects typically encompass five fundamental constraint types: cost restrictions, tim

<span>Deepfakes have become possible using artificial intelligence techniques, replacing one person’s face with another person’s face (primarily a public figure), making the latter do or say things he would not have done. Therefore, contributing to a solution for video credibility has become a critical goal that we will address in this paper. Our work exploits the visible artifacts (blur inconsistencies) which are generated by the manipulation process. We analyze focus quality and its ability to detect these artifacts. Focus measure operators in this paper include image Laplacian and image gradient groups, which are very fast to compute and do not need a large dataset for training. The results showed that i) the Laplacian