Deploying SIP-based Mobile Exam Application onto Next Generation Network testbed

Over the past few years, mobile operators are faced with enormous challenges. Of such challenges, evolved user demands on personalized applications. Telecommunications industry as well as research community have paid enormous attention to Next Generation Networks (NGN) to address this challenge. NGN is perceived as a sophisticated platform where both application developers and mobile operators cooperate to develop user applications with enhanced quality of experience. The objective of this paper is twofold: first we present an introduction to state-of-the-art NGN testbed to be developed at KAU, and second we provide initial analysis for deploying a mobile application on top of the testbed.Comment: 6 Pages, Electronics, Communications and Photonics Conference (SIECPC), 2011 Saudi International, Riyadh, KSA, 24-26 April 201

Numerical and experimental study of cellular structures as a heat dissipation media

High heat flux generation in electronic devices demands new modes, methods and structures to dissipate heat effectively. We investigate the thermal performance of cellular structures using computational fluid dynamics (CFD) and obtained an optimal cellular structure for effective heat dissipation. Then, we validate our numerical results with experimental results obtained using optimized cellular structure. We found the minimum base temperature for the optimized cellular structure to be 43.6 °C and 47.4 °C numerically and experimentally respectively at inlet velocity of 10 m/s. We carried out experiments and simulations at the heat flux of 35,503 W/m 2. We found a close agreement between numerical and experimental results with an error of 8.71% for the base temperature. Previously the best base temperatures were reported to be 55 °C and 40.5 °C using air and water respectively [1, 2]. </p

Fabrication and characterization of curcumin loaded ZnO nanoparticles and their in vitro antibacterial activity

Nanotechnology is broadly defined as the study and development of the chemical physical and natural properties of materials, devices, and structures that differ from those found on a larger scale, and Nano patents are derived from the Japanese language. Zinc oxide nanoparticles are used in a wide-ranging applications, visible light, catalytic actions, ultrasonic, deodorizing, diabetes treatment, cosmetics, lasers, paints, ultraviolet light absorbing constituents, rubber industry, catalytic agent for light flattening, and specifically in the medical and pharmaceutical sciences7. Curcumin is a useful plant-based material derived from "turmeric" that has the potential to be used in the green synthesis of ZnONPs. This is due to the influence of "polyphenol," which may also result in the formation of ZnONPs during the reduction process. Characterization reported Spherical particles with varying size from few nanometers to about 900 nm. The antibacterial activity by disk diffusion method against E. coli (Gram negative), Pseudomonas aerugionsa, Bordetella bronchiseptics &amp; Micrococcus luteus revealed mark able zone of inhibition that declared potent antibacterial activity of Curcumin ZnO NP against gram positive bacteria more than negative ones where Ciprofloxacin was used as standard

Ethical implications of AI (artificial intelligence) in healthcare mainly focus on surgical procedures : identification of ethical issues of AI in surgical procedures and ranking of ethical issues based on criticality

The integration of Artificial Intelligence (AI) in the healthcare sector, particularly within surgical procedures, presented advancements in accuracy and effectiveness while facing considerable ethical concerns. These concerns include transparency, medical data privacy, economic and accessibility challenges, algorithmic bias, human oversight, accountability, and the influence on professional surgeons. This thesis identifies and prioritizes these ethical issues to ensure AI technologies' responsible and fair utilization in surgical procedures. The study aims to categorize the most critical ethical concerns, assess them based on criticality, and propose recommendations to highlight the three most critical issues. A comprehensive literature review and a survey involving experts from healthcare, AI, and ethics fields were conducted to rank the identified ethical issues based on their criticality. The Multi-Criteria Group Decision-Making (MCGDM) method was implemented to assess and prioritize these ethical issues methodically. The study found the most critical ethical issues, where transparency and explainability ranked the foremost concern, followed by medical data privacy and economic and accessibility challenges. Drawing from these results, the study proposed recommendations for healthcare providers, researchers, and AI developers to ensure transparency, enhance medical data privacy, and overcome accessibility barriers. Furthermore, it recommends reducing algorithmic bias, ensuring continual human oversight, and furnishing recurrent training for surgeons. These recommendations are geared towards promoting ethical and secure integration of AI in surgical procedures, enhancing patient results, and upholding trust in AI-driven healthcare systems. This study contributes towards highlighting and mitigating the ethical implications caused by AI in surgical operations, providing a framework for forthcoming research and recommendations for the most critical ethical concerns