A New Method of Rainfall Forecast Based on the Virtual Amount of the Air Temperature: Theoretical Study

Njipouakouyou Samuel, Moussa Mahamat Saleh, Abdelkerim Brahim Adam — Thu, 21 May 2026 00:00:00 +0100

Here is developed a new method of the rainfall forecast based on the virtual amount of the air temperature. The main advantages of this method are that between others, it needs a minimum number of physical meteorological parameters commonly observed in almost all the stations, even in the poorest countries in the world, it does not need neither sophisticated tool for its realization, nor high-qualified personnel for operational works. Thus, the authors are sure that its world-wide implementation. It is evident that it will help solving actual crucial problems linked to the today ongoing climate change, between others hunger and generated violences. The permanent none availability of meteorological data in many developing countries in general and in our geographical areas in particular has made its operational implementation quite impossible. This situation has forced the authors to limit this study just to its theoretical presentation. Despite this handicap, they are very sure of its accuracy during operational works.

Failure Modes and Effects Analysis of AI-Enabled Technologies for Aeronautical and Astronautical Applications

Y. F. Khalil — Mon, 25 May 2026 00:00:00 +0100

AI technologies (AIT) have the potential to transform business processes by increasing productivity and reducing costs, but their adoption may also introduce unintended consequences. The overarching objective of this study is to examine the key promises and perils of AIT in the aerospace industry and to provide recommendations for safer AI use across the aerospace ecosystem, both airborne and ground-based. To this end, we adapt the traditional failure modes and effects analysis (FMEA) method to the aerospace domain—encompassing aeronautics and astronautics—and designate the resulting approach as the AIT-FMEA framework. Applying AIT-FMEA, we identify 23 AIT-related failure modes (FMs), characterize their potential effects, and propose targeted risk-mitigation strategies. The FMs are grouped into five categories: Technical [T], Social/Societal [S/S], Institutional/Organizational [I/O], Environmental [E], and Political [P]. Of the identified FMs, 43.48% fall under [T], 21.74% under [S/S], 17.39% under [I/O], 13.04% under [P], and 4.35% under [E]. We map these FMs to relevant aerospace standards, including ARP4761A, DO-178C, DO-326B, and DO-356A. A two-factor (4×5) risk model indicates that, if unmitigated, these FMs could pose medium to critical risks, exceeding an acceptability threshold defined by improbable or remote likelihood combined with low severity. Addressing these FMs is essential to realize the benefits of AIT while avoiding undue risk. The study’s insights are intended to support AI policymakers, aerospace standards bodies, and AIT developers in prioritizing verification and validation (V&V) and implementing other proactive measures to manage AIT-related risks.

Journal of Research in Engineering and Computer Sciences

A New Method of Rainfall Forecast Based on the Virtual Amount of the Air Temperature: Theoretical Study

Failure Modes and Effects Analysis of AI-Enabled Technologies for Aeronautical and Astronautical Applications