Academic papers were published in Elsevier and Journal IEEE Access
Air Force Agency: ITA, by Lieutenant Leonardo
The study developed by the researcher of the Graduate Program in Operational Applications (PPGAO) of the Technological Institute of Aeronautics (ITA), Lieutenant Colonel Gustavo Barbi Vieira, is featured in one of the world’s most important scientific journals in the project management sector, Elsevier. The article by Colonel Engineer Gustavo Farhat de Araújo, also a PPGAO researcher, was the subject of interest in one of the main international engineering journals, the IEEE Access Journal.
The work published in the Elsevier journal presents an innovative proposal for analyzing the interdependencies between projects and creating a classification standard. In addition, the research proposes a new terminology to improve the portfolio selection process in strategic military activities. The publication in the IEEE Access Journal analyzes non-collaborative targets of interest to the Brazilian Air Force (FAB) and uses Artificial Intelligence to develop a method for identifying these objectives.
Studies under development
Entitled “Project Portfolio Selection considering interdependencies: A review of terminology and approaches”, Lieutenant-Colonel Gustavo Vieira’s doctoral work addresses the interdependencies between projects and their effects on portfolio selection in organizations such as the Air Force General Staff (EMAER). The research showed that these interdependencies are particularly important in military applications, since projects aimed at developing operational capabilities generally require integration between the various initiatives in order to achieve the desired effect. As a result, an original classification proposal is presented for these interdependencies, as a way of standardizing the understanding of the relationships between projects during the selection and management of portfolios for these activities.
Colonel Gustavo’s work, entitled “Synthetic SAR Data Generator using Pix2pix cGAN Architecture for Automatic Target Recognition”, uses a special type of deep learning network, the Conditional Generative Adversarial Networks (cGAN). The Artificial Intelligence developed in the research generates false images that are similar to real images generated by a Synthetic Aperture Radar (SAR). The aim was to develop a system capable of providing data for training algorithms for classifying non-cooperative targets, i.e. targets of great strategic value that are rarely exposed, making it difficult to collect a sufficient number of images for training the algorithm.
For the author of the paper Project Portfolio Selection considering interdependencies: A review of terminology and approaches, Lieutenant-Colonel Gustavo Vieira, this is an important conceptual milestone in the sector of portfolio and project selection and management, as it clarifies how the relationships between them should be classified, as well as mapping the effects of this management process. “This study discusses how future research into the effects of interdependencies between projects can contribute from now on to the improvement of portfolio selection methods in organizations in general and, in particular, in the FAB. It is very important that we are able to manage this integration at all stages of the life cycle of its strategic projects,” he concluded.
The work carried out by Colonel Gustavo on Artificial Intelligence, according to the Assistant Coordinator of the PPGAO, Lieutenant Colonel Geraldo Mulado de Lima Filho, demonstrates a rapprochement between the academic and operational areas, representing disruptive knowledge on the military scene. “It is extremely important that this technology is developed internally in the country, because when it is acquired from foreign companies it arrives as a black box, i.e. without access to the parameters and functions of the computational model used. This makes it impossible to assess the suitability of these parameters for operational applications in the Air Force, which can be done using systems developed by the FAB,” he concluded.
Images: ITA *** Translated by DEFCONPress FYI Team ***