A considerable amount of literature has been published on Corporate Reputation, Branding and Brand Image. These studies are extensive and focus particularly on questionnaires and statistical analysis. Although extensive research has been carried out, no single study was found which attempted to predict corporate reputation performance based on data collected from media sources. To perform this task, a biLSTM Neural Network extended with attention mechanism was utilized. The advantages of this architecture are that it obtains excellent performance for NLP tasks. The state-of-the-art designed model achieves highly competitive results, F1 scores around 72%, accuracy of 92% and loss around 20%.
MULTIFILE
Abstract Technology has a major impact on the way nurses work. Data-driven technologies, such as artificial intelligence (AI), have particularly strong potential to support nurses in their work. However, their use also introduces ambiguities. An example of such a technology is AI-driven lifestyle monitoring in long-term care for older adults, based on data collected from ambient sensors in an older adult’s home. Designing and implementing this technology in such an intimate setting requires collaboration with nurses experienced in long-term and older adult care. This viewpoint paper emphasizes the need to incorporate nurses and the nursing perspective into every stage of designing, using, and implementing AI-driven lifestyle monitoring in long-term care settings. It is argued that the technology will not replace nurses, but rather act as a new digital colleague, complementing the humane qualities of nurses and seamlessly integrating into nursing workflows. Several advantages of such a collaboration between nurses and technology are highlighted, as are potential risks such as decreased patient empowerment, depersonalization, lack of transparency, and loss of human contact. Finally, practical suggestions are offered to move forward with integrating the digital colleague
Despite the vast potential drone technologies have, their integration to our society has been slow due to restricting regulations. Recently, a new EU-wide drone regulation has been published. This regulation is intended to harmonize the non-uniform national regulations across EU. It also relaxes the existing restrictions and allows previously prohibited operations that have significant socio-economic and technological impacts, such as autonomous BVLOS flights even over populated areas. However, there are challenges with regard to specifics and accessibilities of the required technological & procedural prerequisite this regulation entails. There is, therefore, a demand from SMEs for practical knowledge on technological and procedural aspects of a safe, robust and BVLOS operable security drone with short and long-term autonomy that fully complies to the new drone regulation. The required drone technologies include robust obstacle avoidance, intelligence failsafe for robust, reliable and safe autonomous flights with long-term autonomy capabilities. The operational procedures include SORA, pre/in/post-flight analysis and ROC/LUC permissions. In this project, these two aspects will be addressed in an integral manner. The consortium recognizes that developing such advanced security drone in two years is ambitious. Yet, they firmly believe that it is realizable due to the complementary expertise of the consortium and their commitment for the success of the project. With this project, the knowledge institutes will enrich their practical knowledge in the area of autonomous and BVLOS capable drones, operational procedures, risk analysis and mitigations. The partner companies will be equipped with the necessary technologies, operation permission and knowledge on optimal operation procedures to be at the forefront and benefit from the exploding market opportunities when the new regulation is fully implemented in July 2022. Moreover, this project will also make a demonstrable contribution to the renewal of higher professional education.
