The Bucharest University of Economic Studies, Faculty of Economic Cybernetics, Statistics and Informatics, Department of Economic Informatics and Cybernetics
Mr. Antonio Clim
The Bucharest University of Economic Studies, Faculty of Economic Cybernetics, Statistics and Informatics, Department of Economic Informatics and Cybernetics
Cities have grown in development and sophistication throughout human history. Smart cities are the current incarnation of this process, with increased complexity and social importance. This complexity has come to involve significant digital components and has thus come to raise the associated cybersecurity concerns. Major security relevant events can cascade into the connected systems making up a smart city, causing significant disruption of function and economic damage. The present paper aims to survey the landscape of scientific publication related to cybersecurity-related issues in relation to smart cities. Relevant papers were selected based on the number of citations and the quality of the publishing journal as a proxy indicator for scientific relevance. Cybersecurity will be shown to be reflected in the selected literature as an extremely relevant concern in the operation of smart cities. Generally, cybersecurity is implemented in actual cities through the concerted application of both mature existing technologies and emerging new approaches.
This paper provides an in-depth analysis of the Big Data application in the field of medicine. This innovative technology is a significant topic because Big Data introduces new opportunities for medical practitioners and patients, including the improvement of patients’ quality of life and healthcare systems, the mitigation of specific illnesses, and the reduction of state-level healthcare costs. This paper discusses implications relative to wearable sensing devices as well as personalised medicine. The advantages of the analytical capabilities of Big Data are also discussed. For instance, Big Data analytics can aid in the improvement of healthcare cost-efficiency and profit generating capabilities. The limitations and vulnerabilities of Big Data application in the healthcare field, such as the development of the domain-specific system architecture, are exposed. This paper examines the elements of architecture (data acquisition & transmission, cloud processing, and analytics) adapted to healthcare needs. A brief outline of the restrictions for official approval of the new devices and methodologies is presented. Specifically, the sensor data are heterogeneous and untagged. Previously, the implementation of clinical records into models was required. Currently, adaptation of machine-learning techniques is required. Ethical issues relative to the personal privacy involved in healthcare data acquisition, storage, and processing are considered.
Education is another field which generative artificial intelligence has made its way into, intervening in students’ learning processes. This article explores students’ perspectives on the use of generative AI tools, specifically ChatGPT-3.5 (free version) and ChatGPT-4 (with a subscription). The results of the survey revealed a correlation between the use of ChatGPT and the perception of grade improvement by students. In addition, this article proposes an architecture for an adaptive learning system based on generative artificial intelligence (AI). To develop the architectural proposal, we incorporated the results of the student survey along with insights gained from analyzing the architectures of other learning platforms. The proposed architecture is based on a study of adaptive learning platforms with classically virtual assistants. The main question from which the current research started was how artificial intelligence can be integrated into a learning system to improve student outcomes based on their experience with generative AI. This has been sectioned into two more specific questions: 1. How do students perceive the use of generative artificial intelligence tools, such as ChatGPT, in enhancing their learning journey? 2. Is it possible to integrate generative AI into a learning system used in education? Consequently, this article concludes with a proposed architecture for a learning platform incorporating generative artificial intelligence technologies. This article aims to present a way to understand how generative AI technologies support education and contribute to improving academic performance.