The article explores the application of neuro- symbolic approaches utilizing artificial neural networks for diagnosing neurological disorders among individuals with autism spectrum conditions. It demonstrates how these networks can identify and enhance distinctive strengths, such as advanced pattern recognition and systematic reasoning, facilitating their integration into professional environments.
In this study, we develop and evaluate performance of a location-tracking application built using a Python/Django/PostgreSQL stack. Through rigorous experimentation and its analysis, we scrutinize the efficiency of WebSocket connections in facilitating real-time communication and data retrieval. By comparing our findings with the previous research results available on an ASP.NET stack, we contribute to understanding of the technologies for stack selection and the strategies used for optimization of the location-tracking applications.
This paper represents a list of widely known issues of risk implementation related to specific negative scenarios of software use. The core selection criteria were an opportunity to identify impact areas that led to the core losses for each case. Main preconditions, course of events and consequences are highlighted. In addition, it is explicitly defined which negative scenario was ignored or missed and how it led to the damage.
The modern software development uses ‘use cases’ as a core tool of applications’ business logic description. Their core aim is to describe a scenario leading to the delivery of the application’s business value. Aside from positive use cases intended to describe an aim of this application or it’s core features negative use cases are describing acts of software misuse able to cause undesirable consequences. At some circumstances, such misuse may cause significant losses for business and society. But on the other hand mitigation of negative scenarios may raise project costs.