Sensor-based Methodology for Indoor Trajectory Determination

The unprecedented development in the realm of Internet of Things in recent times has facilitated the adoption and integration of microcontrollers and sensors into a large variety of contexts and at a significant scale. Among the multitude of concepts that derive from this paradigm, a topic that recently grabbed both industry and academic interest is the indoor location, a field where dynamic challenges are currently tackled in order to enhance existing emergency evacuation systems, behavioural based recommendation engines and improve indoor assistants for optimized path finding and accurate guidance

“An Effective Multidimensional Model for Analyzing Social Web Big Data – Testing in simple Web 2.0 Applications of Internet Politics”

Web 2.0 applications have provided researchers with vast quantities of Big Data, opening up new horizons for developing innovative analysis techniques that are applicable in multiple cognitive fields. Politics is definitely among them and is currently in a dynamically evolving range of these applications.

A Descriptive Study on Cybersecurity Challenges of Working from Home during COVID-19 Pandemic and a Proposed 8 step WFH Cyber-attack Mitigation Plan

Organizations struggle to strike the right balance between flexibility and security for remote work. With the major portion of the workforce in every country working from home during the covid-19 pandemic, employers might not have accounted for this scale of load on their IT infrastructure, not to mention their cybersecurity preparedness.

A Cross-sectional Study on Improving Privacy Policy Read Rate and Comprehension via Better UX/UI Design

Data privacy is becoming one of the major risks faced by organizations. With the emergence of new technologies such as Internet of Things (IoT), Automated vehicles, mobile payments, privacy is no longer a compliance issue, but also a user responsibility to ensure users are aware of the risks of sharing personal data with third parties.

Better Management of Rabies Using Innovative Statistical Tools

The aim of this paper is to illustrate how statistical tools can benefit healthcare policy makers specialised in the rabies management. Understanding the prevalence of such a disease is crucial for management teams. Seasonality may be a salient feature of data series provided by medical units, that is why the use of an innovative tool for seasonal adjustment is needed. For this paper, the data series (number of persons examined for rabies, by age and residency) were provided by one single health care unit – The National Institute of Infectious Diseases “Matei Bals”.

How Artificial Intelligence can make Competition more Intelligent

A company's environment is constantly changing, new competitive models have appeared, new tangible and intangible resources are being built and new competitive regulations form a new competitive framework which opens the field to new opportunities and new threats. With this dynamic, companies are rushing towards the development of their strategic decision system which must be powerful to follow any material (product and service) or immaterial resource (belief, knowledge, know-how) coming from one of the direct competitors. In this context, a conceptual study is carried out with the objective to analyze the evolution of cognition-based competition using artificial intelligence (AI) technology as a support for strategic decision-making; this is in order to transform the competition into an intelligent mode. The finding is presented in an intelligent approach designed to generate automatic competition rules based on deep learning techniques.