First Responders' Localization and Health Monitoring During Rescue Operations

Currently, first responders’ coordination and decision-making during res-cue, firefighting or police operations is performed via radio/GSM channels with some support of video streaming. In unknown premises, officers have no global situational awareness on operation status, which reduces coordination efficiency and increases decision making mistakes. This paper pro-poses a solution enabling the situational awareness by introducing an integrated operation workflow for actors localization and health monitoring. The solution will provide global situational awareness to both coordinators and actors, thereby increasing efficiency of coordination, reducing mistakes in decision making and diminishing risks of unexpected situations to appear. This will result in faster operation progress, lower number of human casualties and financial losses and, the most important, saved human lives in calamity situations

Obituary

On 6th February, Professor Ioan Dzitac passed away. &nbsp

An Ensemble Machine Learning Approach to Understanding the Effect of a Global Pandemic on Twitter Users’ Attitudes

It is thought that the COVID-19 outbreak has significantly fuelled racism and discrimination, especially towards Asian individuals[10]. In order to test this hypothesis, in this paper, we build upon existing work in order to classify racist tweets before and after COVID-19 was declared a global pandemic. To overcome the difficult linguistic and unbalanced nature of the classification task, we combine an ensemble of machine learning techniques such as a Linear Support Vector Classifiers, Logistic Regression models, and Deep Neural Networks. We fill the gap in existing literature by (1) using a combined Machine Learning approach to understand the effect of COVID-19 on Twitter users’ attitudes and by (2) improving on the performance of automatic racism detectors. Here we show that there has not been a sharp increase in racism towards Asian people on Twitter and that users that posted racist Tweets before the pandemic are prone to post an approximately equal amount during the outbreak. Previous research on racism and other virus outbreaks suggests that racism towards communities associated with the region of the origin of the virus is not exclusively attributed to the outbreak but rather it is a continued symptom of deep-rooted biases towards minorities[13]. Our research supports these previous findings. We conclude that the COVID-19 outbreak is an additional outlet to discriminate against Asian people, instead of it being the main cause

VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live

The best and worst places to live have been analysed in the world for many years and multiple criteria analysis has been used for that purpose. The quality of housing and its environment, pollution, green places, public spaces, physical movement and health, crime rates and individual safety, the wellbeing of youngsters, unemployment, job value, economic scarcity, governance, circadian rhythm, weekly rhythm and other factors are the focus of such analyses that aim to determine levels of positive emotions and happiness in built environment. Questionnaires are the most common tool for such analyses, where inhabitants are asked to rank their happiness experience as a whole in built environment. Many studies demonstrate that happy people are effective in multiple areas of their life including job efficiency, salary, health, human relations, etc. The innovative aspect of this research stems from the fact that biometric technologies (affective attitudes, emotional and physiological states) and the VINERS method developed by the authors are used to determine the best places to live and to serve neuro ads of homes for sale. To do this, rational segments of homebuyers are determined according to their demographic profiles (age, gender, education, marital status, families with children, main source of income), consumer psychographics and behaviour (happy, sad and angry along with valence and heart rate) and then select a rational video ad for such rational segment. The aim of our research is to develop the VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live (VINERS method) by combining the Somatic Marker Hypothesis, biometrics, neuromarketing and COPRAS method. This article presents a case study to demonstrate the VINERS method put to practice

VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live

The best and worst places to live have been analysed in the world for many years and multiple criteria analysis has been used for that purpose. The quality of housing and its environment, pollution, green places, public spaces, physical movement and health, crime rates and individual safety, the wellbeing of youngsters, unemployment, job value, economic scarcity, governance, circadian rhythm, weekly rhythm and other factors are the focus of such analyses that aim to determine levels of positive emotions and happiness in built environment. Questionnaires are the most common tool for such analyses, where inhabitants are asked to rank their happiness experience as a whole in built environment. Many studies demonstrate that happy people are effective in multiple areas of their life including job efficiency, salary, health, human relations, etc. The innovative aspect of this research stems from the fact that biometric technologies (affective attitudes, emotional and physiological states) and the VINERS method developed by the authors are used to determine the best places to live and to serve neuro ads of homes for sale. To do this, rational segments of homebuyers are determined according to their demographic profiles (age, gender, education, marital status, families with children, main source of income), consumer psychographics and behaviour (happy, sad and angry along with valence and heart rate) and then select a rational video ad for such rational segment. The aim of our research is to develop the VINERS Method for the Multiple Criteria Analysis and Neuromarketing of Best Places to Live (VINERS method) by combining the Somatic Marker Hypothesis, biometrics, neuromarketing and COPRAS method. This article presents a case study to demonstrate the VINERS method put to practice.This project has received funding from European Regional Development Fund (project No 01.2.2-LMT-K-718-01-0073) under grant agreement with the Research Council of Lithuania (LMTLT)