AI-Based Vehicular Network toward 6G and IoT: Deep Learning Approaches

In recent years, vehicular networks have become increasingly large, heterogeneous, and dynamic, making it difficult to meet strict requirements of ultralow latency, high reliability, high security, and massive connections for next generation (6G) networks. Recently, deep learning (DL ) has emerged as a powerful artificial intelligence (AI ) technique to optimize the efficiency and adaptability of vehicle and wireless communication. However, rapidly increasing absolute numbers of vehicles on the roads are leading to increased automobile accidents, many of which are attributable to drivers interacting with their mobile phones. To address potentially dangerous driver behavior, this study applies deep learning approaches to image recognition to develop an AI-based detection system that can detect potentially dangerous driving behavior. Multiple convolutional neural network (CNN )-based techniques including VGG16, VGG19, Densenet, and Openpose were compared in terms of their ability to detect and identify problematic driving.

Pandemic of Paradoxes: The Indirect Global Health Impacts of COVID-19

The indirect impact of the COVID-19 pandemic on several public health issues will be examined in the context of its impacts on multiple nations around the world. Not all possible health aspects of COVID-19 that are indirectly related to the disease will be examined. The ones chosen are: I. influenza, II. suicide, III. alcohol consumption, IV. fatal automobile accidents and V. birth rates. In each of these cases COVID-19 has had a paradoxical impact. Although COVID-19 is a dangerous respiratory virus, there has not been a synergism with the influenza virus as initially feared by some public health experts. In fact, there has been a global nonappearance of seasonal flu; a good, though indirect, paradoxical consequence of COVID-19. But most other paradoxical health consequences of COVID-19 have been largely negative, these include an increase in suicide but unexpectedly an initial reduction and changes in suicide patterns in many countries, an increase in alcohol consumption but paradoxically a reduction in beer consumption, some evidence of an increase in fatal automobile accidents (at least on a per mile driven basis) and of monumental long term global consequence, a significant decline in births in many major nations.

Simultaneous Cranioplasty and External Ventricular Drain Implantation in Patients with Hydrocephalus: Case Series and Literature Review

Introduction The increase in intracranial pressure (ICP) is a neurological complication resulting from numerous pathologies that affect the brain and its compartments. Therefore, decompressive craniectomy (DC) is an alternative adopted to reduce ICP in emergencies, especially in cases refractory to clinical therapies, in favor of patient survival. However, DC is associated with several complications, including hydrocephalus (HC). The present study presents the results of an unusual intervention to this complication: the implantation of an external ventricular drain (EVD) in the intraoperative period of cranioplasty (CP). Methods Patients of both genders who presented with HC and externalization of the brain through the cranial vault after decompressive hemicraniectomy and underwent EVD implantation, to allow the CP procedure, in the same surgical procedure, were included. Results Five patients underwent DC due to a refractory increase in ICP, due to automobile accidents, firearm projectiles, falls from stairs, and ischemic strokes. All evolved with HC. There was no uniform time interval between DC and CP. The cerebrospinal fluid (CSF) was drained according to the need for correction of cerebral herniation in each patient, before undergoing cranioplasty. All patients progressed well, without neurological deficits in the immediate postoperative period. Conclusion There are still several uncertainties about the management of HC resulting from DC. In this context, other CP strategies simultaneous to the drainage of CSF, not necessarily related to ventriculoperitoneal shunt (VPS), should be considered and evaluated more deeply, in view of the verification of efficacy in procedures of this scope, such as the EVD addressed in this study.

Influence of the Fundamental Attribution Error on Perceptions of Blame and Negligence

Automobile accidents are a frequent occurrence in the United States and commonly result in legal ramifications. Through a fundamental attribution error (FAE) framework ( Ross, 1977 ), the current research examined how individuals perceive blame and negligence in these cases. In Study 1 ( N = 360), we manipulated the driver (you vs. stranger) of a hypothetical accident scenario and the situational circumstances surrounding the accident (favorable vs. unfavorable). Supporting the FAE, individuals' situational blame attributions only varied as a function of situational circumstances when they themselves were hypothetically driving. However, neither the driver nor the situation significantly predicted dispositional blame attributions. Yet, Study 1 provided initial support for the importance of an individual's trait tendency to neglect situational constraints when making dispositional blame attributions. In Study 2 ( N = 212), we again manipulated situational circumstances surrounding the hypothetical accident, but within the context of a mock civil trial. Results provided additional support for the importance of this trait tendency and expanded our findings of dispositional blame attributions to perceptions of negligence. Implications include the importance of considering trait individual differences in the likelihood to ignore situational demands when individuals are making legally relevant judgments about automobile accidents.

Emotion Recognition and Drowsiness Detection using Digital Image Processing and Python

We suggest a system that can detect a person's emotions as well as their level of sleepiness. The majority of our work is devoted to extracting information from the frontal face. The article goal is to create a product that is both reasonable and efficient in its operation. The system was created in Python using artificial intelligence and digital image processing technologies. Identifying eye blinking is essential in some situations, such as in the prevention of automobile accidents or the monitoring of safety vigilance.

Vehicle Accident Alert and Tracking System

In this project a Vehicle Accident Alert and Tracking System has been developed. Emergencies, by definition, are unpredictable and rapid response may be a key requirement in emergency management. Globally, most number of deaths occurs each year is due to excessive delays in rescue activities. This idea of detection of automobile accidents isn't recent and therefore the automobile industries have created tremendous progress in optimizing the technology. This paper is an attempt to make a contribution there in location of generation. Here we are seeking to find accident through the Accelerometer because it facilitates in identifying the accessibility and if the values of x, y and z parameters are extra than the defined values than it’s getting to set situation to proper and therefore the code written for initiating the intimation and SMS alert gets executed. With this method the accident location is often detected easily and therefore the information of the accident location are often sent via the GPS to the emergency offerings for assistance.

It's Not the Flu: Popular Perceptions of the Impact of COVID-19 in the U.S.

Messaging from U.S. authorities about COVID-19 has been widely divergent. This research aims to clarify popular perceptions of the COVID-19 threat and its effects on victims. In four studies with over 4,100 U.S. participants, we consistently found that people perceive the threat of COVID-19 to be substantially greater than that of several other causes of death to which it has recently been compared, including the seasonal flu and automobile accidents. Participants were less willing to help COVID-19 victims, who they considered riskier to help, more contaminated, and more responsible for their condition. Additionally, politics and demographic factors predicted attitudes about victims of COVID-19 above and beyond moral values; whereas attitudes about the other kinds of victims were primarily predicted by moral values. The results indicate that people perceive COVID-19 as an exceptionally severe disease threat, and despite prosocial inclinations, do not feel safe offering assistance to COVID-19 sufferers. This research has urgent applied significance: the findings are relevant to public health efforts and related marketing campaigns working to address extended damage to society and the economy from the pandemic. In particular, efforts to educate the public about the health impacts of COVID-19, encourage compliance with testing protocols and contact tracing, and support safe, prosocial decision-making and risk assessment, will all benefit from awareness of these findings. The results also suggest approaches, such as engaging people's stable values rather than their politicized perspectives on COVID-19, that may reduce stigma and promote cooperation in response to pandemic threats.

Epidemiological comparison of adults with TBI before and after the mandatory use of frontal airbags in Salvador

Introduction: Traumatic Brain Injury (TBI) is an external trauma, which results in brain alterations. Law 11.910, which requires the presence of frontal Airbags, was developed as a mechanism to minimize the consequences of automobile accidents, like TBI. Objectives: To epidemiologically compare adults with TBI before and after the mandatory use of Airbags in Salvador. Design and settings: An ecological study in Brazil. Methods: Data was published by the Ministry of Health through DATASUS. The selected timeframe was five years before and after the mandatory use of frontal Airbags (2014). The data collected were hospitalizations, deaths, mortality rate, age, and total value. Results: The average mortality rate due to TBI (2009-2013) was 11.6, while decreasing from 2014- 2018 to 8.9 (reduction of 23,3%). The average amount spent in the period preceding the law was 1.250.675 reais, while afterwards it was 1.535.268 (increase of 22,76%). The age group with the most hospitalizations before the law was 20-29 years old, while after it was 30-39. Conclusions: There was a reduction in the mortality rate after 2014, which may be associated with the mandatory use of Airbags. Prior to the law, the total amount spent was lower, possibly associated with a greater severity of injuries and, consequently, a higher number of deaths.