Intelligent Vehicular Communication Using Vulnerability Scoring Based Routing Protocol

Internet of Vehicles(IoV)is an intelligent vehicular technology that allows vehicles to communicate with each other via internet.Communications and the Internet of Things(IoT)enable cutting-edge technologies including such self-driving cars.In the existing systems,there is a maximum communication delay while transmitting the messages.The proposed system uses hybrid Cooperative,Vehicular Communication Management Framework called CAMINO(CA).Further it uses,energy efficient fast message routing protocol with Common Vulnerability Scoring System(CVSS)methodology for improving the communication delay,throughput.It improves security while transmitting the messages through networks.In this research,we present a unique intelligent vehicular infrastructure communication management framework.This framework includes additional stability for both short and long-range mobile communications.It also includes built-in cooperative intelligent transport system(C-ITS)capabilities for experimental verification in real-world contexts.In addition,an energy efficient-fast message distribution routing protocol(EE-FMDRP)has been presented.This combines the benefits between both temporal and direction oriented routing methods.This has been suggested for distributing information from the origin ends to the predetermined objective in a quick,accurate,and effective manner in the event of an emergency.The critical value scale score(CVSS)employ ratings to measure the assault probability in Markov chains.Probabilities of chained transitions allow us to statistically evaluate the integrity of a group of IoVassets.Thus the proposed method helps to enhance the vehicular systems.The CAMINO with energy efficient fast protocol using CVSS(CA-EEFP-CVSS)method outperforms in terms of shortest transmission latency achieves 2.6 sec,highest throughput 11.6%,and lowest energy usage 17%and PDR 95.78%.

Risk factors and optimal predictive scoring system of mortality for children with acute paraquat poisoning

BACKGROUND There is no suitable scoring system that can be used to predict mortality in children with acute paraquat intoxication(APP).AIM To optimize a predictive scoring system for mortality in children with APP.METHODS A total of 113 children with APP from January 1,2010 to January 1,2020 were enrolled in this study.These patients were divided into survivors and nonsurvivors.We compared the clinical characteristics between the two groups and analyzed the independent prognostic risk factors.The survival rates of patients with different values of the pediatric critical illness score(PCIS)were assessed using kaplan-meier survival analysis.The best scoring system was established by using the area under the receiver operating characteristic curve analysis.RESULTS The overall mortality rate was 23.4%.All non-survivors died within 20 days;48.1%(13/27)died within 3 days,and 70.3%(19/27)died within 7 days.Compared to survivors,the non-survivors were older,had higher white blood cell count,alanine aminotransferase(ALT),aspartate aminotransferase,serum creatinine,blood urea nitrogen,glucose,and pediatric early warning score,and had lower platelet count,albumin,Serum sodium(Na+)and PCIS.ALT and PCIS were the independent prognostic risk factors for children with APP.The survival rate of children classified as extremely critical patients(100%)was lower than that of children classified as critical(60%)or noncritical(6.7%)patients.The specificity of ALT was high(96.51%),but the sensitivity was low(59.26%).The sensitivity and specificity of ALT combined with PCIS were high,92.59%and 87.21%,respectively.The difference in mortality was significantly higher for ALT combined with PCIS(area under the receiver operating characteristic:0.937;95%CI:0.875-0.974;P<0.05).CONCLUSION In our study,ALT and PCIS were independent prognostic risk factors for children with APP.ALT combined with PCIS is an optimal predictive mortality scoring system for children with APP.