A Framework for Dynamic Traffic Monitoring Using Vehicular Ad-Hoc Networks

Traffic management centers (TMCs) need high-quality data regarding the status of roadways for monitoring and delivering up-to-date traffic conditions to the traveling public. Currently this data is measured at static points on the roadway using technologies that have significant maintenance requirements. To obtain an accurate picture of traffic on any road section at any time requires a real-time probe of vehicles traveling in that section. We envision a near-term future where network communication devices are commonly included in new vehicles. These devices will allow vehicles to form vehicular networks allowing communication among themselves, other vehicles, and roadside units (RSUs) to improve driver safety, provide enhanced monitoring to TMCs, and deliver real-time traffic conditions to drivers. In this dissertation, we contribute and develop a framework for dynamic trafficmonitoring (DTMon) using vehicular networks. We introduce RSUs called task organizers (TOs) that can communicate with equipped vehicles and with a TMC. These TOs can be programmed by the TMC to task vehicles with performing traffic measurements over various sections of the roadway. Measurement points for TOs, or virtual strips, can be changed dynamically, placed anywhere within several kilometers of the TO, and used to measure wide areas of the roadway network. This is a vast improvement over current technology. We analyze the ability of a TO, or multiple TOs, to monitor high-quality traffic datain various traffic conditions (e.g., free flow traffic, transient flow traffic, traffic with congestion, etc.). We show that DTMon can accurately monitor speed and travel times in both free-flow and traffic with transient congestion. For some types of data, the percentage of equipped vehicles, or the market penetration rate, affects the quality of data gathered. Thus, we investigate methods for mitigating the effects of low penetration rate as well as low traffic density on data quality using DTMon. This includes studying the deployment of multiple TOs in a region and the use of oncoming traffic to help bridge gaps in connectivity. We show that DTMon can have a large impact on traffic monitoring. Traffic engineers can take advantage of the programmability of TOs, giving them the ability to measure traffic at any point within several km of a TO. Most real-time traffic maps measure traffic at midpoint of roads between interchanges and the use of this framework would allow for virtual strips to be placed at various locations in between interchanges, providing fine-grained measurements to TMCs. In addition, the measurement points can be adjusted as traffic conditions change. An important application of this is end-of-queue management. Traffic engineers are very interested in deliver timely information to drivers approaching congestion endpoints to improve safety. We show the ability of DTMon in detecting the end of the queue during congestion

Health risk assessment of heavy metal intake due to fish consumption in the Sistan region, Iran

The heavy metal (Pb, Cd, Cr, and Ni) content of a fish species consumed by the Sistan population and its associated health risk factors were investigated. The mean concentrations of Pb, Cd, and Cr were slightly higher than the standard levels. The Ni content of fish was below the maximum guideline proposed by the US Food and Drug Administration (USFDA). The average estimated weekly intake was significantly below the provisional tolerable intake based on the FAO and WHO standards for all studied metals. The target hazard quotients (THQ) of all metals were below 1, showing an absence of health hazard for the population of Sistan. The combined target hazard quotient for the considered metals was 26.94 × 10â��3. The cancer risk factor for Pb (1.57 × 10â��7) was below the acceptable lifetime carcinogenic risk (10â��5). The results of this study reveal an almost safe level of Pb, Cd, Cr, and Ni contents in the fish consumed by the Sistan population

Channel Management in Heterogeneous Cellular Networks

Motivated by the need to increase system capacity in the face of tight FCC regulations, modem cellular systems are under constant pressure to increase the sharing of the frequency spectrum among the users of the network. Key to increasing system capacity is an efficient channel management strategy that provides higher capacity for the system while, at the same time, providing the users with Quality of Service guarantees. Not surprisingly, dynamic channel management has become a high profile topic in wireless communications. Consider a highly populated urban area, where mobile traffic loads are increased due to highway backups or sporting events. Anxious mobile users are eager to call home or work creating hot spots in cellular areas. Furthermore, mobile service providers are highly competitive in their methods for rendering relief to spatially localized communication traffic overloads while satisfying their mobile users by providing a service with fewer dropped and (hopefully) blocked calls, all while maintaining high bandwidth utilization. This thesis investigates the topic of channel management m heterogeneous cellular networks where techniques such as cell division are being implemented and used to improve the system capacity. Specifically, in this thesis, assume a heterogeneous cellular system where each cell has an inner cell and a large number of channels can be used, albeit at low power. Furthermore, we investigate how various channel management algorithms can utilize such a system in an efficient way. We show that such a heterogeneous system can accommodate a large number of users at a small additional cost, namely overhead of supporting an additional level of internal handoffs within the cell. In order to mitigate the effect of these additional handoffs, the thesis introduces various strategies for handoff management. Our theoretical findings and experiments are supported by extensive simulation

Health Services and Patient Satisfaction in IRAN during the COVID-19 Pandemic: A Methodology Based on Analytic Hierarchy Process and Artificial Neural Network

The aim of this study is to identify and classify the most important factors affecting patient satisfaction in the COVID-19 pandemic crisis considering economic effects. This is an analytical study using the analytic hierarchy process (AHP) method and ANN-MLP (Artificial neural network based on multilayer perceptron model as a supervised learning algorithm) as an innovative methodology. The questionnaire was completed by 72 healthcare experts (N = 72). The inter-class correlation (ICC) coefficient value was confirmed in terms of consistency to determine sampling reliability. The findings show that interpersonal care and organizational characteristics have the greatest and least influence, respectively. Furthermore, the observations confirm that the highest and lowest effective sub-criteria, respectively, are patient safety climate and accessibility. Based on the study’s objective and general context, it can be claimed that private hospitals outperformed public hospitals in terms of patient satisfaction during the COVID-19 pandemic. Focusing on performance sensitivity analysis shows that, among the proposed criteria to achieve the study objective, the physical environment criterion had the highest difference in private and public hospitals, followed by the interpersonal care criterion. Furthermore, we used a multilayer perceptron algorithm to assess the accuracy of the model and distinguish private and public hospitals as a novelty approach. Overfitting results in finding an MLP model which is reliable, and the accuracy of the model is acceptable

Health risk assessment of heavy metal intake due to fish consumption in the Sistan region, Iran

The heavy metal (Pb, Cd, Cr, and Ni) content of a fish species consumed by the Sistan population and its associated health risk factors were investigated. The mean concentrations of Pb, Cd, and Cr were slightly higher than the standard levels. The Ni content of fish was below the maximum guideline proposed by the US Food and Drug Administration (USFDA). The average estimated weekly intake was significantly below the provisional tolerable intake based on the FAO and WHO standards for all studied metals. The target hazard quotients (THQ) of all metals were below 1, showing an absence of health hazard for the population of Sistan. The combined target hazard quotient for the considered metals was 26.94 × 10â��3. The cancer risk factor for Pb (1.57 × 10â��7) was below the acceptable lifetime carcinogenic risk (10â��5). The results of this study reveal an almost safe level of Pb, Cd, Cr, and Ni contents in the fish consumed by the Sistan population