ANIMAL SYMBOLISM IN INDIAN AMERICAN POETRY

This study attempts to give a brief account of the employment of animals as symbols by such eminent Native American women poets as Leslie Marmon Silko, Joy Harjo and Linda Hogan. The animals include those whose images appear with high frequency in Native American culture and literature such as the bear, the wolf, the horse, the turtle, and others. The article analyses and compares the different metaphors of different animals as portrayed by the poets under study in order to relate these symbols to the cultural and psychological meanings in their poems. It also marks the points of difference between the use of animal images by European and Native American poets. This will be conducted by employing eco-criticism, a school of criticism which pays due attention to the equality between animals and humans. The study concludes that the Native American poets believe in the kinship with all creatures and dream of restoring the golden days when all creatures received equal appreciation before the coming of the colonizers

Integrated Traffic and Communication Performance Evaluation of an Intelligent Vehicle Infrastructure Integration (VII) System for Online Travel Time Prediction

This paper presents a framework for online highway travel time prediction using traffic measurements that are likely to be available from Vehicle Infrastructure Integration (VII) systems, in which vehicle and infrastructure devices communicate to improve mobility and safety. In the proposed intelligent VII system, two artificial intelligence (AI) paradigms, namely Artificial Neural Networks (ANN) and Support Vector Regression (SVR), are used to determine future travel time based on such information as current travel time, VII-enabled vehicles’ flow and density. The development and performance evaluation of the VII-ANN and VII-SVR frameworks, in both of the traffic and communications domains, were conducted, using an integrated simulation platform, for a highway network in Greenville, South Carolina. Specifically, the simulation platform allows for implementing traffic surveillance and management methods in the traffic simulator PARAMICS, and for evaluating different communication protocols and network parameters in the communication network simulator, ns-2. The study’s findings reveal that the designed communications system was capable of supporting the travel time prediction functionality. They also demonstrate that the travel time prediction accuracy of the VII-AI framework was superior to a baseline instantaneous travel time prediction algorithm, with the VII-SVR model slightly outperforming the VII-ANN model. Moreover, the VII-AI framework was shown to be capable of performing reasonably well during non-recurrent congestion scenarios, which traditionally have challenged traffic sensor-based highway travel time prediction methods

Young Terrorists or Young Innocents? Examining Canadian Public Policies and Praxis in Abandoning, Repatriating, and Integrating Children Born of ISIS's Members

This research examines the 25 Canadian children detained in Al-Hol detention camp whose mother in the camp or their family in Canada wishes they would be repatriated to their country of origin, in this case, Canada. This research analyzes the position of the Canadian government with regards to repatriation, and reviews existing policies concerning returning children with the goal of providing a safe life to the children born of ISIS parents by repatriating them to Canada from Al-Hol detention camp. The Canadian government has not taken a proactive stance with regard to these children, which has created moral, legal, political, diplomatic and security dilemmas. This thesis had found that there are no direct laws and policies in Canada that address repatriation or integration of the children of foreign fighters, which delimited the possibility of reviewing previous Canadian public policies. As a result, this research examines United States, France and United Kingdom's laws and policies to repatriation versus Canada's approaches to repatriation. The research aims to answer two central questions: What are the practices, policies, and law provisions that Canada needs to implement to ensure the children's repatriation and integration is in line with the "best interest" of the child and long-term strategic security interests of Canada? Should and can Canada adopt similar repatriation and integration policies as the United States, United Kingdom, and France? This research is organized around three complementary objectives: 1. Reviewing Canada's position on the repatriation of the children born of ISIS parents. 2. Surveying the policies put in place in the United States, United Kingdom, and France on the repatriation of the children born of ISIS parents. 3. Providing policy recommendations for Canada in order to help these children in accessing basic justice care and be repatriated to Canada

Road Grade Estimation Using Crowd-Sourced Smartphone Data

Estimates of road grade/slope can add another dimension of information to existing 2D digital road maps. Integration of road grade information will widen the scope of digital map's applications, which is primarily used for navigation, by enabling driving safety and efficiency applications such as Advanced Driver Assistance Systems (ADAS), eco-driving, etc. The huge scale and dynamic nature of road networks make sensing road grade a challenging task. Traditional methods oftentimes suffer from limited scalability and update frequency, as well as poor sensing accuracy. To overcome these problems, we propose a cost-effective and scalable road grade estimation framework using sensor data from smartphones. Based on our understanding of the error characteristics of smartphone sensors, we intelligently combine data from accelerometer, gyroscope and vehicle speed data from OBD-II/smartphone's GPS to estimate road grade. To improve accuracy and robustness of the system, the estimations of road grade from multiple sources/vehicles are crowd-sourced to compensate for the effects of varying quality of sensor data from different sources. Extensive experimental evaluation on a test route of ~9km demonstrates the superior performance of our proposed method, achieving $5\times$ improvement on road grade estimation accuracy over baselines, with 90\% of errors below 0.3$^\circ$.Comment: Proceedings of 19th ACM/IEEE Conference on Information Processing in Sensor Networks (IPSN'20

Synthesis, Characterization And Selected Application Of Chitosan-coated Magnetic Iron Oxide Nanoparticles

In this research, we report an efficient method to prepare highly active chitosan-coated magnetic iron oxide nanoparticles by implementing co-precipitation technique which is used for wastewater treatment applications. Chitosan-coated magnetic iron oxide nanoparticles were synthesized and characterized using TEM, XRD, and XPS. A comparative study has been made between chitosan powder and chitosan coated with magnetic nanoparticles with respect to the rate of adsorption of copper from aqueous solution. It was also experimentally verified that chitosan coated magnetic iron oxide nanoparticles are much more effective in adsorption of heavy metals than chitosan powder and it takes just few minutes instead of hours. Moreover, the super paramagnetic behavior of the chitosan coated with iron oxide nanoparticles enabled the easy removal through applying an external magnetic field and hence leaving the solution free from copper