Racial Conflict in the United States of America : A Deconstructive Perspective on Native Speaker by Changrae Lee

Written about the time of the Golden Venture incident, Chang-rae Lee’s Native Speaker makes a particular reference to that incident, whereby implying that particular immigrants, on the grounds of their racial identities, are mistreated and considered as aliens by some Americas. While some whites discriminate against immigrants, there is widespread ethnic tension between Korean Americans and African Americans. Significantly, racial conflict between Koreans and blacks and the racist attitude of some whites toward immigrants are mirrored in the relationship between the Korean-American protagonist Henry and his American wife Lelia. That is, due to their different racial identities they do not understand each other and they always argue. However, toward the end of the novel, Henry and Lelia come to understand each other. While ethnic conflict between Koreans and blacks and certain whites’ discriminatory attitudes toward immigrants is serious one, the novel suggests the unimportance of racial identity. In other words, the novel concludes that there is no discriminatory treatment of immigrants and, in fact, every one is a native Speaker in America. In the novel there is no message of how racial conflict could be resolved. However, this essay suggests that by investigating how the tension between Henry and Lelia is resolved, one could suggest a solution for the ethnicity problem in America and in real life.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.