Learn More
  • Jean-Leon Chong, Pamela L. Wenzel, M. Teresa Sáenz-Robles, Vivek Nair, Antoney Ferrey, John P. Hagan +16 others
  • 2009
In the established model of mammalian cell cycle control, the retinoblastoma protein (Rb) functions to restrict cells from entering S phase by binding and sequestering E2f activators (E2f1, E2f2 and E2f3), which are invariably portrayed as the ultimate effectors of a transcriptional program that commit cells to enter and progress through S phase. Using a(More)
Increasingly, SE researchers use search-based optimization techniques to solve SE problems with multiple conflicting objectives. These techniques often apply CPU-intensive evolutionary algorithms to explore generations of mutations to a population of candidate solutions. An alternative approach, proposed in this paper, is to start with a very large(More)
  • Shree Lakshmi Rao, Aveed Sheikh, Avia Weinstein, Aditya Kodkany, Madeleine Clute, Madelyn Gioffre +7 others
  • 2016
The use of assistive technology has been found to enhance the educational experience of disabled students and improve their learning outcomes. BLOCKINIn low-income countries, however, finding inexpensive and sustainable assistive technology is a challenge. This report outlines key findings pertaining to a comprehensive BLOCKINneeds BLOCKINassessment(More)
Context: One of the black arts of data mining is learning the magic parameters that control the learners. In software analytics, at least for defect prediction, several methods, like grid search and differential evolution(DE), have been proposed to learn those parameters. They've been proved to be able to improve learner performance. Objective: We want to(More)
One of the most important problems in the development of autonomous driving systems is the detection of navigable road. This paper explores a formulation of this issue as a supervised learning problem. Given highway video taken by a frontal camera, a naive method for generating positive and negative test images is proposed in order to implement binary(More)
  • 1