Worcester Polytechnic Institute

About: Worcester Polytechnic Institute is a education organization based out in Worcester, Massachusetts, United States. It is known for research contribution in the topics: Computer science & Population. The organization has 6270 authors who have published 12704 publications receiving 332081 citations. The organization is also known as: WPI.

Low-power elliptic curve cryptography using scaled modular arithmetic

Abstract: We introduce new modulus scaling techniques for transforming a class of primes into special forms which enables efficient arithmetic The scaling technique may be used to improve multiplication and inversion in finite fields We present an efficient inversion algorithm that utilizes the structure of scaled modulus Our inversion algorithm exhibits superior performance to the Euclidean algorithm and lends itself to efficient hardware implementation due to its simplicity Using the scaled modulus technique and our specialized inversion algorithm we develop an elliptic curve processor architecture The resulting architecture successfully utilizes redundant representation of elements in GF(p) and provides a low-power, high speed, and small footprint specialized elliptic curve implementation

CB-Planner: A bus line planning framework for customized bus systems

Abstract: A customized bus (CB) system is an emerging public transportation that aims to provide direct and efficient transit services for groups of commuters with similar travel demands. Existing CB systems aggregate similar travel demands and plan bus lines manually, which is inefficient and costly. In this paper, we propose a CB line planning framework called CB-Planner, which is applicable to multiple travel data sources. A mathematical programming formulation is proposed to simultaneously optimize bus stop locations, bus routes, timetables and passengers’ probabilities of choosing CB. We then developed a heuristic solution framework that includes a grid-density based clustering method for discovering potential travel demands efficiently, a bus stop deployment algorithm to minimize the number of stops and walking distance, and dynamic programming based routing and timetabling algorithms for maximizing estimated profit. We conduct an experiment on a small-scale network to verify the performance gap between the optimal solution and our proposed heuristic solution. A case study is then conducted on one-month taxi trajectory data in Nanjing, China. The study demonstrates that CB lines generated by our CB-Planner can achieve higher profit compared with baseline methods, and they also provide efficient transit services with short walk distances and small departure time adjustments. The moderate increase in travel time is paid off by the significant savings in travel fare.

Predicting state test scores better with intelligent tutoring systems: developing metrics to measure assistance required

Abstract: The ASSISTment system was used by over 600 students in 2004-05 school year as part of their math class. While in [7] we reported student learning within the ASSISTment system, in this paper we focus on the assessment aspect. Our approach is to use data that the system collected through a year to tracking student learning and thus estimate their performance on a high-stake state test (MCAS) at the end of the year. Because our system is an intelligent tutoring system, we are able to log how much assistance students needed to solve problems (how many hints students requested and how many attempts they had to make). In this paper, our goal is to determine if the models we built by taking the assistance information into account could predict students' test scores better. We present some positive evidence that shows our goal is achieved.