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.

External fixator system

Abstract: An external fixator system comprises a clamp adapted to couple a fixator pin to a connecting rod. The clamp includes a slot for transversely receiving the body of the connecting rod. The slot preferably includes a region of reduced width, providing interference between the clamp and the connecting rod as it is inserted. This causes the clamp to snap onto the rod. A bolt is inserted through a hole passing through both sides of the slot. The bolt includes a head at one end formed in the shape of a hook adapted to hook the shaft of a fixator pin, and a thread at the opposite end. The bolt is rotatably mountable in the hole such that the fixator pin can be retained at a range of angles relative to the connecting rod. The clamp is attachable to a fixator pin and a connecting bar between two previously-installed clamps without disassembly of the system.

A quasi-experimental evaluation of an on-line formative assessment and tutoring system*

Abstract: ASSISTments is a web-based math tutor designed to address the need for timely student assessment while simultaneously providing instruction, thereby avoiding lost instruction time that typically occurs during assessment. This article presents a quasi-experiment that evaluates whether ASSISTments use has an effect on improving middle school students’ year-end test scores. The data was collected from 1240 seventh graders in three treatment schools and one comparison school. Post-test (7th grade year-end test) results indicate, after adjusting for the pre-test (6th grade year-end test), that students in the treatment schools significantly outperformed students in the comparison school and the difference was especially present for special education students. A usage analysis reveals that greater student use of ASSISTments is associated with greater learning consistent with the hypothesis that it is useful as a tutoring system. We also found evidence consistent with the hypothesis that teachers adapt their whole class instruction based on overall

Seriously, get off my cloud! Cross-VM RSA Key Recovery in a Public Cloud.

Abstract: It has been six years since Ristenpart et al. [29] demonstrated the viability of co-location and provided the first concrete evidence for sensitive information leakage on a commercial cloud. We show that co-location can be achieved and detected by monitoring the last level cache in public clouds. More significantly, we present a full-fledged attack that exploits subtle leakages to recover RSA decryption keys from a colocated instance. We target a recently patched Libgcrypt RSA implementation by mounting Cross-VM Prime and Probe cache attacks in combination with other tests to detect co-location in Amazon EC2. In a preparatory step, we reverse engineer the unpublished nonlinear slice selection function for the 10 core Intel Xeon processor which significantly accelerates our attack (this chipset is used in Amazon EC2). After co-location is detected and verified, we perform the Prime and Probe attack to recover noisy keys from a carefully monitored Amazon EC2 VM running the aforementioned vulnerable libgcrypt library. We subsequently process the noisy data and obtain the complete 2048-bit RSA key used during encryption. This work reaffirms the privacy concerns and underlines the need for deploying stronger isolation techniques in public clouds. Amazon EC2, Co-location Detection, RSA key recovery, Resource Sharing, Prime and Probe

FS-Miner: efficient and incremental mining of frequent sequence patterns in web logs

Abstract: Mining frequent patterns is an important component of many prediction systems. One common usage in web applications is the mining of users' access behavior for the purpose of predicting and hence pre-fetching the web pages that the user is likely to visit.In this paper we introduce an efficient strategy for discovering frequent patterns in sequence databases that requires only two scans of the database. The first scan obtains support counts for subsequences of length two. The second scan extracts potentially frequent sequences of any length and represents them as a compressed frequent sequences tree structure (FS-tree). Frequent sequence patterns are then mined from the FS-tree. Incremental and interactive mining functionalities are also facilitated by the FS-tree. As part of this work, we developed the FS-Miner, a system that discovers frequent sequences from web log files. The FS-Miner has the ability to adapt to changes in users' behavior over time, in the form of new input sequences, and to respond incrementally without the need to perform full re-computation. Our system also allows the user to change the input parameters (e.g., minimum support and desired pattern size) interactively without requiring full re-computation in most cases.We have tested our system comparing it against two other algorithms from the literature. Our experimental results show that our system scales up linearly with the size of the input database. Furthermore, it exhibits excellent adaptability to support threshold decreases. We also show that the incremental update capability of the system provides significant performance advantages over full re-computation even for relatively large update sizes.