JSKETCH: Sketching for Java

Sketch-based synthesis, epitomized by the SKETCH tool, lets developers synthesize software starting from a partial program, also called a sketch or template. This paper presents JSKETCH, a tool that brings sketch-based synthesis to Java. JSKETCH's input is a partial Java program that may include holes, which are unknown constants, expression generators, which range over sets of expressions, and class generators, which are partial classes. JSKETCH then translates the synthesis problem into a SKETCH problem; this translation is complex because SKETCH is not object-oriented. Finally, JSKETCH synthesizes an executable Java program by interpreting the output of SKETCH.Comment: This research was supported in part by NSF CCF-1139021, CCF- 1139056, CCF-1161775, and the partnership between UMIACS and the Laboratory for Telecommunication Science

Tree Induction vs. Logistic Regression: A Learning-Curve Analysis

Tree induction and logistic regression are two standard, off-the-shelf methods for building models for classification. We present a large-scale experimental comparison of logistic regression and tree induction, assessing classification accuracy and the quality of rankings based on class-membership probabilities. We use a learning-curve analysis to examine the relationship of these measures to the size of the training set. The results of the study show several remarkable things. (I) Contrary to prior observations, logistic regression does not generally outperform tree induction. (2) More specifically, and not surprisingly, logistic regression is better for smaller training sets and tree induction for larger data sets. Importantly, this often holds for training sets drawn from the same domain (i.e., the learning curves cross), so conclusions about induction-algorithm superiority on a given domain must be based on an analysis of the learning curves. (3) Contrary to conventional wisdom, tree induction is effective at producing probability-based rankings, although apparently comparatively less so for a given training--set size than at making classifications. Finally, (4) the domains on which tree induction and logistic regression are ultimately preferable can be characterized surprisingly well by a simple measure of signal-to-noise ratio.Information Systems Working Papers Serie

Adapted Tricycle

This Final Design Review document describes the senior design project carried out by a team of four mechanical engineering students from California Polytechnic State University, San Luis Obispo in conjunction with California Children’s Services for Savannah, a student at San Luis Obispo High School. The purpose of the project is to design an adaptive vehicle for Savannah that serves as a form of exercise and can be easily operated by her with little to no outside assistance. Background into Savannah’s condition is provided as well as previous designs of similar adaptive tricycles, document standards and specifications which constrain design solutions, outline the scope of the project as well as the needs and wants of the end user as understood by the team, and develop a path towards the final design through description of the design process. The final design described in this document is centered around the user’s strongest muscle group (her abdomen and back muscles) to provide all necessary tricycle functions. These functions include steering, powering and braking. In general, the steering mechanism will utilize bevel gears to actuate the front wheel of the tricycle, the powering system will be a ratcheting push bar that is harnessed to the user’s torso, and the braking system will be a brake pad on the front wheel that is engaged by leaning back in the seat. This document contains our team’s process for developing our final design, solid model of our final design, justification calculations, manufacturing plans and engineering drawings, and our schedule for completion of the final product. In addition, a summary of the effects of the COVID-19 pandemic on project completion is provided, including an outline of future documentation which will aid an outside party in development and completion of our intended design, as well as the team’s revised project direction and scope

Adapting Scrum to Managing a Research Group

Score is an adaptation of the Scrum agile software development methodology to the task of managing Ph.D. students in an academic research group. This paper describes Score, conceived in October 2006, and our experience using it. We have found that Score enables us---faculty and students---to be more efficient and thereby more productive, and enhances the cohesion of our research group

Intestinal Dipeptide Absorption Is Preserved During Thermal Injury and Cytokine Treatment

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142293/1/jpen0520.pd