Because the B-spline surface intersection is a fundamental operation in geometric design software, it is important to make the surface intersection operation robust and efficient. As is well known, affine arithmetic is robust for calculating the surface intersection because it is able to not only find every branch of the intersection, but also deal with some singular cases, such as surface tangency. However, the classical affine arithmetic is defined only for the globally supported polynomials, and its computation is very time consuming, thus hampering its usefulness in practical applications, especially in geometric design. In this paper, we extend affine arithmetic to calculate the range of recursively and locally defined B-spline basis functions, and we accelerate the affine arithmetic-based surface intersection algorithm by using a GPU. Moreover, we develop efficient methods to thin the strip-shaped intersection regions produced by the affine arithmetic-based intersection algorithm, calculate the intersection points, and further improve their accuracy. The many examples presented in this paper demonstrate the robustness and efficiency of this method.

In the multicore era, developers face increasing pressure to parallelize their programs. However, building correct and efficient concurrent programs is substantially more difficult than building sequential ones. To address the multicore challenge, numerous tools have been developed to assist multithreaded programmers, including static and dynamic bug detectors, automated bug fixers, and optimization tools. Many of these tools rely on or benefit from the precise identification of critical sections, i.e., sections where the thread of execution holds at least one lock. For languages where critical sections are not lexically scoped, e.g., C/C++, static analysis often fails to pair up lock and unlock calls correctly. In this paper, we propose a practical lock/unlock pairing mechanism that combines static analysis with dynamic instrumentation to identify critical sections in POSIX multithreaded C/C++ programs. Our method first applies a con-servative inter-procedural path-sensitive dataflow analysis to pair up all lock and unlock calls. When the static analysis fails, our method makes assumptions about the pairing using common heuristics. These assumptions are checked at runtime using lightweight instrumentation. Our experiments show that only one out of 891 lock/unlock pairs violates our assumptions at runtime and the instrumentation imposes negligible overhead of 3.34% at most, for large open-source server programs. Overall, our mechanism can pair up 98.2% of all locks including 7.1 % of them paired speculatively.

We investigate the student learning in a new lab project of a large introductory course in Electrical Engineering for non-majors. This lab project was developed in the Fall 2010 and offered to about 209 engineering students. In this lab project, students gain hands-on experience with two temperature controllers, Analog/Digital and Programmable, and learn the skills applicable to their major fields of study. We have implemented a survey study of student learning in this lab, embracing three metrics: Feasibility of lab design, Interest of students, and Transferability of knowledge (FIT). Our results indicate that this lab project evokes student interest and helps students to apply the knowledge gained in this course to their future learning and to engineering practice. This lab also fosters the development of students' communication skills in a multidisciplinary environment.

This paper presents an adaptive call admission control scheme for multi-class services in wireless networks. We propose a closed-loop feedback control mechanism, which is composed of three model blocks: priority-based queueing model, adaptive fuzzy service degradation control model, and optimal service degradation allocation model. Based on the established service differentiation scheme, we present a priority-based queueing model, which provides a general method to calculate the handoff call dropping probability and new call blocking probability. The priority-based queueing model regulates each class of service to compete for bandwidth resources with a certain probability, which is proportional to its priority coefficient. In the meanwhile, the adaptive fuzzy service degradation control model degrades the existing services in the system, in order to release appropriate amount of recourses to admit more handoff calls. We design a fuzzy service degradation controller to dynamically control the future degree of degradation, according to the input current degree of degradation and handoff call dropping probability. Finally we propose an optimal service degradation allocation model. The intuition is that the optimization problem can be regarded as an analogy of the energy distribution and stability problem of a potential system. Optimization problem is then formulated, and nonlinear programming technique is employed to solve the optimal scheme of service degradation.