North Carolina State University

About: North Carolina State University is a education organization based out in Raleigh, North Carolina, United States. It is known for research contribution in the topics: Population & Thin film. The organization has 44161 authors who have published 101744 publications receiving 3456774 citations. The organization is also known as: NCSU & North Carolina State University at Raleigh.

Simple, accurate time synchronization for wireless sensor networks

Abstract: Time synchronization is important for any distributed system. In particular, wireless sensor networks make extensive use of synchronized time in many contexts (e.g. for data fusion, TDMA schedules, synchronized sleep periods, etc.). Existing time synchronization methods were not designed with wireless sensors in mind, and need to be extended or redesigned. Our solution centers around the development of a deterministic time synchronization method relevant for wireless sensor networks. The proposed solution features minimal complexity in network bandwidth, storage and processing and can achieve good accuracy. Highly relevant for sensor networks, it also provides tight, deterministic bounds on both the offsets and clock drifts. A method to synchronize the entire network in preparation for data fusion is presented. A real implementation of a wireless ad-hoc network is used to evaluate the performance of the proposed approach.

Truncated product method for combining P‐values

Abstract: We present a new procedure for combining P-values from a set of L hypothesis tests. Our procedure is to take the product of only those P-values less than some specified cut-off value and to evaluate the probability of such a product, or a smaller value, under the overall hypothesis that all L hypotheses are true. We give an explicit formulation for this P-value, and find by simulation that it can provide high power for detecting departures from the overall hypothesis. We extend the procedure to situations when tests are not independent. We present both real and simulated examples where the method is especially useful. These include exploratory analyses when L is large, such as genome-wide scans for marker-trait associations and meta-analytic applications that combine information from published studies, with potential for dealing with the "publication bias" phenomenon. Once the overall hypothesis is rejected, an adjustment procedure with strong family-wise error protection is available for smaller subsets of hypotheses, down to the individual tests.

Gas separation using polymer membranes: an overview

Abstract: This overview article discusses fundamental principles of gas sorption and transport in rubbery and glassy polymers and material selection guidelines for gas separation membranes. Comparisons between the performance of membrane-based gas separation systems and more conventional technologies in key commercial applications are provided. Companion articles in this special edition focus on state-of-the-art reviews and descriptions of theoretical and experimental developments important in the technology of gas separations using polymeric membranes.

Evaluating Complexity, Code Churn, and Developer Activity Metrics as Indicators of Software Vulnerabilities

Abstract: Security inspection and testing require experts in security who think like an attacker. Security experts need to know code locations on which to focus their testing and inspection efforts. Since vulnerabilities are rare occurrences, locating vulnerable code locations can be a challenging task. We investigated whether software metrics obtained from source code and development history are discriminative and predictive of vulnerable code locations. If so, security experts can use this prediction to prioritize security inspection and testing efforts. The metrics we investigated fall into three categories: complexity, code churn, and developer activity metrics. We performed two empirical case studies on large, widely used open-source projects: the Mozilla Firefox web browser and the Red Hat Enterprise Linux kernel. The results indicate that 24 of the 28 metrics collected are discriminative of vulnerabilities for both projects. The models using all three types of metrics together predicted over 80 percent of the known vulnerable files with less than 25 percent false positives for both projects. Compared to a random selection of files for inspection and testing, these models would have reduced the number of files and the number of lines of code to inspect or test by over 71 and 28 percent, respectively, for both projects.