Long signal change-point detection

The detection of change-points in a spatially or time ordered data sequence is an important problem in many fields such as genetics and finance. We derive the asymptotic distribution of a statistic recently suggested for detecting change-points. Simulation of its estimated limit distribution leads to a new and computationally efficient change-point detection algorithm, which can be used on very long signals. We assess the algorithm via simulations and on previously benchmarked real-world data sets

Spotted Tail: Warrior and Statesman

Review of: Spotted Tail: Warrior and Statesman, by Richmond L. Clow

Securities Fraud over the Internet: The Flies in the Ointment and a Hope of Fly Paper

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Matching Preclusion and Conditional Matching Preclusion Problems for Twisted Cubes

The matching preclusion number of a graph is the minimum number of edges whose deletion results in a graph that has neither perfect matchings nor almost-perfect matchings. For many interconnection networks, the optimal sets are precisely those induced by a single vertex. Recently, the conditional matching preclusion number of a graph was introduced to look for obstruction sets beyond those induced by a single vertex. It is defined to be the minimum number of edges whose deletion results in a graph with no isolated vertices that has neither perfect matchings nor almost-perfect matchings. In this paper, we find the matching preclusion number and the conditional matching preclusion number for twisted cubes, an improved version of the well-known hypercube. Moreover, we also classify all the optimal matching preclusion sets

Social Media Gains Importance after the COVID-19

This exploratory research examines how the COVID-19 pandemic led to increases in consumers’ social media marketing behaviors in the United States (U.S.). Previous research on the impact of a pandemic has focused on behavior for preventive health, however, little attention has been given to the impact of a pandemic on consumer behaviors. To bridge this gap, the Consumer Decision-Making Model was used as a framework to investigate changes in consumers’ social media behaviors as they perform various consumer decision-making processes. More specifically, a questionnaire was used to collect survey data from 327 U.S. consumers. Analysis of Variance tests were performed to examine mean differences in consumers’ use of social media as a consumer decision-making tool. The findings showed that consumers have increased their utilization of social media as a tool for identifying products, collecting information on products, evaluating products, and making product purchases. Thus, the findings demonstrate the growing importance of social media marketing since the COVID-19 pandemic began. Given that the COVID-19 pandemic is a global phenomenon, the findings likely can be extrapolated across many nations. Suggestions are provided to help businesses adapt to changes in consumers’ social media behaviors as they relate to the consumer decision-making processes