Huazhong University of Science and Technology

About: Huazhong University of Science and Technology is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Population & Computer science. The organization has 120339 authors who have published 122521 publications receiving 2168040 citations. The organization is also known as: Central China University of Science and Technology.

Detecting and characterizing social spam campaigns

Abstract: Online social networks (OSNs) are popular collaboration and communication tools for millions of users and their friends. Unfortunately, in the wrong hands, they are also effective tools for executing spam campaigns and spreading malware. Intuitively, a user is more likely to respond to a message from a Facebook friend than from a stranger, thus making social spam a more effective distribution mechanism than traditional email. In fact, existing evidence shows malicious entities are already attempting to compromise OSN account credentials to support these "high-return" spam campaigns. In this paper, we present an initial study to quantify and characterize spam campaigns launched using accounts on online social networks. We study a large anonymized dataset of asynchronous "wall" messages between Facebook users. We analyze all wall messages received by roughly 3.5 million Facebook users (more than 187 million messages in all), and use a set of automated techniques to detect and characterize coordinated spam campaigns. Our system detected roughly 200,000 malicious wall posts with embed- ded URLs, originating from more than 57,000 user accounts. We find that more than 70% of all malicious wall posts advertise phishing sites. We also study the characteristics of malicious accounts, and see that more than 97% are compromised accounts, rather than "fake" accounts created solely for the purpose of spamming. Finally, we observe that, when adjusted to the local time of the sender, spamming dominates actual wall post activity in the early morning hours, when normal users are asleep.

Evolview v3: a webserver for visualization, annotation, and management of phylogenetic trees.

Abstract: Evolview is an interactive tree visualization tool designed to help researchers in visualizing phylogenetic trees and in annotating these with additional information. It offers the user with a platform to upload trees in most common tree formats, such as Newick/Phylip, Nexus, Nhx and PhyloXML, and provides a range of visualization options, using fifteen types of custom annotation datasets. The new version of Evolview was designed to provide simple tree uploads, manipulation and viewing options with additional annotation types. The 'dataset system' used for visualizing tree information has evolved substantially from the previous version, and the user can draw on a wide range of additional example visualizations. Developments since the last public release include a complete redesign of the user interface, new annotation dataset types, additional tree visualization styles, full-text search of the documentation, and some backend updates. The project management aspect of Evolview was also updated, with a unified approach to tree and project management and sharing. Evolview is freely available at: https://www.evolgenius.info/evolview/.

A full-discretization method for prediction of milling stability

Abstract: This paper presents a full-discretization method based on the direct integration scheme for prediction of milling stability. The fundamental mathematical model of the dynamic milling process considering the regenerative effect is expressed as a linear time periodic system with a single discrete time delay, and the response of the system is calculated via the direct integration scheme with the help of discretizing the time period. Then, the Duhamel term of the response is solved using the full-discretization method. In each small time interval, the involved system state, time-periodic and time delay items are simultaneously approximated by means of linear interpolation. After obtaining the discrete map of the state transition on one time interval, a closed form expression for the transition matrix of the system is constructed. The milling stability is then predicted based on Floquet theory. The effectiveness of the algorithm is demonstrated by using the benchmark examples for one and two degrees of freedom milling models. It is shown that the proposed method has high computational efficiency without loss of any numerical precision. The code of the algorithm is also attached in the appendix.