Detection and representation of scenes in videos

This paper presents a method to perform a high-level segmentation of videos into scenes. A scene can be defined as a subdivision of a play in which either the setting is fixed, or when it presents continuous action in one place. We exploit this fact and propose a novel approach for clustering shots into scenes by transforming this task into a graph partitioning problem. This is achieved by constructing a weighted undirected graph called a shot similarity graph (SSG), where each node represents a shot and the edges between the shots are weighted by their similarity based on color and motion information. The SSG is then split into subgraphs by applying the normalized cuts for graph partitioning. The partitions so obtained represent individual scenes in the video. When clustering the shots, we consider the global similarities of shots rather than the individual shot pairs. We also propose a method to describe the content of each scene by selecting one representative image from the video as a scene key-frame. Recently, DVDs have become available with a chapter selection option where each chapter is represented by one image. Our algorithm automates this objective which is useful for applications such as video-on-demand, digital libraries, and the Internet. Experiments are presented with promising results on several Hollywood movies and one sitcom.     

An evaluation of process-parameter and part-geometry effects on the quality of filling in micro-injection moulding

This paper addresses the use of micro-injection moulding for the fabrication of polymeric parts with microfeatures. Five separate parts with different micro-feature designs are moulded of Polymethylmethacrylate. The design-of-experiments approach is applied to correlate the quality of the parts to the processing parameters. Five processing parameters are investigated using a screening half-factorial experimentation plan to determine their possible effect on the filling quality of the moulded parts. The part mass is used as an output parameter to reflect the filling of the parts. The experiments showed that the holding pressure is the most significant processing parameter for all the different shapes. In addition, the experiments showed that the geometry of the parts plays a role in determining the significant processing parameters. For a more complex part, injection speed and mould temperature became statistically significant. A desirability function approach was successfully used to improve the filling quality of each part.     

On Secure and Privacy-Aware Sybil Attack Detection in Vehicular Communications

The foreseen dream of Vehicular Ad Hoc NETwork (VANET) deployment is obstructed by long-chased security and privacy nightmares. Despite of the increasing demand for perfect privacy, it conflicts with rather more serious security threat called ‘Sybil Attack’ which refers to, impersonation of one physical entity for many, namely Sybil nodes. In such circumstances, data received from malicious Sybil attacker may seem as if it was received from many distinct physical nodes. Sybil nodes may deliberately mislead other neighbors, resulting in catastrophic situations like traffic jams or even deadly accidents. Preventing such attacks in a privacy-enabled environment is not a trivial task. In this paper, we aim at two conflicting goals, i.e. privacy and Sybil attack in VANET. We leverage pseudonymless beaconing in order to preserve privacy. To cope with Sybil attack, we put forth a twofold strategy. In order to avoid Sybil attack through scheduled beacons, we employ tamper resistant module (TRM) to carry out a pre-assembly data analysis on data that is used to assemble beacons whereas for event reporting message (ERM), we employ road side units (RSUs) to localize Sybil nodes in VANET and report them to the revocation authority(s). RSUs distribute authorized tokens among the benign vehicular nodes which in turn are consumed to report ERMs. RSUs collect ERMs for certain event and figures out if more than one ERM for the same event includes identical token or, if an ERM is sent more than once by the same source. Our proposed scheme preserves privacy in both beacons and ERMs, and provides conditional anonymity where in case of a dispute; malicious attackers are subject to revocation. We also show that our proposed scheme outperforms the previously proposed scheme from security and computational complexity standpoint.