The purpose of this study was to investigate the functional connectivity (FC) of thalamic subdivisions in patients with juvenile myoclonic epilepsy (JME). Resting state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data were acquired from 22 JME and 25 healthy controls. We first divided the thalamus into eight subdivisions by performing independent component analysis on tracking fibers and clustering thalamus-related FC maps. We then analyzed abnormal FC in each subdivision in JME compared with healthy controls, and we investigated their associations with clinical features. Eight thalamic sub-regions identified in the current study showed unbalanced thalamic FC in JME: decreased FC with the superior frontal gyrus and enhanced FC with the supplementary motor area in the posterior thalamus increased thalamic FC with the salience network (SN) and reduced FC with the default mode network (DMN). Abnormalities in thalamo-prefrontocortical networks might be related to the propagation of generalized spikes with frontocentral predominance in JME, and the network connectivity differences with the SN and DMN might be implicated in emotional and cognitive defects in JME. JME was also associated with enhanced FC among thalamic sub-regions and with the basal ganglia and cerebellum, suggesting the regulatory role of subcortical nuclei and the cerebellum on the thalamo-cortical circuit. Additionally, increased FC with the pallidum was positive related with the duration of disease. The present study provides emerging evidence of FC to understand that specific thalamic subdivisions contribute to the abnormalities of thalamic-cortical networks in JME. Moreover, the posterior thalamus could play a crucial role in generalized epileptic activity in JME.

Smart Grid is a complex cyber-physical system that modernizes the traditional electric power infrastructure by sensing, control, computation and communication. Validating the functionality, security and reliability of Smart Grid applications within such a system requires the modeling and emulation of both power networks and communication networks, as well as the interactions between them. In this paper, we present the design, implementation and evaluation of an integrated scalable cyber-physical experiment environment for Smart Grid, called ScorePlus. Compared with previous related works, ScorePlus fills the gap by: 1) Creating and integrating both software emulator and hardware testbed, such that they all follow the same architecture and interface, and the same Smart Grid application program can be tested on either of them without any modification; 2) Providing remote access to the hardware testbed such that users can configure physical devices of the hardware testbed through Internet; 3) Supporting scalable distributed experiments such that multiple software emulators and hardware testbeds running at different locations are able to connect and form a larger Smart Grid system.

A novel class of malicious data attacks, LPAttack, are presented against the state estimation process in Smart Grid. Here LP represents leverage points, which are the outliers in the factor space of the regression model for Smart Grid state estimation. The attacker strategically manipulates the parameter data in Smart Grid to mislead the control center with incorrect system parameter information, such that leverage points are created within the factor space of the state estimation regression model. As a result, the attacker can freely inject arbitrary errors into the meter measurements corresponded with the leverage points, while bypassing the existing bad data detection mechanism. We first introduce the fundamental principles and strategies of launching LPAttack in Smart Grid. Then the potential countermeasure based on robust Schweppe-Huber Generalized-M estimator is proposed. Finally, we evaluate the LPAttack principles and its countermeasure through simulations in IEEE test system, and examine in particular the effect of the attacks on Locational Marginal Prices in real-time pricing power market.

In this demonstration, we demonstrate a mobile-based celebrity video browsing system called CeleBrowser. Using this system, users can interactively switch among four views: people-centric, timeline-centric, month-centric and topic-centric, for browsing celebrity-related hot videos. A peculiarity of the demonstration is to highlight the advantage of multi-perspective information organization and presentation in engaging users for exploratory browsing of large number of Web videos on a device with small screen. Technology-wise the demonstration shows how query logs collected for six months from two vertical search engines are leveraged for mining hot events and videos of celebrities.

Organizing video search results in a list view is widely adopted by current commercial search engines, which cannot support efficient browsing for complex search topics that have multiple semantic facets. In this article, we propose to organize video search results in a highly structured way. Specifically, videos are placed on a semantic hierarchy that accurately organizes various facets of a given search topic. To pick the most suitable videos for each node of the hierarchy, we define and utilize three important criteria: relevance, uniqueness, and diversity. Extensive evaluations on a large YouTube video dataset demonstrate the effectiveness of our approach.

Most search engines return a ranked list of items in response to a query. The list however tells very little about the relationship among items. For videos especially, users often read to spend significant amount of time to navigate the search result. Exploratory search presents a new paradigm for browsing where the browser takes up the role of information exploring and presents a well-organized browsing structure for users to navigate. The proposed interface Galaxy Browser adopts the recent advances in near-duplicate detection and then synchronizes the detected near-duplicate information with comprehensive background knowledge derived from online external resources. The result is a topic structure on which users can easily browse and explore.

No abstract available.

With the rapid growth of social media, there are plenty of information sources freely available online for use. Nevertheless, how to synchronize and leverage these diverse forms of information for multimedia applications remains a problem yet to be seriously studied. This paper investigates the synchronization of multiple media content in the physical form of hyperlinking them. The ultimate goal is to develop browsing systems that author search results with rich media information mined from various knowledge sources. The authoring enables the vivid visualization and exploration of different information landscapes inherent in search results. Several key techniques are studied in this paper for developing these browsing features. These techniques include content mining and selection from web videos, space-time alignment of multiple media, and augmenting of search result with when and what information. We conduct both quantitative and user studies on a large video dataset for performance evaluation. Comparison with traditional techniques including storyboard summarization and video skimming are also presented.

Search engines are used to return a long list of hundreds or even thousands of videos in response to a query topic. Efficient navigation of videos becomes difficult and users often need to painstakingly explore the search list for a gist of the search result. This paper addresses the challenge of topical summarization by providing a timeline-based visualization of videos through matching of heterogeneous sources. To overcome the so called sparse-text problem of web videos, auxiliary information from Google context is exploited. Google Trends is used to predict the milestone events of a topic. Meanwhile, the typical scenes of web videos are extracted by visual near-duplicate threading. Visual-text alignment is then conducted to align scenes from videos and articles from Google News. The outcome is a set of scene-news pairs, each representing an event mapped to the milestone timeline of a topic. The timeline-based visualization provides a glimpse of major events about a topic. We conduct both the quantitative and subjective studies to evaluate the practicality of the application.

The massive amount of near-duplicate and duplicate Web videos has presented both challenge and opportunity to multimedia computing. On one hand, browsing videos on Internet becomes highly inefficient for the need to repeatedly fast-forward videos of similar content. On the other hand, the tremendous amount of somewhat duplicate content also makes some traditionally difficult vision tasks become simple and easy. For example, annotating pictures can be as simple as recycling the tags of Internet images retrieved from image search engines. Such tasks, of either to eliminate or to recycle near-duplicates, can usually be achieved by the nearest neighbor search of videos from Internet. The fundamental problem lies on the scalability of a search technique, in face of the intractable volume of videos which keep rolling on the Web. In this paper, we investigate scalability of several well-known features including color signature and visual keywords for Web-based retrieval. Indexing these features based on embedding technique for scalable retrieval is also presented. On an Internet video dataset of more than 700 hours collected during years 2006 to 2008, we show some preliminary insights to the challenge of scalable retrieval.