9059175
On thermal effects in deep sub-micron VLSI interconnects
This paper presents a comprehensive analysis of the thermal effects in advanced high performance interconnect systems arising due to self-heating under various circuit conditions, including electrostatic discharge. Technology (Cu, low-k etc.) and scaling effects on the thermal characteristics of the interconnects, and on their electromigration reliability has been analyzed simultaneously, which will have important implications for providing robust and aggressive deep sub-micron interconnect design guidelines. Furthermore, the impact of these thermal effects on the design (driver sizing) and optimization of the interconnect length between repeaters at the upper-level signal lines are investigated.
206440147
Berkeley reliability tools-BERT
Berkeley reliability tools (BERT) simulates the circuit degradation (drift) due to hot-electron degradation in MOSFETs and bipolar transistors and predicts circuit failure rates due to oxide breakdown and electromigration in CMOS, bipolar, and BiCMOS circuits. With the increasing importance of reliability in today's and future technology, a reliability simulator such as this is expected to serve as the engine of design-for-reliability in a building-in-reliability paradigm. BERT works in conjunction with a circuit simulator such as SPICE in order to simulate reliability for actual circuits, and, like SPICE, acts as an interactive tool for design. BERT is introduced and the current work being done is summarized. BERT is used to study the reliability of a BiCMOS inverter chain, and performance data are presented. >
16132997
Manifold of facial expression
We propose the concept of manifold of facial expression based on the observation that images of a subject's facial expressions define a smooth manifold in the high dimensional image space. Such a manifold representation can provide a unified framework for facial expression analysis. We first apply active wavelet networks (AWN) on the image sequences for facial feature localization. To learn the structure of the manifold in the feature space derived by AWN, we investigated two types of embeddings from a high dimensional space to a low dimensional space: locally linear embedding (LLE) and Lipschitz embedding. Our experiments show that LLE is suitable for visualizing expression manifolds. After applying Lipschitz embedding, the expression manifold can be approximately considered as a super-spherical surface in the embedding space. For manifolds derived from different subjects, we propose a nonlinear alignment algorithm that keeps the semantic similarity of facial expression from different subjects on one generalized manifold. We also show that nonlinear alignment outperforms linear alignment in expression classification.
7704531
A TCAM-based distributed parallel IP lookup scheme and performance analysis
Using ternary content addressable memory (TCAM) for high-speed IP address lookup has been gaining popularity due to its deterministic high performance. However, restricted by the slow improvement of memory accessing speed, the route lookup engines for next-generation terabit routers demand exploiting parallelism among multiple TCAM chips. Traditional parallel methods always incur excessive redundancy and high power consumption. We propose in this paper an original TCAM-based IP lookup scheme that achieves both ultra-high lookup throughput and optimal utilization of the memory while being power-efficient. In our multi-chip scheme, we devise a load-balanced TCAM table construction algorithm together with an adaptive load balancing mechanism. The power efficiency is well controlled by decreasing the number of TCAM entries triggered in each lookup operation. Using four 133 MHz TCAM chips and given 25% more TCAM entries than the original route table, the proposed scheme achieves a lookup throughput of up to 533 MPPS while remains simple for ASIC implementation
17727182
E-Partner: A Photo-Realistic Conversation Agent
An E-Partner is a photo-realistic conversation agent, which has a talking head that not only look photo-realistic but also can have a conversation with the user about a given topic. The conversation is multimedia-enriched in that the E-Partner presents relevant multimedia materials throughout the conversation. To address the challenges presented by the complex conversation domain and task, and to achieve adaptive behaviors, we have derived a novel dialogue manager design consisting of five parts: a domain model, a dialogue model, a discourse model, a task model, and a user model. We also extended existing facial animation techniques to create photo-realistic talking heads that facilitate conversational interactions. Some practical issues like how to handle the uncertainty from speech level are also discussed.
35202136
Supporting Problem Solving with Case-Stories Learning Scenario and Video-based Collaborative Learning Technology
In this paper, we suggest that case-based resources, which are used for assisting cognition during problem solving, can be structured around the work of narratives in social cultural psychology. Theories and other research methods have proposed structures within narratives and stories which may be useful to the design of case-based resources. Moreover, embedded within cases are stories which are contextually rich, supporting the epistemological groundings of situated cognition. Therefore the purposes of this paper are to discuss possible frameworks of case-stories; derive design principles as to “what” constitutes a good case story or narrative; and suggest how technology can support story-based learning. We adopt video-based Computer-Supported Collaborative Learning (CSCL) technology to support problem solving with casestories learning scenarios. Our hypothesis in this paper is that well-designed case-based resources are able to aid in the cognitive processes undergirding problem solving and meaning making. We also suggest the use of an emerging video-based collaborative learning technology to support such an instructional strategy.
123451361
Probabilistic expression analysis on manifolds
In this paper, we propose a probabilistic video-based facial expression recognition method on manifolds. The concept of the manifold of facial expression is based on the observation that the images of all possible facial deformations of an individual make a smooth manifold embedded in a high dimensional image space. An enhanced Lipschitz embedding is developed to embed the aligned face appearance in a low dimensional space while keeping the main structure of the manifold. In the embedded space, a complete expression sequence becomes a path on the expression manifold, emanating from a center that corresponds to the neutral expression. Each path consists of several clusters. A probabilistic model of transition between the clusters and paths is learned through training videos in the embedded space. The likelihood of one kind of facial expression is modeled as a mixture density with the clusters as mixture centers. The transition between different expressions is represented as the evolution of the posterior probability of the six basic paths. The experimental results demonstrate that the probabilistic approach can recognize expression transitions effectively. We also synthesize image sequences of changing expressions through the manifold model.