8404805
Fractal Dimensions for Percolation and Phase Transition Models: Theory and New Monte Carlo Calculation Method
44360962
Parallel Solution of the Poisson-Boltzmann Equation for Proteins
A fortran code PBSOLVE is created for numerical solution of a linear Poissson-Boltzman equation. Finite difference discretization and successive overrelaxation (SOR) iterations on the sequence of grids are used to obtain the approximate electrostatic potential on the grid. Error control is provided by comparison of solution on nested grids. A parallel versioon of the PBSOLVE which exploits the message passing interface (MPI) has also been constructed. The performances of the program and the efficiency of parallelization have been tested on the small peptide Met-Enkephalin.
8192681
Image Retrieval Using Schwarz Representation of One-Dimensional Feature
Retrieval efficiency and accuracy are two important issues in designing a content based database retrieval system. In order to retrieve efficiently, we must extract feature to build index. Recently intensive research focused on how to extract one-dimensional features and calculate the distance between them, such as color histogram, Fourier descriptor, image shape spectrum (ISS). We develop a new method to match one-dimensional feature function in multiscale space using Schwarz representation. It can obtain closed form match function and similarity measure instead of traditional optimization. Thus we can calculate the global distance when the local information of feature function is matched. In this paper, we use the center distance function of shape as the feature functions. We calculate their Schwarz representation as indices, and calculate the optimal distance as similarity measure to sort the images. Experimental results show its efficiency and accuracy.
1952111
Manifold Based Analysis of Facial Expression
We propose a novel approach for modeling, tracking and recognizing facial expressions. Our method works on a low dimensional expression manifold, which is obtained by Isomap embedding. In this space, facial contour features are first clustered, using a mixture model. Then, expression dynamics are learned for tracking and classification. We use ICondensation to track facial features in the embedded space, while recognizing facial expressions in a cooperative manner, within a common probabilistic framework. The image observation likelihood is derived from a variation of the Active Shape Model (ASM) algorithm. For each cluster in the low-dimensional space, a specific ASM model is learned, thus avoiding incorrect matching due to non-linear image variations. Preliminary experimental results show that our probabilistic facial expression model on manifold significantly improves facial deformation tracking and expression recognition.
5668129
A reactive channel model for expediting wireless network simulation
A major problem with leveraging event-driven, packet-level simulation environments, such as ns2[6], J-Sim[1], OpNet[2]), and QualNet[3]), in conducting wireless network simulation is the vast number of events generated, a majority of which are related to signal transmission in the PHY/MAC layers.In this extended abstract, we investigate the operations of signal transmission in the various stages: signal propagation, signal interference, and interaction with the PHY/MAC layers, and identify where events can be reduced without impairing the accuracy. We propose to leverage the MAC/PHY state information, and devise (from the perspective of network simulation) a reactive channel model (RCM) in which nodes explicitly register their interests in receiving certain events according to the MAC/PHY states they are in and the corresponding operations that should be performed. The simulation study indicates that RCM renders an order of magnitude of speed-up without compromising the accuracy of simulation results. An advantage of RCM with respect to the implementation is that there is no need to re-design the channel model for each specific MAC layer, and the modification made in the MAC/PHY layers is quite modest (e.g., a few API changes). This, coupled with the performance gain, suggests that RCM is an attractive, light-weight mechanism for expediting wireless network simulation.
5138654
LISP: a link-indexed statistical traffic prediction approach to improving IEEE 802.11 PSM
We present a novel and complementary mechanism, called link-indexed statistical traffic predictor (LISP) to improve IEEE 802.11 power saving mechanism (PSM). LISP employs a simple, light-weight traffic prediction mechanism and enables each node to seek the inherent correlation between ATIM.ACKs and incoming traffic. Thereby nodes en route can stay awake in the BI in which a packet is anticipated to arrive, thus bridging a "freeway" for the packet to rapidly traverse the route. Meanwhile, the number of duty cycles is minimized and more energy is conserved. We conduct analytical and simulation studies and demonstrate the effectiveness of LISP.
3771585
Icon-based visualization of large high-dimensional datasets
High dimensional data visualization is critical to data analysts since it gives a direct view of original data. We present a method to visualize large amount of high dimensional data. We divide dimensions of data into several groups. Then, we use one icon to represent each group, and associate visual properties of each icon with dimensions in each group. A high dimensional data record will be represented by multiple different types of icons located in the same position. Furthermore, we use summary icons to display local details of viewer's interests and the whole data set at meantime. We show its effectiveness and efficiency through a case study on a real large data set.