26955217
On Temporal Aggregate Processing Based on Time Points
Temporal aggregation is an extension of conventional aggregate on the domain and range of aggregates to include the time concept. In this paper, we propose a new tree-based temporal aggregation processing method. The time complexity of the proposed method is better than those of the existing methods. The experimental results indicate that our proposed method ourperforms the existing methods.
1994375
Effective Temporal Aggregation Using Point-Based Trees
Temporal databases introduce the concept of time into underlying data, and provide built-in facilities that allow users to store and retrieve time-varying data. The aggregation in temporal databases, that is, temporal aggregation is an extension of conventional aggregation on the domain and range of aggregates to include time concept. Temporal aggregation is important for various applications, but is very expensive. In this paper, we propose a new tree structure for temporal aggregation, called PA-tree, and aggregate processing method based on the PA-tree. We show that the time complexity of the proposed method is better than those of the existing methods. The time complexity of the proposed method is shown to be indeed the lower bound of the problem. We perform comparative experiments and show the performance advantage of our proposed method in practice.
43684392
Wavelet Analysis Based Blind Watermarking for 3-D Surface Meshes
As most previous wavelet analysis based 3-D mesh watermarking methods embed the watermark information into wavelet coefficients arranged in a certain order, they have not been used as blind schemes since the connectivity information must be exactly known in the watermark extraction process. In this paper, we propose a blind watermarking method based on wavelet analysis for 3-D mesh model. Two new techniques are introduced. One is to exploit the statistical features of scale coefficients on an approximation (low resolution) level for watermark embedding. Another is to extract the hidden watermark, not from the same resolution level as used in embedding process, but directly from the spatial domain. As the proposed watermark detection does not require the wavelet analysis, any pre-processing such as registration and re-sampling, is not needed. These techniques allow to detect the watermark without referring to the original meshes. In addition, the proposed are applicable directly to irregular meshes by using irregular wavelet analysis. Through simulations, we prove that our method is fairly robust against various attacks including topological ones.
10669533
Optimal distribution tree for Internet streaming media
Internet radio and television stations require significant bandwidth to support delivery of high quality audio and video streams to a large number of receivers. IP multicast is an appropriate delivery model for these applications. However, widespread deployment of IP multicast on the Internet is unlikely in the near future. An alternative is to build a multicast tree in the application layer Previous studies have addressed tree construction in the application layer However most of them focus on reducing delay. Few systems have been designed to achieve a high throughput for bandwidth-intensive applications. In this paper we present a distributed algorithm to build an application-layer tree. We prove that our algorithm finds a tree such that the average incoming rate of receivers in the tree is maximized (under certain network model assumptions). We also describe protocols that implement the algorithm. For implementation on the Internet, there is a tradeoff between the overhead of available bandwidth measurements and fast convergence to the optimal tree. This tradeoff can be controlled by tuning some parameters in our protocols. Our protocols are also designed to maintain a small number, O(log n), of soft states per node to adapt to network changes and node failures.
1461453
Optimal partitioning of multicast receivers
Multicast sessions may have a large number of receivers with heterogeneous reception capacities. To accommodate this heterogeneity various multi-rate schemes, based upon the use of layering or replication, have been proposed. We consider the optimal partitioning of receivers into groups for multi-rate schemes. For a general class of utility functions, we formulate the partitioning problem as an optimization problem to maximize the sum of receiver utilities. We present an efficient dynamic programming algorithm to solve the partitioning problem, and prove that the solution it finds is optimal. We also show that the majority of the benefit of a multi-rate scheme can be gained by using a small number of groups (or layers), say 4 to 5. To illustrate our solution approach, we apply it to the case where receiver capacities are determined by multi-rate max-min fair rates. A complete protocol for receiver rates computation, rates collection, optimal receiver partitioning, and receiver adaptation is presented. We then compare our approach with other multi-rate approaches as well as a single-rate approach. Experimental results show that our approach provides substantial performance improvements.
20698705
Home health care support
We describe an ap@ication to interconnect health care providers and thew patients in the home. The application includes information services, symptom analy SIS, ~idance in the performance of procedures, emotmnal support, and communications among the health care providers, patients and caretakers.
8330560
Shape Comparison of the Hippocampus Using a Multiresolution Representation and ICP Normalization
It is known that deformation of the hippocampus shape is involved with several neurological diseases. In this paper, we propose a hybrid shape representation scheme, which consists of multiresolution skeletons, voxels and meshes for the shape analysis of the hippocampus. Initially, a hippocampal surface model is reconstructed from MRI and then it is placed into a canonical coordinate system, where the position, orientation and scaling are normalized. From the voxel representation of the hippocampus, multiresolution skeletons are extracted and Iterative Closest Point normalization is carried out. Then the shape similarity of two hippocampal models is computed with a hierarchical fashion. In addition, we have implemented a neural network based classifier to discriminate whether a hippocampal model is normal or not. Results indicate that the proposed hybrid representation and the skeleton-based normalization using ICP are very effective in 3D shape analysis of the hippocampus.