14797393
A system for analyzing and indexing human-motion databases
We demonstrate a data-driven approach for representing, compressing, and indexing human-motion databases. Our modeling approach is based on piecewise-linear components that are determined via a divisive clustering method. Selection of the appropriate linear model is determined automatically via a classifier using a subspace of the most significant, or principle features (markers). We show that, after offline training, our model can accurately estimate and classify human motions. We can also construct indexing structures for motion sequences according to their transition trajectories through these linear components. Our method not only provides indices for whole and/or partial motion sequences, but also serves as a compressed representation for the entire motion database. Our method also tends to be immune to temporal variations, and thus avoids the expense of time-warping.
14374205
Understanding Social Welfare Service Patterns Using Sequential Analysis
Classical exploratory data analysis methods in statistics and many of the earlier KDD methods tend to focus only on basic data types, (interval or categorical data) as the unit of analysis. However, some information cannot be interpreted unless the data is treated as a unit. For example, viewing the data as sequences of sets can reveal useful information that could not be extracted in any other way. Analyzing suitable databases from such a perspective can assist many social scientists in their work.
28890
Extension of Lower Probabilities and Coherence of Belief Measures
Coherence is an important concept which is introduced and discussed in a new mathematics branch, Imprecise Probability Theory. By using the Choquet integral, belief measures can be extended to be coherent lower previsions on the linear space consisting of all bounded functions. As a special case, we establish that all belief measures are coherent imprecise probabilities.
1857380
Mining RNA Tertiary Motifs with Structure Graphs
We present a novel application of graph database mining to identify tertiary motifs in RNA structures. In our method, we abstract an RNA molecule as a labeled graph and use a frequent subgraph mining technique to derive tertiary motifs. By applying our technique to ribosome RNA and transfer RNA, we have identified known RNA tertiary motifs such as the ribose zipper and U-turn, plus candidates for novel tertiary motifs. Finally, we suggest an iterative multiple structure alignment algorithm to classify tertiary motifs and generate consensus motifs.
11001109
DynamO: Dynamic Objects with Persistent Storage
In light of advances in processor and networking technology, especially the emergence of network attached disks, the traditional client-server architecture becomes suboptimal for many computation/data intensive applications, e.g., data mining, scientiic computing, image processing, etc. In this paper, we introduce a revised architecture for this kind of application: the dynamic object server environment (DynamO). The main innovation of this architecture is that the functionality of a persistent storage server is divided into modules which are dynamically migrated to the client on demand. Also, data is transfered directly to the client's cache from network-attached disks, thus avoiding multiple copies from a disk to the server buuer to the network and the client. In this way, a client only places a small load on the server, and also avoids the I/O bottleneck on the server. Furthermore, DynamO employs a distributed cache management allowing several clients to share the in-memory data by using the concept of \who uses it, serves it to others". We show via simulation models how this architecture increases the system's adaptability, scalability and cost performance.
3122822
Clustering pair-wise dissimilarity data into partially ordered sets
Ontologies represent data relationships as hierarchies of possibly overlapping classes. Ontologies are closely related to clustering hierarchies, and in this article we explore this relationship in depth. In particular, we examine the space of ontologies that can be generated by pairwise dissimilarity matrices. We demonstrate that classical clustering algorithms, which take dissimilarity matrices as inputs, do not incorporate all available information. In fact, only special types of dissimilarity matrices can be exactly preserved by previous clustering methods. We model ontologies as a partially ordered set (poset) over the subset relation. In this paper, we propose a new clustering algorithm, that generates a partially ordered set of clusters from a dissimilarity matrix.
270863
Study of distance vector routing protocols for mobile ad hoc networks
We investigate the performance issues of destination-sequenced distance vector (DSDV) and ad-hoc on-demand distance vector (AODV) routing protocols for mobile ad hoc networks. Four performance metrics are measured by varying the maximum speed of mobile hosts, the number of connections, and the network size. The correlation between network topology change and mobility is investigated by using linear regression analysis. The simulation results indicate that AODV outperforms DSDV in less stressful situations, while DSDV is more scalable with respect to the network size. It is observed that network congestion is the dominant reason for packet drop for both protocols. We propose a new routing protocol, congestion-aware distance vector (CADV), to address the congestion issues. CADV outperforms AODV in delivery ratio by about 5%, while introduces less protocol load. The result demonstrates that integrating congestion avoidance mechanisms with proactive routing protocols is a promising way to improve performance.
41218825
Relaxed game chromatic number of graphs
This paper discusses a coloring game on graphs. Let k, d be non-negative integers and C a set of k colors. Two persons, Alice and Bob, alternately color the vertices of G with colors from C, with Alice having the first move. A color i is legal for an uncolored vertex x if by coloring x with color i, the subgraph of G induced by those vertices of color i has maximum degree at most d. Each move of Alice or Bob colors an uncolored vertex with a legal color. The game is over if either all vertices are colored, or no more vertices can be colored with a legal color. Alice's goal is to produce a legal coloring which colors all the vertices of G, and Bob's goal is to prevent this from happening. We shall prove that if G is a forest, then for k = 3, d ≥ 1, Alice has a winning strategy. If G is an outerplanar graph, then for k = 6 and d ≥ 1, Alice has a winning strategy.
7654975
Using low-discrepancy sequences and the Crofton formula to compute surface areas of geometric models
The surface area of a geometric model, like its volume, is an important integral property that needs to be evaluated frequently and accurately in practice. In this paper, we present a new quasi-Monte Carlo method using low-discrepancy sequences for computing the surface area of a 3D object. We show that the new method is more efficient than a Monte Carlo method using pseudo-random numbers. This method is based on the Cauchy ‐ Crofton formula from integral geometry, and it computes the surface area of a 3D body B by counting the number of intersection points between the boundary surface of B and a set of straight lines in E 3 . Low discrepancy sequences are used to generate the set of lines in E 3 to reduce the estimation errors that would be caused by using statistically uniformly distributed lines. We study and compare two different methods for generating 3D random lines, and demonstrate their validity theoretically and experimentally. Experiments suggest that the new quasi-Monte Carlo method is also more efficient than the conventional approach based on surface tessellation. q 2002 Elsevier Science Ltd. All rights reserved.
33629250
Robust Visual Tracking Via Incremental Maximum Margin Criterion
Robust visual object tracking is one of the key problems in computer vision. Subspace based tracking method is a promising approach in handling appearance variability. Linear Discriminant Analysis(LDA) has been applied to this problem, but LDA is not a stable algorithm especially for visual tracking. Maximum Margin Criterion(MMC) is a recently proposed discriminant criterion. Its promising specialities make it a better choice for the tracking problem. In this paper, we present a novel subspace tracking algorithm based on MMC. We also proposed an incremental version of the corresponding algorithm so that the tracker can update in realtime. Experiments show our tracking algorithm is able to track objects well under large lighting, pose and expression variation.
2981606
Distributed Garbage Collection for Mobile Actor Systems: The Pseudo Root Approach
Automatic distributed garbage collection (GC) gives abstraction to grid application development, promoting code quality and improving resource management. Unreachability of active objects or actors from the root set is not a sufficient condition to collect actor garbage, making passive object GC algorithms unsafe when directly used on actor systems. In practical actor languages, all actors have references to the root set since they can interact with users, e.g., through standard input or output streams. Based on this observation, we introduce pseudo roots: a dynamic set of actors that can be viewed as the root set. Pseudo roots use protected (undeletable) references to ensure that no actors are erroneously collected even with messages in transit. Following this idea, we introduce a new direction of actor GC, and demonstrate it by developing a distributed GC framework. The framework can thus be used for automatic life time management of mobile reactive processes with unordered asynchronous communication.