6649365
Performing Incremental Bayesian Inference by Dynamic Model Counting
The ability to update the structure of a Bayesian network when new data becomes available is crucial for building adaptive systems. Recent work by Sang, Beame, and Kautz (AAAI 2005) demonstrates that the well-known Davis-Putnam procedure combined with a dynamic decomposition and caching technique is an effective method for exact inference in Bayesian networks with high density and width. In this paper, we define dynamic model counting and extend the dynamic decomposition and caching technique to multiple runs on a series of problems with similar structure. This allows us to perform Bayesian inference incrementally as the structure of the network changes. Experimental results show that our approach yields significant improvements over the previous model counting approaches on multiple challenging Bayesian network instances.
9445959
Guiding real-world SAT solving with dynamic hypergraph separator decomposition
The general solution of satisfiability problems is NP-complete. Although state-of-the-art SAT solvers can efficiently obtain the solutions of many real-world instances, there are still a large number of real-world SAT families which cannot be solved in reasonable time. Much effort has been spent to take advantage of the internal structure of SAT instances. Existing decomposition techniques are based on preprocessing the static structure of the original problem. We present a dynamic decomposition method based on hypergraph separators. Integrating the separator decomposition into the variable ordering of a modern SAT solver leads to speedups on large real-world satisfiability problems. Compared with a static decomposition based variable ordering, such as Dtree (Huang and Darwiche, 2003), our approach does not need time to construct the full tree decomposition, which sometimes needs more time than the solving process itself. Our primary focus is to achieve speedups on large real-world satisfiability problems. Our results show that the new solver often outperforms both regular zChaff and zChaff integrated with Dtree decomposition. The dynamic separator decomposition shows promise in that it significantly decreases the number of decisions for some real-world problems.
11363507
An efficient method of volume rendering for medical slices
The volume rendering method uses a special light source, slit-light source, to illuminate the volume and simulates the interactions of light with objects, such as light absorption, scattering and reflection. In comparison with previous methods, our method has several advantages. This includes flexibility for implementation, efficiency for computation, high reality for display and easiness of parallelization. The algorithm can be parallelized easily either using the data space subdivision method or the image space subdivision method. We describe some experimental results of applying our method to several sets of MRI and CT slices of human heads, which show the effectiveness of our method.<<ETX>>
6073358
Non-photorealistic virtual environments
We describe a system for non-photorealistic rendering (NPR) of virtual environments. In real time, it synthesizes imagery of architectural interiors using stroke-based textures. We address the four main challenges of such a system — interactivity, visual detail, controlled stroke size, and frame-to-frame coherence — through image based rendering (IBR) methods. In a preprocessing stage, we capture photos of a real or synthetic environment, map the photos to a coarse model of the environment, and run a series of NPR filters to generate textures. At runtime, the system re-renders the NPR textures over the geometry of the coarse model, and it adds dark lines that emphasize creases and silhouettes. We provide a method for constructing non-photorealistic textures from photographs that largely avoids seams in the resulting imagery. We also offer a new construction, art-maps, to control stroke size across the images. Finally, we show a working system that provides an immersive experience rendered in a variety of NPR styles.
7870275
Information Extraction Supported Question Answering
Abstract : This paper discusses the use of our information extraction (IE) system, Textract, in the question-answering (QA) track of the recently held TREC-8 tests. One of our major objectives is to examine how IE can help IR (Information Retrieval) in applications like QA. Our study shows: (1) IE can provide solid support for QA; (2) low-level IE like Named Entity tagging is often a necessary component in handling most types of questions; (3) a robust natural language shallow parser provides a structural basis for handling questions; (4) high-level domain independent IE, i.e. extraction of multiple relationships and general events, is expected to bring about a breakthrough in QA.
5294188
Method for identifying transcription factor binding sites in yeast
MOTIVATION
Identifying transcription factor binding sites (TFBSs) is helpful for understanding the mechanism of transcriptional regulation. The abundance and the diversity of genomic data provide an excellent opportunity for identifying TFBSs. Developing methods to integrate various types of data has become a major trend in this pursuit.


RESULTS
We develop a TFBS identification method, TFBSfinder, which utilizes several data sources, including DNA sequences, phylogenetic information, microarray data and ChIP-chip data. For a TF, TFBSfinder rigorously selects a set of reliable target genes and a set of non-target genes (as a background set) to find overrepresented and conserved motifs in target genes. A new metric for measuring the degree of conservation at a binding site across species and methods for clustering motifs and for inferring position weight matrices are proposed. For synthetic data and yeast cell cycle TFs, TFBSfinder identifies motifs that are highly similar to known consensuses. Moreover, TFBSfinder outperforms well-known methods.


AVAILABILITY
http://cg1.iis.sinica.edu.tw/~TFBSfinder/.
18531635
A generalized model for network survivability
The high expectation of network to be available and perform at all time has created growing concerns between network operators and engineers all over the globe. Network should be available to users whenever they want to use them. In the wake of an attack, network should be also able to recover as soon as possible. A survivable network is one that can provide services in the presence of an attack or failure and be able to recover fully in a timely manner. Designing a model for network survivability basically involves the understanding of three key issues, i.e, how the system will function in the wake of failures, what will be the impact of failures on the user, and how to overcome these failures. To achieve these goals, this paper proposes a quantitative approach to evaluate the network survivability in terms of using a generalized model; we consider a more complex system with several faults to study the survivability of a network using Markov chain. In presenting a better survivability performance, some numerical comparisons for the network availability, failure frequency and survivability is also developed.