Jyh-Jong Tsay

External-memory computational geometry

In this paper we give new techniques for designing efficient algorithms for computational geometry problems that are too large to be solved in internal memory. We use these techniques to develop optimal and practical algorithms for a number of important large-scale problems. We discuss our algorithms primarily in the context of single processor/single disk machines, a domain in which they are not only the first known optimal results but also of tremendous practical value. Our methods also produce the first known optimal algorithms for a wide range of two-level and hierarchical multilevel memory models, including parallel models. The algorithms are optimal both in terms of I/O cost and internal computation.<<ETX>>

A passive approach for effective detection and localization of region-level video forgery with spatio-temporal coherence analysis

In this paper, we present a passive approach for effective detection and localization of region-level forgery from video sequences possibly with camera motion. As most digital image/video capture devices do not have modules for embedding watermark or signature, passive forgery detection which aims to detect the traces of tampering without embedded information has become the major focus of recent research. However, most of current passive approaches either work only for frame-level detection and cannot localize region-level forgery, or suffer from high false detection rates for localization of tampered regions. In this paper, we investigate two common region-level inpainting methods for object removal, temporal copy-and-paste and exemplar-based texture synthesis, and propose a new approach based on spatio-temporal coherence analysis for detection and localization of tampered regions. Our approach can handle camera motion and multiple object removal. Experiments show that our approach outperforms previous approaches, and can effectively detect and localize regions tampered by temporal copy-and-paste and texture synthesis.

Checkpointing Message-Passing Interface (MPI) parallel programs

Many scientific problems can be distributed on a large number of processes to take advantage of low cost workstations. In a parallel systems, a failure on any processor can halt the computation and requires restarting all applications. Checkpointing is a simple technique to recover the failed execution. Message Passing Interface (MPI) is a standard proposed for writing portable message-passing parallel programs. In this paper, we present a checkpointing implementation for MPI programs, which is transparent, and requires no changes to the application programs. Our implementation combines coordinated, uncoordinated and message logging techniques.

An effective evolutionary algorithm for protein folding on 3D FCC HP model by lattice rotation and generalized move sets

BackgroundProteins are essential biological molecules which play vital roles in nearly all biological processes. It is the tertiary structure of a protein that determines its functions. Therefore the prediction of a proteins tertiary structure based on its primary amino acid sequence has long been the most important and challenging subject in biochemistry, molecular biology and biophysics. In the past, the HP lattice model was one of the ab initio methods that many researchers used to forecast the protein structure. Although these kinds of simplified methods could not achieve high resolution, they provided a macrocosm-optimized protein structure. The model has been employed to investigate general principles of protein folding, and plays an important role in the prediction of protein structures.MethodsIn this paper, we present an improved evolutionary algorithm for the protein folding problem. We study the problem on the 3D FCC lattice HP model which has been widely used in previous research. Our focus is to develop evolutionary algorithms (EA) which are robust, easy to implement and can handle various energy functions. We propose to combine three different local search methods, including lattice rotation for crossover, K-site move for mutation, and generalized pull move; these form our key components to improve previous EA-based approaches.ResultsWe have carried out experiments over several data sets which were used in previous research. The results of the experiments show that our approach is able to find optimal conformations which were not found by previous EA-based approaches.ConclusionsWe have investigated the geometric properties of the 3D FCC lattice and developed several local search techniques to improve traditional EA-based approaches to the protein folding problem. It is known that EA-based approaches are robust and can handle arbitrary energy functions. Our results further show that by extensive development of local searches, EA can also be very effective for finding optimal conformations on the 3D FCC HP model. Furthermore, the local searches developed in this paper can be integrated with other approaches such as the Monte Carlo and Tabu searches to improve their performance.

Hierarchically organized layout for visualization of biochemical pathways

OBJECTIVE Many complex pathways are described as hierarchical structures in which a pathway is recursively partitioned into several sub-pathways, and organized hierarchically as a tree. The hierarchical structure provides a natural way to visualize the global structure of a complex pathway. However, none of the previous research on pathway visualization explores the hierarchical structures provided by many complex pathways. In this paper, we aim to develop algorithms that can take advantages of hierarchical structures, and give layouts that explore the global structures as well as local structures of pathways. METHODS We present a new hierarchically organized layout algorithm to produce layouts for hierarchically organized pathways. Our algorithm first decomposes a complex pathway into sub-pathway groups along the hierarchical organization, and then partition each sub-pathway group into basic components. It then applies conventional layout algorithms, such as hierarchical layout and force-directed layout, to compute the layout of each basic component. Finally, component layouts are joined to form a final layout of the pathway. Our main contribution is the development of algorithms for decomposing pathways and joining layouts. RESULTS Experiment shows that our algorithm is able to give comprehensible visualization for pathways with hierarchies, cycles as well as complex structures. It clearly renders the global component structures as well as the local structure in each component. In addition, it runs very fast, and gives better visualization for many examples from previous related research.

Improving linear classifier for Chinese text categorization

The goal of this paper is to derive extra representatives from each class to compensate for the potential weakness of linear classifiers that compute one representative for each class. To evaluate the effectiveness of our approach, we compared with linear classifier produced by Rocchio algorithm and the k-nearest neighbor (kNN) classifier. Experimental results show that our approach improved linear classifier and achieved micro-averaged accuracy close to that of kNN, with much less classification time. Furthermore, we could provide a suggestion to reorganize the structure of classes when identify new representatives for linear classifier.

AuToCrawler: an integrated system for automatic topical crawler

A topical (or focused) crawler is a Web crawler aiming to search and retrieve Web pages from the World Wide Web, which are related to a specific topic. Rather than downloading all accessible Web pages, a topical crawler analyzes the frontier of the crawled region to visit only the portion of the Web that contains relevant Web pages, and at the same time, try to skip irrelevant regions. This leads to significant savings in both computation and communication resources. In this paper, we present an integrated topical crawler: AuToCrawler. The main features of AuToCrawler consist of a user interest specification module that mediates between users and search engines to identify target examples and keywords that together specify the topic of their interest, and a URL ordering strategy that combines features of several previous approaches and achieves significant improvement. It also provides a graphic user interface such that users can evaluate and visualize the crawling results that can be used as feedback to reconfigure the crawler.

Evolving Intelligent Mario Controller by Reinforcement Learning

Artificial Intelligence for computer games is an interesting topic which attracts intensive attention recently. In this context, Mario AI Competition modifies a Super Mario Bros game to be a benchmark software for people who program AI controller to direct Mario and make him overcome the different levels. This competition was handled in the IEEE Games Innovation Conference and the IEEE Symposium on Computational Intelligence and Games since 2009. In this paper, we study the application of Reinforcement Learning to construct a Mario AI controller that learns from the complex game environment. We train the controller to grow stronger for dealing with several difficulties and types of levels. In controller developing phase, we design the states and actions cautiously to reduce the search space, and make Reinforcement Learning suitable for the requirement of online learning.

Enhancing techniques for efficient topic hierarchy integration

Here, we study the problem of integrating documents from different sources into a comprehensive topic hierarchy. Our objective is to develop efficient techniques that improve the accuracy of traditional categorization methods by incorporating categorization information provided by data sources into categorization process. Notice that in the World-Wide Web, categorization information is often available from information sources. We present several enhancing techniques that use categorization information to enhance traditional methods such as naive Bayes and support vector machines. Experiment on collections from Openfind and Yam, and Google and Yahoo!, well-known popular Web sites in Taiwan and USA, respectively, shows that our techniques significantly improve the classification accuracy from, for example, 55% to 66% for Naive Bayes, and from 57% to 67% for SVM for the data set collected from Yam and Openfind.

Lock-free concurrent tree structures for multiprocessor systems

This paper presents a window-based approach to design lock-free concurrent implementations for a class of top-down tree structures that supports operations whose executions can be modeled as a process of moving a window along a rooted simple path. Our approach can be implemented on multiprocessor systems that, support load-linked, store-conditional and check-valid synchronization primitives that are supported in MIPS-II and DEC Alpha architectures. Our approach achieves high degree of concurrency, requires low coordination overhead, is wait-free and fault tolerant. Simulation shows that our approach is efficient.