7017728
Indexing Genomic Databases for Fast Homology Searching
Genomic sequence databases has been widely used by molecular biologists for homology searching. However, as amino acid and nucleotide databases are growing in size at an alarming rate, traditional brute force approach of comparing a query sequence against each of the database sequences is becoming prohibitively expensive. In this paper, we re-examine the problem of searching for homology in large protein databases. We proposed a novel filter-and-refine approach to speed up the search process. The scheme operates in two phases. In the filtering phase, a small set of candidate database sequences (as compared to all sequences in the database) is quickly identified. This is realized using a signature-based scheme. In the refinement phase, the query sequence is matched against the sequences in the candidate set using any local alignment strategies. Our preliminary experimental results show that the proposed method results in significant savings in computation without sacrificing on the accuracy of the answers as compared to FASTA.
20063786
Implementation of a graphics design framework on the Web
We propose a client-server graphics design framework and implement a room design system using CORBA. We have integrated technologies used in distributed computation (Java and CORBA) and computer graphics (VRML). To support multiuser collaborative design, we propose a supplier-consumer communication approach and implement it using the event service in CORBA. Our system can be applied in electronic commerce to improve the existing systems by allowing customers to select furniture and to visualize the whole furnished room in 3D.
16399618
Fast filter-and-refine algorithms for subsequence selection
Large sequence databases, such as protein, DNA and gene sequences in biology, are becoming increasingly common. An important operation on a sequence database is approximate subsequence matching, where all subsequences that are within some distance from a given query string are retrieved. This paper proposes a filter-and-refine algorithm that enables efficient approximate subsequence matching in large DNA sequence databases. It employs a bitmap indexing structure to condense and encode each data sequence into a shorter index sequence. During query processing, the bitmap index is used to filter out most of the irrelevant subsequences, and false positives are removed in the final refinement step. Analytical and experimental studies show that the proposed strategy is capable of reducing response time substantially while incurring only a small space overhead.
22168621
BLAST++ : A Tool for BLASTing Queries in Batches
BLAST is the standard tool that molecular biologists use to search for sequence similarity in genomic (and protein) databases. It employs a brute force approach of comparing a query sequence against every database sequence - for each pair of the sequences to be matched, BLAST searches for short fixed-length word pairs (seeds) in the sequences and then extends them to higher-scoring regions. To search multiple queries, the basic approach is to run BLAST on each of the queries one at a time. This is clearly inefficient and fails to exploit common subsequences that the collection of queries may share. In this paper, we propose a new genome search tool, BLAST++, that allows multiple, say K, queries to be searched against a database concurrently. The design of BLAST++ is based on our observation that the seed searching step of BLAST is a bottleneck that consumes more than 80% of the total response time! BLAST++ essentially treats a collection of queries as a single virtual query so that the seed searching step needs to be performed only once for common subsequences. We implemented BLAST++ as an extension of the NCBI BLAST, and evaluated its performance. Our study shows that the results obtained by BLAST++ are identical to that obtained by executing BLAST on each of the K queries, but the single-process version of BLAST++ completes the processing in a much shorter time, about only 25% of the original single-process version of NCBI BLAST.
15968114
An Efficient Explicit-time Description Method for Timed Model Checking
Timed modelchecking,the methodtoformallyverifyreal-timesystems, is attractingincreasingatten-tion from both the model checking community and the real-time community. Explicit-time descrip-tion methods verify real-time systems using general model constructs found in standard un-timedmodel checkers. Lamport proposed an explicit-time description method [17] using a clock-tickingprocess (Tick) to simulate the passage of time together with a group of global variables to model timerequirements. Two methods, the Sync-based Explicit-time Description Methodusing rendezvoussynchronization steps and the Semaphore-based Explicit-time Description Methodusing only oneglobal variable were proposed [27, 26]; they both achieve better modularity than Lamport’s methodin modelingthe real-time systems. In contrast to timed automatabased model checkerslike UPPAAL[7], explicit-time description methods can access and store the current time instant for future calcula-tions necessary for many real-time systems, especially those with pre-emptive scheduling. However,the Tick process in the above three methods increments the time by one unit in each tick; the statespaces therefore grow relatively fast as the time parameters increase, a problem when the system’stime period is relatively long. In this paper, we propose a more efﬁcient method which enables theTick process to leap multiple time units in one tick. Preliminary experimentalresults in a high perfor-mance computing environment show that this new method signiﬁcantly reduces the state space andimproves both the time and memory efﬁciency.
940637
Apply ant colony optimization to Tetris
Tetris is a falling block game where the player's objective is to arrange a sequence of different shaped tetrominoes smoothly in order to survive. In the intelligence games, agent imitates the real player and chooses the best move based on a linear value function. In this paper, we apply Ant Colony Optimization (ACO) method to learn the weights of the function, trying to search an optimal weight-path in the weight graph. We use dynamic heuristic to prevent premature convergence to local optima. Our experimental result is better than most of traditional reinforcement learning methods.
16346838
Ant-MST: An Ant-Based Minimum Spanning Tree for Gene Expression Data Clustering
We have proposed an ant-based clustering algorithm for document clustering based on the travelling salesperson scenario. In this paper, we presented an approach called Ant-MST for gene expression data clustering based on both ant-based clustering and minimum spanning trees (MST). The ant-based clustering algorithm is firstly used to construct a fully connected network of nodes. Each node represents one gene, and every edge is associated with a certain level of pheromone intensity describing the co-expression level between two genes. Then MST is used to break the linkages in order to generate clusters. Comparing to other MST-based clustering approaches, our proposed method uses pheromone intensity to measure the similarity between two genes instead of using Euclidean distance or correlation distance. Pheromone intensities associated with every edge in a fully-connected network records the collective memory of the ants. Self-organizing behavior could be easily discovered through pheromone intensities. Experimental results on three gene expression datasets show that our approach in general outperforms the classical clustering methods such as K-means and agglomerate hierarchical clustering.
206800753
Automatic character location and segmentation in color scene images
This paper describes a connected component (CC)-based approach to automatic text location and segmentation in natural scene images. A multi-group decomposition scheme is used to deal with the complexity of the color background. Connected component extraction is implemented using the block adjacency graph (BAG) algorithm after noise filtering and runlength smearing (RLS) operation. Some heuristic features and priority adaptive segmentation (PAS) of characters are proposed in block candidate verification and grayscale-based recognition. A prototype system is completed and the experimental results prove the effectiveness of the proposed method.
59897458
Algorithms and qos of video streaming over wireless networks
Video streaming over wireless networks has attracted much attention recently. It is well known that video streaming is QoS Stringent applications and wireless link suffers from erroneous and time-variant conditions. Significant research work has been conducted on QoS guarantee of video streaming application in Physical, MAC and Network layers. In this dissertation, the author designed a combination of packet ordering algorithm and transmission scheme for streaming video over a single wireless link and a distributed system for streaming video over multi-hop wireless networks, respectively. 
QoS routing has been widely researched and a number of routing protocols have been proposed to support routing of QoS stringent real-time applications. Recently, scalable video coding has been used for adaptation of video streaming to heterogeneous networks, especially wireless networks. The author proposed the routing criteria and routing algorithms for the routing of base layer (BL) and enhancement layer (EL) of MPEG-4 FGS. 
Research on Mobile Ad Hoc networks (MANETS) has been driven by either large scale military applications or specialized civilian applications which are tailored to very specialized missions and cost is typically not a main issue. Wireless mesh networks (WMN) meet the demand of a limited number of people wanting to form an ad hoc network for sharing information. In wireless mesh networks, Peer-to-Peer (P2P) video streaming service request generally can be satisfied by more than one video server. WMN P2P video streaming service can be modeled by K-server problem. Competitive work function algorithm is running in the distributed manner and is robust to the update message loss. Modified work function algorithm is proposed for P2P video streaming service over congested WMN. And the author conjectured that the modified work function algorithm is still competitive.