14619760
A New Inlining Algorithm for Mapping XML DTDs to Relational Schemas
XML is rapidly emerging on the World Wide Web as a standard for representing and exchanging data. It is critical to have efficient mechanisms to store and query XML documents to exploit the full power of this new technology. While one approach is to develop native XML repositories that support XML data models and query languages directly, the other approach is to take advantage of the mature technologies that are provided by current relational or object-relational DBMSs. There is active research along both approaches and it is still not clear which one is better than the other. We continue our effort on the second approach. In particular, we have developed an efficient algorithm which takes an XML DTD as input and produces a relational schema as output for storing and querying XML documents conforming to the input DTD. Our algorithm features several significant improvements over the shared-inlining algorithm including overcoming its incompleteness, eliminating redundancies caused by shared elements, performing optimizations and enhancing efficiency.
16579446
Mining Correlation between Motifs and Gene Expression
One of the major challenges in the post-genomic era is to determine all DNA-binding transcription factors (TFs) and their regulatory binding sites (motifs) within the genomes. To discover the relationship between the motifs and changes in gene expression, we propose a new algorithm, co-miner (correlation miner). Correlation rules are generated based on the expression profiles of genes with significant expression change through the time course of gene expression. Thus, we may consider the change in gene expression to be causatively associated with the transcription binding sites in the upstream sequences. In addition, we introduce partition and constraint pushing techniques to improve the performance and demonstrate their effectiveness by our experiments. By applying co-miner to a yeast dataset, the relationships between motifs and gene expression revealed by co-miner are confirmed in the literature.
7682350
Incremental genetic K-means algorithm and its application in gene expression data analysis
BackgroundIn recent years, clustering algorithms have been effectively applied in molecular biology for gene expression data analysis. With the help of clustering algorithms such as K-means, hierarchical clustering, SOM, etc, genes are partitioned into groups based on the similarity between their expression profiles. In this way, functionally related genes are identified. As the amount of laboratory data in molecular biology grows exponentially each year due to advanced technologies such as Microarray, new efficient and effective methods for clustering must be developed to process this growing amount of biological data.ResultsIn this paper, we propose a new clustering algorithm, Incremental Genetic K-means Algorithm (IGKA). IGKA is an extension to our previously proposed clustering algorithm, the Fast Genetic K-means Algorithm (FGKA). IGKA outperforms FGKA when the mutation probability is small. The main idea of IGKA is to calculate the objective value Total Within-Cluster Variation (TWCV) and to cluster centroids incrementally whenever the mutation probability is small. IGKA inherits the salient feature of FGKA of always converging to the global optimum. C program is freely available at http://database.cs.wayne.edu/proj/FGKA/index.htm.ConclusionsOur experiments indicate that, while the IGKA algorithm has a convergence pattern similar to FGKA, it has a better time performance when the mutation probability decreases to some point. Finally, we used IGKA to cluster a yeast dataset and found that it increased the enrichment of genes of similar function within the cluster.
6486168
A Dataflow-Oriented Atomicity and Provenance System for Pipelined Scientific Workflows
Scientific workflows have gained great momentum in recent years due to their critical roles in e-Science and cyberinfrastructure applications. However, some tasks of a scientific workflow might fail during execution. A domain scientist might require a region of a scientific workflow to be "atomic". Data provenance, which determines the source data that are used to produce a data item, is also essential to scientific workflows. In this paper, we propose: (i) an architecture for scientific workflow management systems that supports both provenance and atomicity; (ii) a dataflow-oriented atomicity model that supports the notions of commit and abort; and (iii) a dataflow-oriented provenance model that, in addition to supporting existing provenance graphs and queries, also supports queries related to atomicity and failure.
18131628
Automatic workflow verification and generation
Correctness is an important aspect of workflow management systems. However, most of the workflow literature focuses only on the modeling aspects and assumes that a workflow is correct if during the execution it respects the control and data dependency specified by the workflow designer. To address the correctness question properly we propose a new workflow model based on Hoare semantics that allows to: (1) automatically check if the desired outcome of a workflow can be produced by its actual implementation, (2) automatically synthesize a workflow implementation from the workflow specification and a given task library.In particular we: (1) formalize the semantics of workflows and tasks with pre-and postconditions, (2) for each control construct we provide a set of sound inference rules formalizing its semantics. While most of our workflow constructs are standard, two of them are new: the universal and the existential constructs. We then describe algorithms for automatically checking the correctness of workflows and for automatic workflow generation.
14239575
Semantics based verification and synthesis of BPEL4WS abstract processes
We introduce a logic model to formally specify the semantics of workflows and their composite tasks described as BPEL4WS abstract processes. Based on the model, we present a set of inference rules to deduce the strongest postcondition and weakest precondition of a workflow and demonstrate that automatic workflow verification is possible due to the restrictions on data manipulation in an abstract process. We then sketch an algorithm that automatically synthesizes a workflow given its specification and a task library.
28843712
Generalized Recursive Splitting Algorithms for Learning Hybrid Concepts
This paper describes the Competitive Relation Learner (CRL), a generalized recursive splitting algorithm capable of producing a wide range of hybrid concept representations through the competitive application of multiple learning strategies, multiple decomposition strategies, and multiple decomposition evaluation strategies. Experimental results are reported that demonstrate CRL's ability to outperform several well known fixed-bias strategies.
30203063
Discourse model for collaborative design
Abstract A Discourse Model, including a structure and a process, is developed that provides software support for collaborative engineering design. The model shares characteristics of other design systems in the literature, including frames, constraints, semantic networks, and libraries of sharable design objects. It contributes a new model for conflict-aware agents, dynamic identification and dissemination of agent interest sets, a virtual workspace language, automatic detection of conflict, and a unique protocol for negotiation that ensures that interested agents have an opportunity to participate. The model is implementation independent and applicable to many research and commercial design environments currently available. An example scenario is provided in the architecture/engineering/construction domain that illustrates collaboration during the conceptual design of a fire station.
2219088
A self-coordinating approach to distributed fair queueing in ad hoc wireless networks
Distributed fair queueing in shared-medium ad hoc wireless networks is non-trivial because of the unique design challenges in such networks, such as location-dependent contention, distributed nature of ad hoc fair queueing, channel spatial reuse, and scalability in the presence of node mobility. In this paper, we seek to devise new distributed, localized, scalable and efficient solutions to this problem. We first analyze an ideal centralized fair queueing algorithm developed for ad hoc networks, and extract the desired global properties that the localized algorithms should possess. We then propose three localized fair queueing models, in which local schedulers self-coordinate their local interactions and collectively achieve the desired global properties. We further describe a novel implementation of the proposed models within the framework of the popular CSMA/CA paradigm and address several practical issues. Our simulations and analysis demonstrate the effectiveness of our proposed design.
13148267
Fair scheduling in wireless packet networks
Fair scheduling of delay and rate-sensitive packet flows over a wireless channel is not addressed effectively by most contemporary wireline fair scheduling algorithms because of two unique characteristics of wireless media: (a) bursty channel errors, and (b) location-dependent channel capacity and errors. Besides, in packet cellular networks, the base station typically performs the task of packet scheduling for both downlink and uplink flows in a cell; however a base station has only a limited knowledge of the arrival processes of uplink flows.In this paper, we propose a new model for wireless fair scheduling based on an adaptation of fluid fair queueing to handle location-dependent error bursts. We describe an ideal wireless fair scheduling algorithm which provides a packetized implementation of the fluid model while assuming full knowledge of the current channel conditions. For this algorithm, we derive the worst-case throughput and delay bounds. Finally, we describe a practical wireless scheduling algorithm which approximates the ideal algorithm. Through simulations, we show that the algorithm achieves the desirable properties identified in the wireless fluid fair queueing model.
611972
Tracking Causal Dependencies in an Active Object-Oriented Database
As active and deductive databases are applied to more complex domains (e.g. engineering design), the need to track the causality of data which has been derived by rules in the database becomes vital. Truth maintenance systems have been used in the area of artificial intelligence to track the causal dependencies of data derived from rules in knowledge-based systems. These same techniques can be applied to active object-oriented databases to provide the users with the means to track the relationships between data and rules. This paper describes the relevant features of a simple truth maintenance systems and puts forth a model of how truth maintenance systems can be integrated with an active object-oriented database, including the definition of new query operators to interpret the causal information for the end user.