17686470
Inter-enterprise business document exchange
Electronic business document interoperation is the cornerstone of business process integration. An essential issue for business document interoperation is to maintain semantic consistency of the exchanged business documents between any two autonomous business communities, where the document sender and receiver have no misunderstanding in using the exchanged documents. Existing approaches to resolving this issue either adopts document standards to map heterogeneous document elements or applies business ontologies to mediate inconsistent document elements. While these approaches are effective in certain degree, the issues of limited flexibility and evolvability in using standards and the lack of accuracy in using ontologies to mediate document elements must be explored and resolved. This paper proposes a Collaborative Document Exchange (CODEX) approach to resolving the issues. In this approach, structures and concepts of business document are separated and layered in CODEX framework. Structures provide the commonality of business documents through classified concept identifiers while concepts support particularity of business documents through collaboration.
9204785
Achieving Transparent Integration of Information, Documents and Processes
While progress is made in the individual integration of business information, documents and processes, the issue of how to vertically integrate these individually integrated results needs to be resolved. This paper proposes a novel TRANSCODE approach to the issue. The approach represents business information, business documents and business processes in three TRANSCODE structures, which are then implemented, conceptualized and reified in an integrated and flexible 3-layer TRANSCODE model
6950256
Context representation, transformation and comparison for ad hoc product data exchange
Product data exchange is the precondition of business interoperation between Web-based firms. However, millions of small and medium sized enterprises (SMEs) encode their Web product data in ad hoc formats for electronic product catalogues. This prevents product data exchange between business partners for business interoperation. To solve this problem, this paper has proposed a novel concept-centric catalogue engineering approach for representing, transforming and comparing semantic contexts in ad hoc product data exchange. In this approach, concepts and contexts of product data are specified along data exchange chain and are mapped onto several novel XML product map (XPM) documents by utilizing XML hierarchical structure and its syntax. The designed XPM has overcome the semantic limitations of XML markup and has achieved the semantic interoperation for ad hoc product data exchange.
30330476
Measurement Models for Survivability and Competitiveness of Very Large E-marketplace
E-Marketplace is a man-made profit center with emergent customer requirements. This emergence nature poses many difficulties for e-marketplace to satisfy its customers and thus affects its survivability and competitiveness. To challenge this issue, this paper has introduced a novel emergent emarketplace model, and analyzed and quantified the emergent properties of emarketplace from simple ESMs to very large complex electronic intermediary EIMs. The measurement models developed in this paper are very useful for producing dynamic interaction records appropriate for further simulation model of e-marketplaces.
37890888
Alibaba International: Building a Global Electronic Marketplace
Alibaba is the largest global electronic marketplace (GEM) in the world in terms of its participated users. It was successful due to the factors of China's foreign trade regime, the image of low product cost of China, Alibaba's contingent adaptation to users' changing requirements and e-commerce environments. Alibaba is not a technically mature GEM platform compared with the ideal functions of GEM. Suggested solution for Alibaba to continuing its success is to adopt a novel GEM connectivity model
10069776
Automated Generation of Search Tree Algorithms for Hard Graph
Modification Problems
Abstract
We present a framework for an automated 
generation of exact search tree algorithms for NP-hard problems.
The purpose of our approach is twofold—rapid development and 
improved upper bounds. 
Many search tree algorithms for various problems
in the literature are based on complicated
case distinctions. Our approach may lead to a much 
simpler process of developing and analyzing these algorithms.
Moreover, using the sheer computing power of machines it may also 
lead to improved upper bounds on
search tree sizes (i.e., faster exact solving algorithms) in comparison
with previously developed “hand-made” search trees.
Among others, such an example is given with the NP-complete 
Cluster Editing problem (also known as Correlation
Clustering on complete unweighted graphs), which asks for the minimum
number of edge additions and deletions to create a graph which is a
disjoint union of cliques. The
hand-made search tree
for Cluster Editing
had worst-case size O(2.27k), which now is improved to 
O(1.92k) due to our new method.
(Herein, k denotes the number of edge modifications allowed.)


8023010
PROSPECT-PSPP: an automatic computational pipeline for protein structure prediction
Knowledge of the detailed structure of a protein is crucial to our understanding of the biological functions of that protein. The gap between the number of solved protein structures and the number of protein sequences continues to widen rapidly in the post-genomics era due to long and expensive processes for solving structures experimentally. Computational prediction of structures from amino acid sequence has come to play a key role in narrowing the gap and has been successful in providing useful information for the biological research community. We have developed a prediction pipeline, PROSPECT-PSPP, an integration of multiple computational tools, for fully automated protein structure prediction. The pipeline consists of tools for (i) preprocessing of protein sequences, which includes signal peptide prediction, protein type prediction (membrane or soluble) and protein domain partition, (ii) secondary structure prediction, (iii) fold recognition and (iv) atomic structural model generation. The centerpiece of the pipeline is our threading-based program PROSPECT. The pipeline is implemented using SOAP (Simple Object Access Protocol), which makes it easier to share our tools and resources. The pipeline has an easy-to-use user interface and is implemented on a 64-node dual processor Linux cluster. It can be used for genome-scale protein structure prediction. The pipeline is accessible at http://csbl.bmb.uga.edu/protein_pipeline.
75279
Error Compensation in Leaf Power Problems
AbstractThe k-Leaf Power recognition problem is a particular case of graph
 power problems: For a given graph it asks whether there exists an
 unrooted tree—the k-leaf root—with leaves one-to-one labeled by
 the graph vertices and where the leaves have distance at most k iff their corresponding vertices in the graph are connected by an
 edge. Here we study "error correction" versions of k-Leaf
 Power recognition—that is, adding or deleting at most l
 edges to generate a graph that has a k-leaf root. We provide
 several NP-completeness results in this context, and we show that
 the NP-complete Closest 3-Leaf Power problem (the error
 correction version of 3-Leaf Power) is fixed-parameter
 tractable with respect to the number of edge modifications or vertex
 deletions in the given graph. Thus, we provide the seemingly first
 nontrivial positive algorithmic results in the field of error
 compensation for leaf power problems with k > 2. To this end, as a
 result of independent interest, we develop a forbidden subgraph
 characterization of graphs with 3-leaf roots.
14425036
Parameterized Intractability of Distinguishing Substring Selection
Abstract
A central question in computational biology is the design of genetic
markers to distinguish between two given sets of (DNA) sequences. This question is formalized as 
the NP-complete Distinguishing Substring Selection problem (DSSS for short) which asks, given a set of "good" strings and a set of "bad" strings, for a solution string which is, with respect to the Hamming metric, "away" from the good strings and "close" to the bad strings. More precisely, given integers dg, db, and L, we ask for a length-L string s such that s has Hamming distance at least dg to every length-L substring of the good strings and such that every bad string has a length-L substring with Hamming distance at most db to s. Studying the parameterized complexity of DSSS, we show that, already for binary alphabet, DSSS is W[1]-hard with respect to its natural parameters. This, in particular, implies that a recently given polynomial-time approximation scheme (PTAS) by Deng et al. cannot be replaced by a so-called efficient polynomial-time approximation scheme (EPTAS) unless an unlikely collapse in parameterized complexity theory occurs. This is seemingly the first computational biology problem for which such a border between PTAS (which exists) and EPTAS (which is unlikely to exist) could be established. By way of contrast, for a special case of DSSS, we present an exact fixed-parameter algorithm solving the problem efficiently. In this way we also exhibit a sharp border between fixed-parameter tractability and intractability results.

6234679
A Model-based Approach to Hair Region Segmentation
Hair regions represent an important external feature in many tasks involving the processing of human faces. Currently, the task of locating the hair region in a facial image requires manual intervention. In this paper we examine the different aspects of the hair region segmentation problem and develop an automatic system for such a problem. The system incorporates the human knowledge on where the hair is usually located in a facial image. Segmentation is performed via the classification of image pixels and is based on both textural and geometrical features. Experiments have shown that the segmentation results are generally satisfactory and are at least comparable to the performance of manual extraction.