17676271
Ontology Modeling and Storage System for Robot Context Understanding
A mobile robot that interacts with its environment needs a machine-understandable representation of objects and their usages. We present an ontology of objects, with generic shape representations obtained through form-function reasoning. Sets of objects are associated with typical human activities, which supports context understanding. We describe an efficient ontology document storage system, which is based on stable and well-known relational databases. We first design a relational data schema appropriate for Web Ontology Language (OWL) documents, and then develop a transformation mechanism from OWL documents to the relational schema.
8273227
Mapping from BPMN-Formed Business Processes to XPDL Business Processes
In the business process management, many business process execution languages such as XPDL, BPML, BPEL4WS have been specified with different origins and goals. Most of all, XPDL proposed by WfMC has been widely used in the related applications, especially workflows whose concepts are currently interchangeable with those of business processes. On the other hand, Business Process Modeling Notation (BPMN) driven by BPMI has recently been specified as a standardized graphical notation for a business process. We can therefore commonly design and analyze various business processes using the design tools to support BPMN. Notice that a BPMN-formed business process should be converted to its semantically equivalent business process languages such as XPDL which can consequently be executed by business process engines. In this regard, we propose a transformation mechanism from BPMN-formed business processes to corresponding XPDL processes.
14075641
Business process choreography for B2B collaboration
We describe a proposed methodology for business process choreography. We focus on two types of business processes (contract and executable) and provide an interface protocol to represent interoperability patterns between them. The approach is designed to let existing processes, usually managed by an enterprise's own internal workflow management system, collaborate.
46189778
Knowledge-Based Modeling and Simulation of Network Access Control Mechanisms Representing Security Policies
It is quite necessary that an organization's information network should be equipped with a proper security system based on its scale and importance. One of the effective methods is to use the simulation model for deciding which security policy and mechanism is appropriate for the complex network. Our goal is to build a foundation of knowledge-based modeling and simulation environment for the network security. Within this environment, users can construct the simulation model of security mechanisms, apply various security policies, and quantitatively analyze their security performance against possible attacks. In this study, we considered security domain and implemented the models based on a systematic modeling approach. We enabled the model to include knowledge in modular fashion and provided well-defined guidelines for transforming security policy to concrete rule set.
27330844
Efficient processing of regular path joins using PID
Abstract XML is data that has no fixed structure. So it is hard to design a schema for storing and querying an XML data. Instead of a fixed schema, graph-based data models are widely adopted for querying XML. Queries on XML are based on paths in a data graph. A meaningful query usually has several paths in it, but much of recent research is more concerned with optimizing a single path in a query. In this paper, we present an efficient technique for processing multiple path expressions in a query. We implemented our technique and present preliminary performance results.
36995505
Fast and accurate binary halftone image resolution increasing by decision-tree learning
Digital halftone is the technique used to convert gray-scale images into binary ones, simulating gray shades by scattering appropriately black and white pixels. Sometimes, there arises the necessity of increasing the resolution of a halftone image. Some recent works have proposed a number of learning-based techniques to zoom binary images. However, they cannot consider a large neighborhood to decide the colors of the resolution-increased pixels, because their running time skyrockets with the growth of the window and the sample images sizes. The use of large window and samples is required to zoom halftone images accurately. This paper presents a new technique to zoom quickly and precisely images generated by any locally-decided halftone algorithm. It is based on decision-tree learning and it is very fast, even using a large window or large samples. The zoomed images obtained by this technique are incredibly sharp and accurate.
17995343
Automatic design of nonlinear filters by nearest neighbor learning
Nonlinear filters have been used not only in noise elimination but in a wide variety of image processing applications. Traditionally the design of a digital filter is a manual task and the user accomplishes it based on previous experiences. Unfortunately often this is not a trivial task. Thus some works try to overcome this difficulty constructing the filters automatically by computational learning neural networks, genetic algorithms and statistical estimation. These works use typical input-output images of the application as the training samples. Many different kinds of filters can be easily constructed using this approach. This paper proposes the use of nearest neighbor (NN) learning to automatic filter construction. The kd-tree (k-dimensional binary tree) is used to accelerate the NN searching. A texture recognition application example is depicted.