6849879
An ontology of quality for enterprise modelling
The TOVE Quality Ontology is the formal representation (using first-order logic) of terms, relationships, and axioms about quality which are generic beyond any specific quality domain. The assumption that quality is "conformance to requirements" is used to decompose the domain of quality into sub-domains of measurement, quality analysis, identification, and traceability. An ontological engineering methodology of posing ontological scope, stating competency questions, constructing data models and axioms, and visualization of the answering of competency questions is demonstrated with an example from the engineering of the traceability ontology.
8017153
Predicting how ontologies for the semantic web will evolve
The first phase in the evolution of the semantic Web may be the development of decentralized, adaptive ontologies for software specification.
9030536
Using enterprise reference models for automated ISO 9000 compliance evaluation
A computational enterprise model representing key facets of are organization care be are effective tool to consider where planning are enterprise information architecture. For example, a specific organization's quality management business processes and organizational structures can be represented using such a model, and then compared to a reference model of "good" processes and structures, such as the ISO 9000 standards. The specific and reference models can be represented using common entities, attributes, and relationships-comprising general schema or data model-which are then formally defined and constrained. These definitions and constraints can be used as inference rules applied to the models. Hence identification of differences between the models as quality problems can be automatically inferred, as can the analysis and correction of problems. In this paper; the TOTE ISO 9000 Micro-Theory is presented as a formal reference model of quality goodness. ISO 9000 requirements represented as inference rules in the micro-theory are applied to facts about an organization's quality management processes and structures, and conformance or nonconformance to requirements is automatically inferred. TOTE Ontologies for Quality Modeling are the common data and logical (formal definitions and constraints) models of the reference and specific organization's models. The example use of the micro-theory demonstrates enterprise model use for a pre-audit, which lowers the cost and time for improving quality through achieving ISO 9000 compliance. Since these enterprise models are constructed using ontologies, benefits of using ontologies such as model re-usability and sharability can be reaped.
6043201
MOQ: Web services ontologies for QoS and general quality evaluations
When describing web services, one of the obvious aspects that need representing is 'Quality of Service' (QoS), the capability of a web service to meet an acceptable level of service as per factors such as availability and accessibility. However, too much of a focus on developing functional QoS ontologies has led to an over-emphasis on representing solely QoS metrics and units of measurement. For instance, what does round trip time actually mean? Is the round trip time of every data item measured? Is it an average, or is every nth item measured? Is it the actual measure that is important or just the percentage of items that are beyond a certain range? Arguably existing QoS ontologies cannot readily answer many of these design questions because these questions have less to do with evaluating QoS and more to do with representing 'what is quality?' Therefore, there is an unmet need for web services ontologies that are designed at a higher level encompassing domain independent concepts, and generally applicable beyond QoS evaluations. The MOQ set of ontologies, designed from the premise that quality is 'conformance to requirements', aims to fill this need. Comprised of ontologies of requirement, measurement, traceability, and quality management systems, MOQ can be extended to encompass QoS metrics and measurement units or be designed to interoperate with existing QoS ontology. The use of MOQ minimises the ambiguity in QoS evaluations.
17616851
Designing Business Processes and Communication Structures for E-Business Using Ontology-Based Enterprise Models with Mathematical Models
Organizations are apprehensive about developing e-business systems because the endeavor is novel. If e-business is considered as the conduct of business using the Internet--a network of networks--then e-business systems design can be represented as a network design problem. This paper outlines an approach for analysis and design of business process and communications structure networks for e-business. Network design alternatives are generated by applying best practices and design principles to business requirements, using ontology-based enterprise models. Alternatives then are modeled mathematically for analysis and comparison. Domains relevant for e-business systems design are described, formally and systematically, using this approach. These formal descriptions are general axioms, used to logically and mathematically infer prescriptions for specific design problems. These descriptions and prescriptions are sharable and reusable. The mathematical models are developed using known algorithms, heuristics, and formulae. Therefore, fidelity of prescriptions based on these models can be objectively justified. Due to these characteristics, models developed using this technique are especially useful for developing novel e-business systems. An example application of this technique is presented, and research questions addressed using the approach are discussed.
1170029
Toward a secure public-key blockwise fragile authentication watermarking
In this paper, we describe some weaknesses of public-key blockwise fragile authentication watermarkings and the means to make them secure. Wong's (1998) original algorithm is not secure against a mere block cut-and-paste or the well-known birthday attack. To make it secure, some schemes have been proposed to make the signature of each block depend on the contents of its neighboring blocks. We attempt to maximize the change localization resolution using only one dependency per block with a scheme we call hash block chaining version 1 (HBC1). We then show that HBC1, as well as any neighbor-dependent scheme, are susceptible to another forgery technique that we have named a transplantation attack. We also show a new kind of birthday attack that can be effectively mounted against HBC1. To thwart these attacks, we propose using a nondeterministic digital signature together with a signature dependent scheme (HBC2). Finally, we discuss the advantages of using discrete logarithm signatures instead of RSA for watermarking.
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.
9123990
Dimension Reduction in Text Classification with Support Vector Machines
Support vector machines (SVMs) have been recognized as one of the most successful classification methods for many applications including text classification. Even though the learning ability and computational complexity of training in support vector machines may be independent of the dimension of the feature space, reducing computational complexity is an essential issue to efficiently handle a large number of terms in practical applications of text classification. In this paper, we adopt novel dimension reduction methods to reduce the dimension of the document vectors dramatically. We also introduce decision functions for the centroid-based classification algorithm and support vector classifiers to handle the classification problem where a document may belong to multiple classes. Our substantial experimental results show that with several dimension reduction methods that are designed particularly for clustered data, higher efficiency for both training and testing can be achieved without sacrificing prediction accuracy of text classification even when the dimension of the input space is significantly reduced.
15273022
Open Location-Based Service Using Secure Middleware Infrastructure in Web Services
Location-based services or LBS refers to value-added service by processing information utilizing mobile user location. For this kind of LBS, the role of security service is very important in the LBS that store and manage the location information of mobile devices and support various application services using those location information. And in all phases of these functions that include acquisition of location information, storage and management of location information, user management including authentication and information security, and management of the large-capacity location information database, safe security service must be provided. We show the security methods for open LBS in this paper.
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.