Ontology-driven web-based semantic similarity

Estimation of the degree of semantic similarity/distance between concepts is a very common problem in research areas such as natural language processing, knowledge acquisition, information retrieval or data mining. In the past, many similarity measures have been proposed, exploiting explicit knowledge—such as the structure of a taxonomy—or implicit knowledge—such as information distribution. In the former case, taxonomies and/or ontologies are used to introduce additional semantics; in the latter case, frequencies of term appearances in a corpus are considered. Classical measures based on those premises suffer from some problems: in the first case, their excessive dependency of the taxonomical/ontological structure; in the second case, the lack of semantics of a pure statistical analysis of occurrences and/or the ambiguity of estimating concept statistical distribution from term appearances. Measures based on Information Content (IC) of taxonomical concepts combine both approaches. However, they heavily depend on a properly pre-tagged and disambiguated corpus according to the ontological entities in order to compute accurate concept appearance probabilities. This limits the applicability of those measures to other ontologies –like specific domain ontologies- and massive corpus –like the Web-. In this paper, several of the presented issues are analyzed. Modifications of classical similarity measures are also proposed. They are based on a contextualized and scalable version of IC computation in the Web by exploiting taxonomical knowledge. The goal is to avoid the measures’ dependency on the corpus pre-processing to achieve reliable results and minimize language ambiguity. Our proposals are able to outperform classical approaches when using the Web for estimating concept probabilities.     

A semantic model for general purpose content-based image retrieval systems

The ‘semantic gap’ is the main challenge in content-based image retrieval. To overcome this challenge, we propose a semantic-based model to retrieve images efficiently with considering user-interested concepts. In this model, an interactive image segmentation algorithm is carried out on the query image to extract the user-interested regions. To recognize the image objects from regions, a neural network classifier is used in this model. In order to have a general-purpose system, no priori assumptions should be made regarding the nature of images in extracting features. So a large number of features should be extracted from all aspect of the image. The high dimensional feature space, not only increases the complexity and required memory, but also may reduce the efficiency and accuracy. Hence, the ant colony optimization algorithm is employed to eliminate irrelevant and redundant features. To find the most similar images to the query image, the similarity between images is measured based on their semantic objects which are defined according to a predefined ontology.     

A computational model for distributed knowledge systems with learning mechanisms

This paper addresses the issues of machine learning in distributed knowledge systems, which will consist of distributed software agents with problem solving, communication and learning functions. To develop such systems, we must analyze the roles of problem-solving and communication capabilities among knowledge systems. To facilitate the analyses, we propose a computational model: LPC. The model consists of a set of agents with (a) a knowledge base for learned concepts, (b) a knowledge base for problem solving, (c) prolog-based inference mechanisms and (d) a set of beliefs on the reliability of the other agents. Each agent can improve its own problem-solving capabilities by deductive learning from the given problems, by memory-based learning from communications between the agents and by reinforcement learning from the reliability of communications between the other agents. An experimental system of the model has been implemented in Prolog language on a Window-based personal computer. Intensive experiments have been carried out to examine the feasibility of the machine learning mechanisms of agents for problem-solving and communication capabilities. The experimental results have shown that the multiagent system improves the performance of the whole system in problem solving, when each agent has a higher learning ability or when an agent with a very high ability for problem solving joins the organization to cooperate with the other agents in problem solving. These results suggest that the proposed model is useful in analyzing the learning mechanisms applicable to distributed knowledge systems.     

A two-sector model of developing systems

A two-sector model of developing systems of V.M. Glushkov is studied; it is described by a system of nonclassical equations of the Volterra type that includes equations with variable lower limits of both first and second kinds. Numerical methods for solving systems of nonclassical Volterra equations are constructed.     

A spatio-temporal semantic model for multimedia database systemsand multimedia information systems

As more information sources become available in multimedia systems, the development of abstract semantic models for video, audio, text, and image data is becoming very important. An abstract semantic model has two requirements: it should be rich enough to provide a friendly interface of multimedia presentation synchronization schedules to the users and it should be a good programming data structure for implementation in order to control multimedia playback. An abstract semantic model based on an augmented transition network (ATN) is presented. The inputs for ATNs are modeled by multimedia input strings. Multimedia input strings provide an efficient means for iconic indexing of the temporal/spatial relations of media streams and semantic objects. An ATN and its subnetworks are used to represent the appearing sequence of media streams and semantic objects. The arc label is a substring of a multimedia input string. In this design, a presentation is driven by a multimedia input string. Each subnetwork has its own multimedia input string. Database queries relative to text, image, and video can be answered via substring matching at subnetworks. Multimedia browsing allows users the flexibility to select any part of the presentation they prefer to see. This means that the ATN and its subnetworks can be included in multimedia database systems which are controlled by a database management system (DBMS). User interactions and loops are also provided in an ATN. Therefore, ATNs provide three major capabilities: multimedia presentations, temporal/spatial multimedia database searching, and multimedia browsing     

A model for a web-based learning system

The dissemination of knowledge is currently being improved by e-learning, which consists of a combination of teaching methodologies and computer-based tools. Recently e-learning environments have started to exploit web technology to provide a simple, flexible, distributed and open platform. In this paper we propose a model for an e-learning system, aiming at sharing both course contents and teaching materials, in order to provide students with a single and uniform set of concepts to be learned, and promoting active learning by allowing the construction of courses which are personalized in terms of both contents and teaching materials, selected according to each student’s needs and capabilities. A first, open-source prototype based on the proposed model has been implemented to validate the model.     

Convergence agent model for developing u-healthcare systems

Ubiquitous networking, the interlinking of computers, consumer electronics, automobiles, home appliances, medical equipment, transportation systems, animals and plants through an overlapping of electronic spaces and physical spaces, is expected to provide an environment that enhances our lives through improved convenience, efficiency and safety in all areas.Today’s healthcare industry emphasizes safety, efficiency, patient-oriented approach, timeliness and balance. u-healthcare makes it possible to safely deliver appropriate services from any location at any time. To explain the emergence of u-healthcare, one must invoke, first of all, progress in IT and medical technology, and then the desire and willingness on the part of health care institutions to adopt the new service concept and increased health care demand. Digitalization of information, introduction of broadband communication and leaps made in healthcare technology in recent years have provided the technological capacity necessary for the achievement of u-healthcare.Based on recently reached theoretical results, integrating u-healthcare environments in virtual organizations, we proposed a methodology for the design and implementation of u-healthcare, linking the distributed mobile agents with medical entities into a convergence and collaborative environment. Despite the challenges in implementing and deploying u-healthcare, the advantages of ubiquitous healthcare are enabled by our smart model for the soft computing endowed ubiquitous. The strength of our approach is that it relates to u-healthcare a system which consists of its dual character emerging from the synergetic interaction between ubiquitous computing techniques and the mobile devices in convergence manner. We have developed a set of initial healthcare agent services on the mobile collaboration framework. We evaluate the functionality and effectiveness of our convergence mobile agent, whether the platform can manage services based on the model and whether the results of u-healthcare services discovery could satisfy user’s requirements with example cases.     

A semantic backend for content management systems

The users of a content repository express the semantics they have in mind while defining the content items and their properties, and forming them into a particular hierarchy. However, this valuable semantics is not formally expressed, and hence cannot be used to discover meaningful relationships among the content items in an automated way. Although the need is apparent, there are several challenges in explicating this semantics in a fully automated way: first, it is difficult to distinguish between data and the metadata in the repository and secondly, not all the metadata defined, such as the file size or encoding type, contribute to the meaning. More importantly, for the developed solution to have practical value, it must address the constraints of the content management system (CMS) industry: CMS industry cannot change their repositories in production use and they need a generic solution not limited to a specific repository architecture. In this article, we address all these challenges through a set of tools developed which first semi-automatically explicate the content repository semantics to a knowledge-base and establish semantic bridges between this backend knowledge-base and the content repository. The repository content is dynamic; to be able to maintain the content repository semantics while new content is created, the changes in the repository semantics are reflected onto the knowledge-base through the semantic bridges. The tool set is complemented with a search engine that make use of the explicated semantics.     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Supporting accessible hypermedia in web-based educational systems: defining an accessibility application profile for learning resources

The design and development of web-based educational systems for people with special abilities have recently attracted the attention of the research community. However, although a number of systems that claim to meet accessibility needs and preferences are proposed, most of them are typically supported by hypermedia and multimedia educational content that is specially designed for the user targeted group. Such approaches prevent their user groups (both learners and their tutors) from accessing other available resources. Therefore, it is important to be able to built generic e-learning systems that would allow the reuse of existing learning resources in different accessibility demanding applications. To this end, in this article we propose a methodology for defining an accessibility application profile that captures the accessibility properties of learning objects in a standard form and we examine its application to the IEEE Learning Object Metadata (LOM) standard.     

Timed-pNets: a communication behavioural semantic model for distributed systems

This paper presents an approach to build a communication behavioural semantic model for heterogeneous distributed systems that include synchronous and asynchronous communications. Since each node of such system has its own physical clock, it brings the challenges of correctly specifying the system time constraints. Based on the logical clocks proposed by Lamport, and CCSL proposed by Aoste team in INRIA, as well as pNets from Oasis team in INRIA, we develop timed-pNets to model communication behaviours for distributed systems. Timed-pNets are tree style hierarchical structures. Each node is associated with a timed specification which consists of a set of logical clocks and some relations on clocks. The leaves are represented by timed-pLTSs. Non-leaf nodes (called timed-pNets nodes) are synchronisation devices that synchronize the behaviours of subnets (these subnets can be leaves or non-leaf nodes). Both timed-pLTSs and timed-pNets nodes can be translated to timed specifications. All these notions and methods are illustrated on a simple use-case of car insertion from the area of intelligent transportation systems (ITS). In the end the TimeSquare tool is used to simulate and check the validity of our model.     

A computational model of time for stiff hybrid systems applied to control synthesis

Computation has quickly become of paramount importance in the design of engineered systems, both to support their features as well as their design. Tool support for high-level modeling formalisms has endowed design specifications with executable semantics. Such specifications typically include not only discrete-time and discrete-event behavior, but also continuous-time behavior that is stiff from a numerical integration perspective. The resulting stiff hybrid dynamic systems necessitate variable-step solvers to simulate the continuous-time behavior as well as solver algorithms for the simulation of discrete-time and discrete-event behavior. The combined solvers rely on complex computer code which makes it difficult to directly solve design tasks with the executable specifications. To further leverage the executable specifications in design, this work aims to formalize the semantics of stiff hybrid dynamic systems at a declarative level by removing implementation detail and only retaining ‘what’ the computer code does and not ‘how’ it does it. A stream-based approach is adopted to formalize variable-step solver semantics and to establish a computational model of time that supports discrete-time and discrete-event behavior. The corresponding declarative formalization is amenable to computational methods and it is shown how model checking can automatically generate, or synthesize, a feedforward control strategy for a stiff hybrid dynamic system. Specifically, a stamper in a surface mount device is controlled to maintain a low acceleration of the stamped component for a prescribed minimum duration of time.     

A web-based screening model for climate risk to water supply systems in the northeastern United States

The aim of this study is to describe the development and application of a web-based decision support tool (ViRTUE) for performing climate risk evaluations of water supply systems. The tool is designed for small-scale water utilities in the northeastern United States that may lack the resources for detailed climate change risk investigations. Development of this tool demonstrates a relatively new approach to web application development using the Shiny framework for the R programming language to create an interactive environment for stakeholders and water managers to explore climate vulnerabilities. Using a decision-scaling framework, the tool allows the user to perform a climate stress test to evaluate the performance and vulnerability to water supply shortfalls of local reservoir systems over a wide range of potential climate change scenarios using a generic systems model. Probabilities of future climate conditions derived from climate projections then help inform utility operators of impending risk.     

A novel algorithm for performance prediction of web-based software systems

Performance metrics can be predicted with appropriate performance models and evaluation algorithms. The goal of our work is to adapt the Mean-Value Analysis evaluation algorithm to model the behavior of the thread pool. The computation time and the computational complexity of the proposed algorithm have been provided. The limit of the response time and the throughput sequences computed by the novel algorithm has been determined. It has been shown that the proposed algorithm can be applied to performance prediction of web-based software systems in ASP.NET environment. The proposed algorithm has been validated and the correctness of performance prediction with the novel algorithm has been verified with performance measurements. Error analysis has been performed to verify the correctness of performance prediction.     

Content annotation for the semantic web: an automatic web-based approach

Semantic Annotation is required to add machine-readable content to natural language text. A global initiative such as the Semantic Web directly depends on the annotation of massive amounts of textual Web resources. However, considering the amount of those resources, a manual semantic annotation of their contents is neither feasible nor scalable. In this paper we introduce a methodology to partially annotate textual content of Web resources in an automatic and unsupervised way. It uses several well-established learning techniques and heuristics to discover relevant entities in text and to associate them to classes of an input ontology by means of linguistic patterns. It also relies on the Web information distribution to assess the degree of semantic co-relation between entities and classes of the input domain ontology. Special efforts have been put in minimizing the amount of Web accesses required to evaluate entities in order to ensure the scalability of the approach. A manual evaluation has been carried out to test the methodology for several domains showing promising results.     

Guidelines for developing educational computer programs

This paper considers the design and production of a CAL or CML package from the point of view of the programmer assisting the teacher who is going to use it. The various stages of production are illustrated by reference to two case studies, the CAMOL (Computer Assisted Management of Learning) system, and CAL packages developed for the Royal Naval College, Greenwich.     

A software environment for studying computational neural systems

UCLA-SFINX is a neural network simulation environment that enables users to simulate a wide variety of neural network models at various levels of abstraction. A network specification language enables users to construct arbitrary network structures. Small, structurally irregular networks can be modeled by explicitly defining each neuron and can be modeled by explicitly defining each neuron and corresponding connections. Very large networks with regular connectivity patterns can be implicitly specified using array constructs. Graphics support, based on X Windows System, is provided to visualize simulation results. Details of the simulation environment are described, and simulation examples are presented to demonstrate SFINX's capabilities     

A computational model for visual selection.

We propose a computational model for detecting and localizing instances from an object class in static gray-level images. We divide detection into visual selection and final classification, concentrating on the former: drastically reducing the number of candidate regions that require further, usually more intensive, processing, but with a minimum of computation and missed detections. Bottom-up processing is based on local groupings of edge fragments constrained by loose geometrical relationships. They have no a priori semantic or geometric interpretation. The role of training is to select special groupings that are moderately likely at certain places on the object but rate in the background. We show that the statistics in both populations are stable. The candidate regions are those that contain global arrangements of several local groupings. Whereas our model was not conceived to explain brain functions, it does cohere with evidence about the functions of neurons in V1 and V2, such as responses to coarse or incomplete patterns (e.g., illusory contours) and to scale and translation invariance in IT. Finally, the algorithm is applied to face and symbol detection.