Cost-sensitive web-based information acquisition for record matching

Ph.DDOCTOR OF PHILOSOPH

Multi modal multi-semantic image retrieval

PhDThe rapid growth in the volume of visual information, e.g. image, and video can overwhelm users’ ability to find and access the specific visual information of interest to them. In recent years, ontology knowledge-based (KB) image information retrieval techniques have been adopted into in order to attempt to extract knowledge from these images, enhancing the retrieval performance. A KB framework is presented to promote semi-automatic annotation and semantic image retrieval using multimodal cues (visual features and text captions). In addition, a hierarchical structure for the KB allows metadata to be shared that supports multi-semantics (polysemy) for concepts. The framework builds up an effective knowledge base pertaining to a domain specific image collection, e.g. sports, and is able to disambiguate and assign high level semantics to ‘unannotated’ images. Local feature analysis of visual content, namely using Scale Invariant Feature Transform (SIFT) descriptors, have been deployed in the ‘Bag of Visual Words’ model (BVW) as an effective method to represent visual content information and to enhance its classification and retrieval. Local features are more useful than global features, e.g. colour, shape or texture, as they are invariant to image scale, orientation and camera angle. An innovative approach is proposed for the representation, annotation and retrieval of visual content using a hybrid technique based upon the use of an unstructured visual word and upon a (structured) hierarchical ontology KB model. The structural model facilitates the disambiguation of unstructured visual words and a more effective classification of visual content, compared to a vector space model, through exploiting local conceptual structures and their relationships. The key contributions of this framework in using local features for image representation include: first, a method to generate visual words using the semantic local adaptive clustering (SLAC) algorithm which takes term weight and spatial locations of keypoints into account. Consequently, the semantic information is preserved. Second a technique is used to detect the domain specific ‘non-informative visual words’ which are ineffective at representing the content of visual data and degrade its categorisation ability. Third, a method to combine an ontology model with xi a visual word model to resolve synonym (visual heterogeneity) and polysemy problems, is proposed. The experimental results show that this approach can discover semantically meaningful visual content descriptions and recognise specific events, e.g., sports events, depicted in images efficiently. Since discovering the semantics of an image is an extremely challenging problem, one promising approach to enhance visual content interpretation is to use any associated textual information that accompanies an image, as a cue to predict the meaning of an image, by transforming this textual information into a structured annotation for an image e.g. using XML, RDF, OWL or MPEG-7. Although, text and image are distinct types of information representation and modality, there are some strong, invariant, implicit, connections between images and any accompanying text information. Semantic analysis of image captions can be used by image retrieval systems to retrieve selected images more precisely. To do this, a Natural Language Processing (NLP) is exploited firstly in order to extract concepts from image captions. Next, an ontology-based knowledge model is deployed in order to resolve natural language ambiguities. To deal with the accompanying text information, two methods to extract knowledge from textual information have been proposed. First, metadata can be extracted automatically from text captions and restructured with respect to a semantic model. Second, the use of LSI in relation to a domain-specific ontology-based knowledge model enables the combined framework to tolerate ambiguities and variations (incompleteness) of metadata. The use of the ontology-based knowledge model allows the system to find indirectly relevant concepts in image captions and thus leverage these to represent the semantics of images at a higher level. Experimental results show that the proposed framework significantly enhances image retrieval and leads to narrowing of the semantic gap between lower level machinederived and higher level human-understandable conceptualisation

INTEGRATION PROCESSES QUALITY IN HETEROGENOUS ENVIRONMENTS

It presents heterogeneous distributed software applications concept. It describes integration techniques. It defines quality of integration processes regarding heterogeneous environments. It defines quality metrics for heterogeneous e-commerce applications.integration, distributed environments, software process

Newmarket Open Space Conservation Plan

Open spaces – forests, fields, wetlands, floodplains, salt marshes, rivers and streams – are integral to our community. These lands and waters that thread through our neighborhoods are a scenic reminder of our history, when people made their living by working the land. Yet we still depend on these open spaces for our health and our wellbeing. These places provide many “services” such as clean air, flood control, filtering pollutants and purifying drinking water, natural pest control, plant pollination, cooler summer temperatures, and areas for relaxing, exercising and recreating. Collectively these can be thought of as a “natural services network” – a minimum framework or backbone of open spaces that offer these services to all of us regardless of age, income, or points of view. New Hampshire is transforming from a largely rural state to a mostly urban and suburban one. This trend will continue at a rapid pace as the State is expected to grow by 358,000 people (or more than 28%) from 2000 to 2025. Most of this growth will occur in the four southeastern counties, with the Town of Newmarket in the heart of this growth area. The major land use trends include loss of unfragmented forestland, lack of protected lands around public water supplies and aquifers, and loss of intact wetlands and wildlife habitat (SPNHF 2005). Many communities, including the residents of Newmarket, have acknowledged these changes and the need to conserve special places and ecosystems by supporting land use planning tools, natural resource inventories, conservation funds, and stewardship of lands. Since 2001, 83 New Hampshire towns have passed open space bond issues or appropriated funds for land acquisition worth more than $135 million (NH Center for Land Conservation Assistance). In 2002, Newmarket residents overwhelmingly passed a$2 million land acquisition bond. Landowners in our community have generously donated interest in land or easements to ensure that conservation values are protected in perpetuity. This support for land and water conservation that benefits all of us is a tribute to the community land ethic in our region. The Town of Newmarket boasts a rich diversity of natural habitats and associated plants and animals. The Lamprey and Piscassic Rivers, Great Bay Estuary, and Tuttle Swamp, to name just a few, all contribute to the sense of place and allure of the town (Map 1). Balancing the preservation of open space with responsible development, long maintained as a priority by Newmarket citizens, business owners and town officials, is necessary, as growth and all its requisite accompaniments present increasing challenges. Recent concerns about the availability of drinking water for Newmarket residents and businesses as well as the floods of 2006 reflect these challenges. As Newmarket continues to grow, so will concern over loss of natural areas, recreational opportunities, and the quality of life that residents have long enjoyed. Maintaining a network of rivers and wetlands, forests and fields throughout Newmarket for the health of the land and people requires vision, support, and action. In 1991, the Town of Newmarket hired the Smart Associates to prepare a Natural Resource Inventory and Conservation Plan. This was the beginning of efforts by the Conservation Commission to conserve important lands identified in the “Smart Report.” In the fifteen years that have elapsed since the Smart Report, Newmarket has undergone many changes, highlighting the need to revisit the current state of natural resources within the community. The Open Space Commission and Conservation Commission have led recent efforts to identify and protect conservation and recreation areas. The Planning Board and staff have led in creating effective land use planning tools that conserve open spaces while allowing orderly and thoughtful development. Together, Newmarket Open Space Conservation Plan Page 7 of 94 these boards applied for a grant from the NH Estuaries Project (NHEP) Technical Assistance Program in 2006 to develop an Open Space Plan. The NHEP awarded the grant of $6,200 to Ibis Wildlife Consulting to work with the Town of Newmarket to prepare this Plan

Trying to break new ground in aerial archaeology

Aerial reconnaissance continues to be a vital tool for landscape-oriented archaeological research. Although a variety of remote sensing platforms operate within the earth’s atmosphere, the majority of aerial archaeological information is still derived from oblique photographs collected during observer-directed reconnaissance flights, a prospection approach which has dominated archaeological aerial survey for the past century. The resulting highly biased imagery is generally catalogued in sub-optimal (spatial) databases, if at all, after which a small selection of images is orthorectified and interpreted. For decades, this has been the standard approach. Although many innovations, including digital cameras, inertial units, photogrammetry and computer vision algorithms, geographic(al) information systems and computing power have emerged, their potential has not yet been fully exploited in order to re-invent and highly optimise this crucial branch of landscape archaeology. The authors argue that a fundamental change is needed to transform the way aerial archaeologists approach data acquisition and image processing. By addressing the very core concepts of geographically biased aerial archaeological photographs and proposing new imaging technologies, data handling methods and processing procedures, this paper gives a personal opinion on how the methodological components of aerial archaeology, and specifically aerial archaeological photography, should evolve during the next decade if developing a more reliable record of our past is to be our central aim. In this paper, a possible practical solution is illustrated by outlining a turnkey aerial prospection system for total coverage survey together with a semi-automated back-end pipeline that takes care of photograph correction and image enhancement as well as the management and interpretative mapping of the resulting data products. In this way, the proposed system addresses one of many bias issues in archaeological research: the bias we impart to the visual record as a result of selective coverage. While the total coverage approach outlined here may not altogether eliminate survey bias, it can vastly increase the amount of useful information captured during a single reconnaissance flight while mitigating the discriminating effects of observer-based, on-the-fly target selection. Furthermore, the information contained in this paper should make it clear that with current technology it is feasible to do so. This can radically alter the basis for aerial prospection and move landscape archaeology forward, beyond the inherently biased patterns that are currently created by airborne archaeological prospection

A framework for utility data integration in the UK

In this paper we investigate various factors which prevent utility knowledge from being fully exploited and suggest that integration techniques can be applied to improve the quality of utility records. The paper suggests a framework which supports knowledge and data integration. The framework supports utility integration at two levels: the schema and data level. Schema level integration ensures that a single, integrated geospatial data set is available for utility enquiries. Data level integration improves utility data quality by reducing inconsistency, duplication and conflicts. Moreover, the framework is designed to preserve autonomy and distribution of utility data. The ultimate aim of the research is to produce an integrated representation of underground utility infrastructure in order to gain more accurate knowledge of the buried services. It is hoped that this approach will enable us to understand various problems associated with utility data, and to suggest some potential techniques for resolving them

CERN openlab Whitepaper on Future IT Challenges in Scientific Research

This whitepaper describes the major IT challenges in scientific research at CERN and several other European and international research laboratories and projects. Each challenge is exemplified through a set of concrete use cases drawn from the requirements of large-scale scientific programs. The paper is based on contributions from many researchers and IT experts of the participating laboratories and also input from the existing CERN openlab industrial sponsors. The views expressed in this document are those of the individual contributors and do not necessarily reflect the view of their organisations and/or affiliates

Grid-based semantic integration of heterogeneous data resources: Implementation on a HealthGrid

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise to meet this challenge in a systematic manner, making data applications more scalable and manageable. The thesis conducts a thorough investigation of the problem, the state of the art, and the related technologies, and proposes an Architecture for Semantic Integration of Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a simple mechanism for the interoperability of heterogeneous data sources in order to extract or discover information regardless of their different semantics. The constituent technologies of this architecture include Globus Toolkit (GT4) and OGSA-DAI (Open Grid Service Architecture Data Integration and Access) alongside other web services technologies such as XML (Extensive Markup Language). To show this, the ASIDS architecture was implemented and tested in a realistic setting by building an exemplar application prototype on a HealthGrid (pilot implementation). The study followed an empirical research methodology and was informed by extensive literature surveys and a critical analysis of the relevant technologies and their synergies. The two literature reviews, together with the analysis of the technology background, have provided a good overview of the current Grid and HealthGrid landscape, produced some valuable taxonomies, explored new paths by integrating technologies, and more importantly illuminated the problem and guided the research process towards a promising solution. Yet the primary contribution of this research is an approach that uses contemporary Grid technologies for integrating heterogeneous data resources that have semantically different. data fields (attributes). It has been practically demonstrated (using a prototype HealthGrid) that discovery in semantically integrated distributed data sources can be feasible by using mainstream Grid technologies, which have been shown to have some Significant advantages over non-Grid based approaches