415,711 research outputs found

    Life-cycle assessment of buildings: a Review

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    Life-Cycle Assessment (LCA) is one of various management tools for evaluating environmental concerns. This paper reviews LCA from a buildings perspective. It highlights the need for its use within the building sector, and the importance of LCA as a decision making support tool. It discusses LCA methodologies and applications within the building sector, reviewing some of the life-cycle studies applied to buildings or building materials and component combinations within the last fifteen years in Europe and the United States. It highlights the problems of a lack of an internationally comparable and agreed data inventory and assessment methodology which hinder the application of LCA within the building industry. It identifies key areas for future research as (i) the whole process of construction, (ii) the relative weighting of different environmental impacts and (iii) applications in developing countries

    Current Results of the EC-sponsored Catchment Modelling (CatchMod) Cluster

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    To support the Water Framework Directive implementation, much research has been commissioned at both national and European levels. CatchMod is a cluster of these projects, which is focusing on the development of computational catchment models and related tools. This paper presents an overview of the results of the CatchMod cluster to dat

    Modeling the object-oriented software process: OPEN and the unified process

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    A short introduction to software process modeling is presented, particularly object-oriented modeling. Two major industrial process models are discussed: the OPEN model and the Unified Process model. In more detail, the quality assurance in the Unified Process tool (formally called Objectory) is reviewed

    Comparing and Combining Sentiment Analysis Methods

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    Several messages express opinions about events, products, and services, political views or even their author's emotional state and mood. Sentiment analysis has been used in several applications including analysis of the repercussions of events in social networks, analysis of opinions about products and services, and simply to better understand aspects of social communication in Online Social Networks (OSNs). There are multiple methods for measuring sentiments, including lexical-based approaches and supervised machine learning methods. Despite the wide use and popularity of some methods, it is unclear which method is better for identifying the polarity (i.e., positive or negative) of a message as the current literature does not provide a method of comparison among existing methods. Such a comparison is crucial for understanding the potential limitations, advantages, and disadvantages of popular methods in analyzing the content of OSNs messages. Our study aims at filling this gap by presenting comparisons of eight popular sentiment analysis methods in terms of coverage (i.e., the fraction of messages whose sentiment is identified) and agreement (i.e., the fraction of identified sentiments that are in tune with ground truth). We develop a new method that combines existing approaches, providing the best coverage results and competitive agreement. We also present a free Web service called iFeel, which provides an open API for accessing and comparing results across different sentiment methods for a given text.Comment: Proceedings of the first ACM conference on Online social networks (2013) 27-3

    A comparison of forensic toolkits and mass market data recovery applications

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    Digital forensic application suites are large, expensive, complex software products, offering a range of functions to assist in the investigation of digital artifacts. Several authors have raised concerns as to the reliability of evidence derived from these products. This is of particular concern, given that many forensic suites are closed source and therefore can only be subject to black box evaluation. In addition, many of the individual functions integrated into forensic suites are available as commercial stand-alone products, typically at a much lower cost, or even free. This paper reports research which compared (rather than individually evaluated) the data recovery function of two forensic suites and three stand alone `non-forensic' commercial applications. The research demonstrates that, for this function at least, the commercial data recovery tools provide comparable performance to that of the forensic software suites. In addition, the research demonstrates that there is some variation in results presented by all of the data recovery tools

    A framework for developing engineering design ontologies within the aerospace industry

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    This paper presents a framework for developing engineering design ontologies within the aerospace industry. The aim of this approach is to strengthen the modularity and reuse of engineering design ontologies to support knowledge management initiatives within the aerospace industry. Successful development and effective utilisation of engineering ontologies strongly depends on the method/framework used to develop them. Ensuring modularity in ontology design is essential for engineering design activities due to the complexity of knowledge that is required to be brought together to support the product design decision-making process. The proposed approach adopts best practices from previous ontology development methods, but focuses on encouraging modular architectural ontology design. The framework is comprised of three phases namely: (1) Ontology design and development; (2) Ontology validation and (3) Implementation of ontology structure. A qualitative research methodology is employed which is composed of four phases. The first phase defines the capture of knowledge required for the framework development, followed by the ontology framework development, iterative refinement of engineering ontologies and ontology validation through case studies and experts’ opinion. The ontology-based framework is applied in the combustor and casing aerospace engineering domain. The modular ontologies developed as a result of applying the framework and are used in a case study to restructure and improve the accessibility of information on a product design information-sharing platform. Additionally, domain experts within the aerospace industry validated the strengths, benefits and limitations of the framework. Due to the modular nature of the developed ontologies, they were also employed to support other project initiatives within the case study company such as role-based computing (RBC), IT modernisation activity and knowledge management implementation across the sponsoring organisation. The major benefit of this approach is in the reduction of man-hours required for maintaining engineering design ontologies. Furthermore, this approach strengthens reuse of ontology knowledge and encourages modularity in the design and development of engineering ontologies

    Changing Tools Changing Attitudes: Effects of introducing a computer system to promote learning at work

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    The use of computer-supported collaborative learning (CSCL) tools to manage and support learning at work offers a lot of advantages, such as the increase in the availability and access to knowledge. However, computer systems also introduce new ways of doing things, which may impact on their acceptability and usage in an organisation. The study considers the issue of re-mediating human activity through the introduction of a CSCL system to support collaborative organisational learning (COL) activities as a way of promoting learning at work. A comparative study into the effects of remediating work practices in an organisation was conducted 'before' and 'after' the introduction of a CSCL system using three selected constitutive elements of COL namely: collaboration, knowledge sharing and interactivity. The study used activity theory as a framework for examining the support mechanisms for the selected elements of COL from a social and cultural perspective in terms of how they occur, and how they are supported in context. Findings highlighted the importance of accounting for social and cultural issues relating to the tool user, prior to the introduction of a CSCL system to support learning at work, as these could impact on the usage and acceptability of such a tool
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