The manualization of linguistic knowledge and the constitution of a non-sexist language

Mobilizing the notions of grammatization (AUROUX, 1992) and manualization (PUECH, 1998), we analyze two manuals in this work: Manual para o uso não sexista da linguagem: o que bem se diz bem se entende (2014, Brazil) and Nombra: la representación del femenino y el masculino en el lenguaje (1995, Spain). Both handbooks propose the use of inclusive language in which the female genre is placed in evidence in linguistic usage. Considering them as a technological tool as well as a sociocultural product of popularization of knowledge on the language, we intend to analyze how the proposal of such manuals which uphold non-sexist language, inclusive of gender, supported by laws, edicts – operates as a language policy, which seeks to control the use of language, feminizes the language and meets feminist demands that clamor for a legitimate position to women, whether in society or in its uses of the language when enunciating itself. KEYWORDS: Manuals - Non-sexist language - Woman

Towartds Computer-aided Editing of Scientific and Technical Texts

The paper discusses facilities of computer systems for editing scientific and technical texts, which partially automate functions of human editor and thus help the writer to improve text quality. Two experimental systems LINAR and CONUT developed in 90s to control the quality of Russian scientific and technical texts are briefly described; and general principles for designing more powerful editing systems are pointed out. Features of an editing system being now under development are outlined, primarily the underlying linguistic knowledge base and procedures controlling the text.

A interlíngua e o alinhamento léxico-conceitual da base de dados bilíngue REBECA

In the architecture of a natural language processing system based on linguistic knowledge, two types of component are important: the knowledge databases and the processing modules. One of the knowledge databases is the lexical database, which is responsible for providing the lexical unities and its properties to the processing modules. The systems that process two or more languages require bilingual and/or multilingual lexical databases. These databases can be constructed by aligning distinct monolingual databases. In this paper, we present the interlingua and the strategy of aligning the two monolingual databases in REBECA, which only stores concepts from the “wheeled vehicle” domain.

Discovering knowledge structures in mind maps of mental health risks

This thesis addressed the problem of risk analysis in mental healthcare, with respect to the GRiST project at Aston University. That project provides a risk-screening tool based on the knowledge of 46 experts, captured as mind maps that describe relationships between risks and patterns of behavioural cues. Mind mapping, though, fails to impose control over content, and is not considered to formally represent knowledge. In contrast, this thesis treated GRiSTs mind maps as a rich knowledge base in need of refinement; that process drew on existing techniques for designing databases and knowledge bases. Identifying well-defined mind map concepts, though, was hindered by spelling mistakes, and by ambiguity and lack of coverage in the tools used for researching words. A novel use of the Edit Distance overcame those problems, by assessing similarities between mind map texts, and between spelling mistakes and suggested corrections. That algorithm further identified stems, the shortest text string found in related word-forms. As opposed to existing approaches’ reliance on built-in linguistic knowledge, this thesis devised a novel, more flexible text-based technique. An additional tool, Correspondence Analysis, found patterns in word usage that allowed machines to determine likely intended meanings for ambiguous words. Correspondence Analysis further produced clusters of related concepts, which in turn drove the automatic generation of novel mind maps. Such maps underpinned adjuncts to the mind mapping software used by GRiST; one such new facility generated novel mind maps, to reflect the collected expert knowledge on any specified concept. Mind maps from GRiST are stored as XML, which suggested storing them in an XML database. In fact, the entire approach here is ”XML-centric”, in that all stages rely on XML as far as possible. A XML-based query language allows user to retrieve information from the mind map knowledge base. The approach, it was concluded, will prove valuable to mind mapping in general, and to detecting patterns in any type of digital information.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Systematising knowledge management in projects

Purpose – The purpose of this paper is to provide a practicable systems-based approach to knowledge management (KM) in a project environment, to encourage organisations to unlock the value in their review processes. It relies on knowledge capture and storage at decision review points, to enrich individual, team and organisational learning during the project life cycle. The project's phases are typically represented horizontally with deliverables (objectives) or project "promises" as the desirable outcomes. The purpose of this paper is to give expression through introducing a vertical dimension to facilitate the KM process. A model is proposed that conceptualises project-specific knowledge drawing on and feeding into the organisation's knowledge management system (KMS) at tactical and strategic levels. Design/methodology/approach – This conceptual paper links concepts from systems theory with KM, to produce a model to identify, collate, and optimise project-based knowledge and integrate it into the management process. Findings – The application of the system theory approach enriches the knowledge generated by a project, and feeds it into the next phase of that project. At the same time, it contributes to the individual's and project team's KM, specifies possible courses of action, together with risks, costs and benefits and thus it expands the organisation's higher level KMS. Research limitations/implications – The concept suggests that the knowledge capture, storage and sharing process may best be undertaken holistically, in view of the systems relationships between the tasks. Systems theory structures this process. Research opportunities include studying the interfaces between levels of KM, in relation to the project's progress. Practical implications – Reconceptualisation of the project as a knowledge creation process may improve the project's progress as well as add to the individual's, project team's, and wider organisation's knowledge base. An example is given. Originality/value – This paper illuminates the broader potential of under-utilised opportunities in well-known management approaches to add dimension to the business project, of knowledge creation, storage and sharing.

Conceptual framework for managing knowledge of police deviance

This is a conceptual article on police deviance and its multi-faceted forms. It seeks to address the lack of an adequately formulated framework in the literature of the breadth and depth of police misconduct and corruption. The article argues for the use of a proposed ‘sliding scale’ of police deviance by examining the nature, extent and progression of police deviance and crime using research in Australia and Canada as illustrative case studies. This sliding scale is designed to research, capture and store, and hence extend the knowledge base of what constitutes police deviance at the level of the individual, the group and the organisational contexts of policing. As such, the conceptual framework is a robust yet flexible research tool and its utility as a sliding scale constitutes a step forward in advancing the knowledge on police deviance and criminality through adopting an integrated and holistic approach to managing such knowledge.

Knowledge-based approach for planning healthy cities : the case of Logan-Beaudesert, Australia

Introduction - The planning for healthy cities faces significant challenges due to lack of effective information, systems and a framework to organise that information. Such a framework is critical in order to make accessible and informed decisions for planning healthy cities. The challenges for planning healthy cities have been magnified by the rise of the healthy cities movement, as a result of which, there have been more frequent calls for localised, collaborative and knowledge-based decisions. Some studies have suggested that the use of a ‘knowledge-based’ approach to planning will enhance the accuracy and quality decision-making by improving the availability of data and information for health service planners and may also lead to increased collaboration between stakeholders and the community. A knowledge-based or evidence-based approach to decision-making can provide an ‘out-of-the-box’ thinking through the use of technology during decision-making processes. Minimal research has been conducted in this area to date, especially in terms of evaluating the impact of adopting knowledge-based approach on stakeholders, policy-makers and decision-makers within health planning initiatives. Purpose – The purpose of the paper is to present an integrated method that has been developed to facilitate a knowledge-based decision-making process to assist health planning Methodology – Specifically, the paper describes the participatory process that has been adopted to develop an online Geographic Information System (GIS)-based Decision Support System (DSS) for health planners. Value – Conceptually, it is an application of Healthy Cities and Knowledge Cities approaches which are linked together. Specifically, it is a unique settings-based initiative designed to plan for and improve the health capacity of Logan-Beaudesert area, Australia. This setting-based initiative is named as the Logan-Beaudesert Health Coalition (LBHC). Practical implications - The paper outlines the application of a knowledge-based approach to the development of a healthy city. Also, it focuses on the need for widespread use of this approach as a tool for enhancing community-based health coalition decision making processes.

Teachers’ conceptions of essential knowledge for integrated social education : a middle years of schooling perspective from Australia

Integrated social education in Australia is a divisive educational issue. The last decade has been marked by a controversial integrated social studies curriculum called Studies of Society and Environment (SOSE) where history, geography and environmental studies were integrated with civics and citizenship. The introduction of a compulsory K-10 Australian Curriculum from 2011, however, marks the return to history and geography and the abandonment of SOSE. Curriculum reform aside, what do teachers think is essential knowledge for middle years social education? The paper reports on a phenomenographical exploration of thirty-one middle school teachers’ conceptions of essential knowledge for SOSE. Framed by Shulman’s (1986, 1987) theoretical framework of the knowledge base for teaching, the research identified seven qualitatively different ways of understanding essential knowledge for integrated social education. The study indicates a practice-based theorization of integrated social education that justifies attention to disciplinary process and teacher identity in middle school social education.

Evaluation of accessibility for knowledge-based cities

Purpose: The purpose of the paper is to develop a framework for evaluation of accessibility for knowledge based cities. ----- ----- Design/methodology/approach: This approach notifies common mistakes and problems in accessibility assessment for knowledge cities. ----- ----- Originality/value: Accessibility plays a key role in transport sustainability and recognizes the crucial links between transport and sustainable goals like air quality, environmental resource consumption & social equity. In knowledge cities, accessibility has significant effects on quality of life and social equity by improving the mobility of people and goods. Accessibility also influences patterns of growth and economic health by providing access to land. Accessibility is not only one of the components of knowledge cities but also affects other elements of knowledge cities directly or indirectly. ----- ----- Practical implications: The outcomes of the application will be helpful for developing particular methodologies for evaluating knowledge cities. On other words, this methodology attempts to develop an assessment procedure for examining accessibility of knowledge-based cities.

Knowledge-based development for cities and societies : integrated multi-level approaches

Over the past twenty years, the conventional knowledge management approach has evolved into a strategic management approach that has found applications and opportunities outside of business, in society at large, through education, urban development, governance, and healthcare, amongst others. Knowledge-Based Development for Cities and Socieities: Integrated Multi-Level Approaches enlightens the concepts and challenges of knowledge management for both urban environments and entire regions, enhancing the expertise and knowledge of scholars, resdearchers, practitioners, managers and urban developers in the development of successful knowledge-based development policies, creation of knowledte cities and prosperous knowledge societies. This reference creates large knowledge base for scholars, managers and urban developers and increases the awareness of the role of knowledge cities and knowledge socieiteis in the knowledge era, as well as of the challenges and opportunities for future research.

Knowledge to deal with challenges to science education from without and within

This chapter focuses on two challenges to science teachers’ knowledge that Fensham identifies as having recently emerged—one a challenge from beyond Science and the other a challenge from within Science. Both challenges stem from common features of contemporary society, namely, its complexity and uncertainty. Both also confront science teachers with teaching situations that contrast markedly with the simplicity and certainty that have been characteristic of most school science education, and hence both present new demands for science teachers’ knowledge and skill. The first, the challenge from without Science, comes from the new world of work and the “knowledge society”. Regardless of their success in traditional school learning, many young persons in many modern economies are now seen as lacking other knowledge and skills that are essential for their personal, social and economic life. The second, the challenge from within Science, derives from changing notions of the nature of science itself. If the complexity and uncertainty of the knowledge society demand new understandings and contributions from science teachers, these are certainly matched by the demands that are posed by the role of complexity and uncertainty in science itself.

The impact of knowledge integration on enterprise system success

Despite promising benefits and advantages, there are reports of failures and low realisation of benefits in Enterprise System (ES) initiatives. Among the research on the factors that influence ES success, there is a dearth of studies on the knowledge implications of multiple end-user groups using the same ES application. An ES facilitates the work of several user groups, ranging from strategic management, management, to operational staff, all using the same system for multiple objectives. Given the fundamental characteristics of ES – integration of modules, business process views, and aspects of information transparency – it is necessary that all frequent end-users share a reasonable amount of common knowledge and integrate their knowledge to yield new knowledge. Recent literature on ES implementation highlights the importance of Knowledge Integration (KI) for implementation success. Unfortunately, the importance of KI is often overlooked and little about the role of KI in ES success is known. Many organisations do not achieve the potential benefits from their ES investment because they do not consider the need or their ability to integrate their employees’ knowledge. This study is designed to improve our understanding of the influence of KI among ES end-users on operational ES success. The three objectives of the study are: (I) to identify and validate the antecedents of KI effectiveness, (II) to investigate the impact of KI effectiveness on the goodness of individuals’ ES-knowledge base, and (III) to examine the impact of the goodness of individuals’ ES-knowledge base on the operational ES success. For this purpose, we employ the KI factors identified by Grant (1996) and an IS-impact measurement model from the work of Gable et al. (2008) to examine ES success. The study derives its findings from data gathered from six Malaysian companies in order to obtain the three-fold goal of this thesis as outlined above. The relationships between the antecedents of KI effectiveness and its consequences are tested using 188 responses to a survey representing the views of management and operational employment cohorts. Using statistical methods, we confirm three antecedents of KI effectiveness and the consequences of the antecedents on ES success are validated. The findings demonstrate a statistically positive impact of KI effectiveness of ES success, with KI effectiveness contributing to almost one-third of ES success. This research makes a number of contributions to the understanding of the influence of KI on ES success. First, based on the empirical work using a complete nomological net model, the role of KI effectiveness on ES success is evidenced. Second, the model provides a theoretical lens for a more comprehensive understanding of the impact of KI on the level of ES success. Third, restructuring the dimensions of the knowledge-based theory to fit the context of ES extends its applicability and generalisability to contemporary Information Systems. Fourth, the study develops and validates measures for the antecedents of KI effectiveness. Fifth, the study demonstrates the statistically significant positive influence of the goodness of KI on ES success. From a practical viewpoint, this study emphasises the importance of KI effectiveness as a direct antecedent of ES success. Practical lessons can be drawn from the work done in this study to empirically identify the critical factors among the antecedents of KI effectiveness that should be given attention.