920 resultados para design innovation


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Effective natural resource policy depends on knowing what is needed to sustain a resource and building the capacity to identify, develop, and implement flexible policies. This retrospective case study applies resilience concepts to a 16-year citizen science program and vernal pool regulatory development process in Maine, USA. We describe how citizen science improved adaptive capacities for innovative and effective policies to regulate vernal pools. We identified two core program elements that allowed people to act within narrow windows of opportunity for policy transformation, including (1) the simultaneous generation of useful, credible scientific knowledge and construction of networks among diverse institutions, and (2) the formation of diverse leadership that promoted individual and collective abilities to identify problems and propose policy solutions. If citizen science program leaders want to promote social-ecological systems resilience and natural resource policies as outcomes, we recommend they create a system for internal project evaluation, publish scientific studies using citizen science data, pursue resources for program sustainability, and plan for leadership diversity and informal networks to foster adaptive governance.

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This paper represents a new theorization of the role of location-based games (LBGs) as potentially playing specific roles in peoples’ access to the culture of cities [22]. A LBG is a game that employs mobile technologies as tools for game play in real world environments. We argue that as a new genre in the field of mobile entertainment, research in this area tends to be preoccupied with the newness of the technology and its commercial possibilities. However, this overlooks its potential to contribute to cultural production. We argue that the potential to contribute to cultural production lies in the capacity of these experiences to enhance relationships between specific groups and new urban spaces. Given that developers can design LBGs to be played with everyday devices in everyday environments, what new creative opportunities are available to everyday people?

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This paper suggests ways for educators and designers to understand and merge priorities in order to inform the development of mobile learning (m-learning) applications that maximise user experiences and hence learning opportunities. It outlines a User Experience Design (UXD) theory and development process that requires designers to conduct a thorough initial contextual inquiry into a particular domain in order to set project priorities and development guidelines. A matrix that identifies the key contextual considerations namely the social, cultural, spatial, technical and temporal constructs of any domain is presented as a vital tool for achieving successful UXD. The frame of reference provided by this matrix ensures that decisions made throughout the design process are attributable to a desired user experience. To illustrate how the proposed UXD theory and development process supports the creation of effective m-learning applications, this paper documents the development process of MILK (Mobile Informal Learning Kit). MILK is a support tool that allows teachers and students to develop event paths that consist of a series SMS question and answer messages that lead players through a series of checkpoints between point A and point B. These event paths can be designed to suit desired learning scenarios and can be used to explore a particular place or subject. They can also be designed to facilitate formal or informal learning experiences.

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In this paper we explore what is required of a User Interface (UI) design in order to encourage participation around playing and creating Location-Based Games (LBGs). To base our research in practice, we present Cipher Cities, a web based system. Through the design of this system, we investigate how UI design can provide tools for complex content creation to compliment and encourage the use of mobile phones for designing, distributing, and playing LBGs. Furthermore we discuss how UI design can promote and support socialisation around LBGs through the design of functional interface components and services such as groups, user profiles, and player status listings.

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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.

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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.

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In a typical large office block, by far the largest lifetime expense is the salaries of the workers - 84% for salaries compared with : office rent (14%), total energy (1%), and maintenance (1%). The key drive for business is therefore the maximisation of the productivity of the employees as this is the largest cost. Reducing total energy use by 50% will not produce the same financial return as 1% productivity improvement? The aim of the project which led to this review of the literature was to understand as far as possible the state of knowledge internationally about how the indoor environment of buildings does influence occupants and the impact this influence may have on the total cost of ownership of buildings. Therefore one of the main focus areas for the literature has been identifying whether there is a link between productivity and health of building occupants and the indoor environment. Productivity is both easy to define - the ratio of output to input - but at the same time very hard to measure in a relatively small environment where individual contributions can influence the results, in particular social interactions. Health impacts from a building environment are also difficult to measure well, as establishing casual links between the indoor environment and a particular health issue can be very difficult. All of those issues are canvassed in the literature reported here. Humans are surprisingly adaptive to different physical environments, but the workplace should not test the limits of human adaptability. Physiological models of stress, for example, accept that the body has a finite amount of adaptive energy available to cope with stress. The importance of, and this projects' focus on, the physical setting within the integrated system of high performance workplaces, means this literature survey explores research which has been undertaken on both physical and social aspects of the built environment. The literature has been largely classified in several different ways, according to the classification scheme shown below. There is still some inconsistency in the use of keywords, which is being addressed and greater uniformity will be developed for a CD version of this literature, enabling searching using this classification scheme.

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An important aspect of designing any product is validation. Virtual design process (VDP) is an alternative to hardware prototyping in which analysis of designs can be done without manufacturing physical samples. In recent years, VDP have been generated either for animation or filming applications. This paper proposes a virtual reality design process model on one of the applications when used as a validation tool. This technique is used to generate a complete design guideline and validation tool of product design. To support the design process of a product, a virtual environment and VDP method were developed that supports validation and an initial design cycle performed by a designer. The product model car carrier is used as illustration for which virtual design was generated. The loading and unloading sequence of the model for the prototype was generated using automated reasoning techniques and was completed by interactively animating the product in the virtual environment before complete design was built. By using the VDP process critical issues like loading, unloading, Australian Design rules (ADR) and clearance analysis were done. The process would save time, money in physical sampling and to large extent in complete math generation. Since only schematic models are required, it saves time in math modelling and handling of bigger size assemblies due to complexity of the models. This extension of VDP process for design evaluation is unique and was developed, implemented successfully. In this paper a Toll logistics and J Smith and Sons car carrier which is developed under author’s responsibility has been used to illustrate our approach of generating design validation via VDP.