15 resultados para Intelligent Design

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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The growing visibility of various forms of creationism in Northern Ireland raises issues for science education. Attempts have been made at political levels to have such “alternatives” to evolution taught in the science classroom, and the issue has received coverage in local press and media. A sample of 112 pre-service science teachers answered a survey on attitudes toward evolution. Preliminary analysis revealed many of these new teachers held views contrary to scientific consensus—over one fifth doubt the evidence for human evolution, and over one quarter dispute the common ancestry of life. Over two thirds indicated a preference for teaching a “range of theories” regarding these issues in science. In addition, 49 pre-service biology teachers viewed a DVD resource promoting “intelligent design” and completed an evaluation of it. The biology teachers also took part in either focus groups or additional questionnaires. A majority took the resource at face value and made positive comments regarding its utility. Many articulated views contrary to the stated positions of science academies, professional associations, and the UK government teaching directives regarding creationism. Most indicated a perception that intelligent design is legitimate science and that there is a scientific “controversy” regarding the legitimacy of evolution. Concern is raised over the ability of these new teachers to distinguish between scientific and non-scientific theories. The suggestion is made that the issue should be addressed directly with pre-service science teachers to make clear the status of such “alternatives.” The paper raises implications for science education and questions for further research.

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This paper presents an approach to develop an intelligent digital mock-up (DMU) through integration of design and manufacturing disciplines to enable a better understanding of assembly related issues during design evolution. The intelligent DMU will contain tolerance information related to manufacturing capabilities so it can be used as a source for assembly simulations of realistic models to support the manufacturing decision making process within the design domain related to tolerance build ups. A literature review of the contributing research areas is presented, from which identification of the need for an intelligent DMU has been developed. The proposed methodology including the applications of cellular modelling and potential features of the intelligent DMU are presented and explained. Finally a conclusion examines the work to date and the future work to achieve an intelligent DMU.

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The implementation of effective time analysis methods fast and accurately in the era of digital manufacturing has become a significant challenge for aerospace manufacturers hoping to build and maintain a competitive advantage. This paper proposes a structure oriented, knowledge-based approach for intelligent time analysis of aircraft assembly processes within a digital manufacturing framework. A knowledge system is developed so that the design knowledge can be intelligently retrieved for implementing assembly time analysis automatically. A time estimation method based on MOST, is reviewed and employed. Knowledge capture, transfer and storage within the digital manufacturing environment are extensively discussed. Configured plantypes, GUIs and functional modules are designed and developed for the automated time analysis. An exemplar study using an aircraft panel assembly from a regional jet is also presented. Although the method currently focuses on aircraft assembly, it can also be well utilized in other industry sectors, such as transportation, automobile and shipbuilding. The main contribution of the work is to present a methodology that facilitates the integration of time analysis with design and manufacturing using a digital manufacturing platform solution.

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Three issues usually are associated with threat prevention intelligent surveillance systems. First, the fusion and interpretation of large scale incomplete heterogeneous information; second, the demand of effectively predicting suspects’ intention and ranking the potential threats posed by each suspect; third, strategies of allocating limited security resources (e.g., the dispatch of security team) to prevent a suspect’s further actions towards critical assets. However, in the literature, these three issues are seldomly considered together in a sensor network based intelligent surveillance framework. To address
this problem, in this paper, we propose a multi-level decision support framework for in-time reaction in intelligent surveillance. More specifically, based on a multi-criteria event modeling framework, we design a method to predict the most plausible intention of a suspect. Following this, a decision support model is proposed to rank each suspect based on their threat severity and to determine resource allocation strategies. Finally, formal properties are discussed to justify our framework.

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This paper presents an automated design framework for the development of individual part forming tools for a composite stiffener. The framework uses parametrically developed design geometries for both the part and its layup tool. The framework has been developed with a functioning user interface where part / tool combinations are passed to a virtual environment for utility based assessment of their features and assemblability characteristics. The work demonstrates clear benefits in process design methods with conventional design timelines reduced from hours and days to minutes and seconds. The methods developed here were able to produce a digital mock up of a component with its associated layup tool in less than 3 minutes. The virtual environment presenting the design to the designer for interactive assembly planning was generated in 20 seconds. Challenges still exist in determining the level of reality required to provide an effective learning environment in the virtual world. Full representation of physical phenomena such as gravity, part clashes and the representation of standard build functions require further work to represent real physical phenomena more accurately.

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The popularity of Computing degrees in the UK has been increasing significantly over the past number of years. In Northern Ireland, from 2007 to 2015, there has been a 40% increase in acceptances to Computer Science degrees with England seeing a 60% increase over the same period (UCAS, 2016). However, this is tainted as Computer Science degrees also continue to maintain the highest dropout rates.
In Queen’s University Belfast we currently have a Level 1 intake of over 400 students across a number of computing pathways. Our drive as staff is to empower and motivate the students to fully engage with the course content. All students take a Java programming module the aim of which is to provide an understanding of the basic principles of object-oriented design. In order to assess these skills, we have developed Jigsaw Java as an innovative assessment tool offering intelligent, semi-supervised automated marking of code.
Jigsaw Java allows students to answer programming questions using a drag-and-drop interface to place code fragments into position. Their answer is compared to the sample solution and if it matches, marks are allocated accordingly. However, if a match is not found then the corresponding code is executed using sample data to determine if its logic is acceptable. If it is, the solution is flagged to be checked by staff and if satisfactory is saved as an alternative solution. This means that appropriate marks can be allocated and should another student have submitted the same placement of code fragments this does not need to be executed or checked again. Rather the system now knows how to assess it.
Jigsaw Java is also able to consider partial marks dependent on code placement and will “learn” over time. Given the number of students, Jigsaw Java will improve the consistency and timeliness of marking.

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This paper examines the integration of a tolerance design process within the Computer-Aided Design (CAD) environment having identified the potential to create an intelligent Digital Mock-Up [1]. The tolerancing process is complex in nature and as such reliance on Computer-Aided Tolerancing (CAT) software and domain experts can create a disconnect between the design and manufacturing disciplines It is necessary to implement the tolerance design procedure at the earliest opportunity to integrate both disciplines and to reduce workload in tolerance analysis and allocation at critical stages in product development when production is imminent.
The work seeks to develop a methodology that will allow for a preliminary tolerance allocation procedure within CAD. An approach to tolerance allocation based on sensitivity analysis is implemented on a simple assembly to review its contribution to an intelligent DMU. The procedure is developed using Python scripting for CATIA V5, with analysis results aligning with those in literature. A review of its implementation and requirements is presented.