890 resultados para no fit polygon


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Cutting and packing problems are found in numerous industries such as garment, wood and shipbuilding. The collision free region concept is presented, as it represents all the translations possible for an item to be inserted into a container with already placed items. The often adopted nofit polygon concept and its analogous concept inner fit polygon are used to determine the collision free region. Boolean operations involving nofit polygons and inner fit polygons are used to determine the collision free region. New robust non-regularized Boolean operations algorithm is proposed to determine the collision free region. The algorithm is capable of dealing with degenerated boundaries. This capability is important because degenerated boundaries often represent local optimal placements. A parallelized version of the algorithm is also proposed and tests are performed in order to determine the execution times of both the serial and parallel versions of the algorithm.

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Cutting and packing problems arise in a variety of industries, including garment, wood and shipbuilding. Irregular shape packing is a special case which admits irregular items and is much more complex due to the geometry of items. In order to ensure that items do not overlap and no item from the layout protrudes from the container, the collision free region concept was adopted. It represents all possible translations for a new item to be inserted into a container with already placed items. To construct a feasible layout, collision free region for each item is determined through a sequence of Boolean operations over polygons. In order to improve the speed of the algorithm, a parallel version of the layout construction was proposed and it was applied to a simulated annealing algorithm used to solve bin packing problems. Tests were performed in order to determine the speed improvement of the parallel version over the serial algorithm

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Brand loyalty is a concept that has garnered considerable interest over recent years from both marketing practitioners and academics alike. While marketers are primarily interested in ways they can generate and increase brand loyalty from their customers, academics strive to conducts research which investigates the antecedents and consequences of customer loyalty (See DeWitt, Nguyen and Marshall 2008; Russell-Bennett, McColl-Kennedy and Coote 2007).

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Significant sums of money are invested in developing technological innovations that have low levels and rates of adoption. Several approaches have been put forward in an effort to improve rates of adoption. This paper presents the results of study that examined the innovation fit of key technological innovations in the beef industry. Findings indicate that be assessing the innovation fit throughout the R&D process researchers and end users can collaborate to improve the innovation fit and the rate of adoption. The paper also put forward a model that demonstrates the linkages between R&D, adoption and innovation fit.

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The number of employees working in nonprofit organisations has grown significantly. These employees are often motivated to join these organisations by a strong desire to fulfil the particular vision and mission of that nonprofit (such as helping the community). While the effects of employee organisation value congruence on job-related attitudes are reasonably well documented, little consideration has been given to the nonprofit context and also perceptions of work stressors and health outcomes. A sample on nonprofit employees from a human services organisation (N = 181) was surveyed with results suggesting that value congruence was related to lower perceptions of role stressors. The results further revealed that value congruence was related to less favourable employee health in some circumstances. Outcomes are discussed in terms of theoretical and practical importance.

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Occupational stress has been a concern for human resource managers in light of research investigating the work stressor-employee adjustment relationship. This research has consistently demonstrated many negative effects between stressors in the workplace and employee adjustment. A considerable amount of literature also describes potential moderators of this relationship. Subjective fit with organizational culture has been established as a significant predictor of employee job-related attitudes; however, research has neglected investigation of the potential moderating effect of subjective fit in the work stressor-employee adjustment process. It was predicted that perceptions of subjective fit with the organization’s values and goals would mitigate the negative effect of work stressors on employee adjustment in an employee sample from three organizations (N ¼ 256). Hierarchical multiple regression analyses revealed support for the stress-buffering effects of high subjective fit in the prediction of physical symptoms, job satisfaction, and intentions to leave. The theoretical and practical implications of the results are discussed.

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This article examines the role of the recently introduced fair dealing exception for the purposes of parody and satire in Australian copyright law. Parody and satire, while central to Australian expression, pose a substantial challenge for copyright policy. The law is asked to strike a delicate balance between an author’s right to exploit their work, the interests of the public in stimulating free speech and critical discussion, the rights of artists who rely on existing material in creating their own expression, and the rights of all artists in their reputation and the integrity of their works. This article highlights the difficulty parodists and satirists have historically faced in Australia and examines the potential of the new fair dealing exceptions to relieve this difficulty. This article concludes that the new exceptions have the potential, if read broadly, not only to bridge the gap between humorous and non-humorous criticism, but also to allow for the use of copyright material to critique figures other than the copyright owner or author, extending to society generally. This article will argue that the new exceptions should be read broadly to further this important policy goal while also being limited in their application so as to prevent mere substitutable uses of copyright material. To achieve these twin goals, I suggest that the primary indication of fairness of an unlicensed parody should be whether or not it adds significant new expression so as not to be substitutable for the original work.

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An iterative method for the fit optimisation of a pre-contoured fracture fixation plate for a given bone data set is presented. Both plate shape optimisation and plate fit quantification are conducted in a virtual environment utilising computer graphical methods and 3D bone and plate models. Two optimised shapes of the undersurface of an existing distal medial tibia plate were generated based on a dataset of 45 3D bone models reconstructed from computed tomography image data of Japanese tibiae. The existing plate shape achieved an anatomical fit on 13% of tibiae from the dataset. Modified plate 1 achieved an anatomical fit for 42% and modified plate 2 a fit for 67% of the bones. If either modified plate 1 or plate 2 is used, then the anatomical fit can be increased to 82% for the same dataset. Issues pertaining to any further improvement in plate fit/shape are discussed.

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There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros